WorldWideScience

Sample records for global modis cloud

  1. Radiative effects of global MODIS cloud regimes

    Science.gov (United States)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji

    2018-01-01

    We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations. PMID:29619289

  2. Radiative Effects of Global MODIS Cloud Regimes

    Science.gov (United States)

    Oraiopoulos, Lazaros; Cho, Nayeong; Lee, Dong Min; Kato, Seiji

    2016-01-01

    We update previously published MODIS global cloud regimes (CRs) using the latest MODIS cloud retrievals in the Collection 6 dataset. We implement a slightly different derivation method, investigate the composition of the regimes, and then proceed to examine several aspects of CR radiative appearance with the aid of various radiative flux datasets. Our results clearly show the CRs are radiatively distinct in terms of shortwave, longwave and their combined (total) cloud radiative effect. We show that we can clearly distinguish regimes based on whether they radiatively cool or warm the atmosphere, and thanks to radiative heating profiles to discern the vertical distribution of cooling and warming. Terra and Aqua comparisons provide information about the degree to which morning and afternoon occurrences of regimes affect the symmetry of CR radiative contribution. We examine how the radiative discrepancies among multiple irradiance datasets suffering from imperfect spatiotemporal matching depend on CR, and whether they are therefore related to the complexity of cloud structure, its interpretation by different observational systems, and its subsequent representation in radiative transfer calculations.

  3. An Examination of the Nature of Global MODIS Cloud Regimes

    Science.gov (United States)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.

    2014-01-01

    We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

  4. Global cloud database from VIRS and MODIS for CERES

    Science.gov (United States)

    Minnis, Patrick; Young, David F.; Wielicki, Bruce A.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Heck, Patrick W.; Dong, Xiquan

    2003-04-01

    The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

  5. Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

    Science.gov (United States)

    Platnick, Steven E.

    2011-01-01

    The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

  6. Global analysis of cloud field coverage and radiative properties, using morphological methods and MODIS observations

    Directory of Open Access Journals (Sweden)

    R. Z. Bar-Or

    2011-01-01

    Full Text Available The recently recognized continuous transition zone between detectable clouds and cloud-free atmosphere ("the twilight zone" is affected by undetectable clouds and humidified aerosol. In this study, we suggest to distinguish cloud fields (including the detectable clouds and the surrounding twilight zone from cloud-free areas, which are not affected by clouds. For this classification, a robust and simple-to-implement cloud field masking algorithm which uses only the spatial distribution of clouds, is presented in detail. A global analysis, estimating Earth's cloud field coverage (50° S–50° N for 28 July 2008, using the Moderate Resolution Imaging Spectroradiometer (MODIS data, finds that while the declared cloud fraction is 51%, the global cloud field coverage reaches 88%. The results reveal the low likelihood for finding a cloud-free pixel and suggest that this likelihood may decrease as the pixel size becomes larger. A global latitudinal analysis of cloud fields finds that unlike oceans, which are more uniformly covered by cloud fields, land areas located under the subsidence zones of the Hadley cell (the desert belts, contain proper areas for investigating cloud-free atmosphere as there is 40–80% probability to detect clear sky over them. Usually these golden-pixels, with higher likelihood to be free of clouds, are over deserts. Independent global statistical analysis, using MODIS aerosol and cloud products, reveals a sharp exponential decay of the global mean aerosol optical depth (AOD as a function of the distance from the nearest detectable cloud, both above ocean and land. Similar statistical analysis finds an exponential growth of mean aerosol fine-mode fraction (FMF over oceans when the distance from the nearest cloud increases. A 30 km scale break clearly appears in several analyses here, suggesting this is a typical natural scale of cloud fields. This work shows different microphysical and optical properties of cloud fields

  7. MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG (MOD08_M3). MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am...

  8. MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG (MYD08_E3). MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator...

  9. MODIS/Terra Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG (MOD08_D3). MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator...

  10. MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG (MYD08_D3). MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator...

  11. Comparison of global cloud liquid water path derived from microwave measurements with CERES-MODIS

    Science.gov (United States)

    Yi, Y.; Minnis, P.; Huang, J.; Lin, B.; Ayers, K.; Sun-Mack, S.; Fan, A.

    Cloud liquid water path LWP is a crucial parameter for climate studies due to the link that it provides between the atmospheric hydrological and radiative budgets Satellite-based visible infrared techniques such as the Visible Infrared Solar Split-Window Technique VISST can retrieve LWP for water clouds assumes single-layer over a variety of surfaces If the water clouds are overlapped by ice clouds the LWP of the underlying clouds can not be retrieved by such techniques However microwave techniques may be used to retrieve the LWP underneath ice clouds due to the microwave s insensitivity to cloud ice particles LWP is typically retrieved from satellite-observed microwave radiances only over ocean due to variations of land surface temperature and emissivity Recently Deeter and Vivekanandan 2006 developed a new technique for retrieving LWP over land In order to overcome the sensitivity to land surface temperature and emissivity their technique is based on a parameterization of microwave polarization-difference signals In this study a similar regression-based technique for retrieving LWP over land and ocean using Advanced Microwave Scanning Radiometer - EOS AMSR-E measurements is developed Furthermore the microwave surface emissivities are also derived using clear-sky fields of view based on the Clouds and Earth s Radiant Energy System Moderate-resolution Imaging Spectroradiometer CERES-MODIS cloud mask These emissivities are used in an alternate form of the technique The results are evaluated using independent measurements such

  12. Global statistics of liquid water content and effective number density of water clouds over ocean derived from combined CALIPSO and MODIS measurements

    OpenAIRE

    Y. Hu; M. Vaughan; C. McClain; M. Behrenfeld; H. Maring; D. Anderson; S. Sun-Mack; D. Flittner; J. Huang; B. Wielicki; P. Minnis; C. Weimer; C. Trepte; R. Kuehn

    2007-01-01

    International audience; This study presents an empirical relation that links layer integrated depolarization ratios, the extinction coefficients, and effective radii of water clouds, based on Monte Carlo simulations of CALIPSO lidar observations. Combined with cloud effective radius retrieved from MODIS, cloud liquid water content and effective number density of water clouds are estimated from CALIPSO lidar depolarization measurements in this study. Global statistics of the cloud liquid water...

  13. Global statistics of liquid water content and effective number density of water clouds over ocean derived from combined CALIPSO and MODIS measurements

    Science.gov (United States)

    Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

    2007-03-01

    This study presents an empirical relation that links layer integrated depolarization ratios, the extinction coefficients, and effective radii of water clouds, based on Monte Carlo simulations of CALIPSO lidar observations. Combined with cloud effective radius retrieved from MODIS, cloud liquid water content and effective number density of water clouds are estimated from CALIPSO lidar depolarization measurements in this study. Global statistics of the cloud liquid water content and effective number density are presented.

  14. Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

    Science.gov (United States)

    Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

    2007-06-01

    This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

  15. Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

    Directory of Open Access Journals (Sweden)

    Y. Hu

    2007-06-01

    Full Text Available This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

  16. Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS collections 5.1 and 6 over global oceans

    Directory of Open Access Journals (Sweden)

    J. Rausch

    2017-06-01

    Full Text Available Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC estimates inferred from the Aqua–MODIS (Moderate Resolution Imaging Spectroradiometer collections 5.1 (C5.1 and 6 (C6 cloud products (MYD06 are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1°  ×  1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS cloud product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above-cloud emission, cloud-top pressure (CTP, and pixel registration. Global results show a neutral to positive (> 50 cm−3 change for C6-derived CDNC relative to C5.1 for the 1.6 and 2.1 µm channel retrievals, corresponding to a neutral to −2 µm difference in droplet effective radius (re. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning −25 to +50 cm−3 related to a +2.5 to −1 µm transition in effective radius. Cloud optical thickness (τ differences were small relative to effective radius and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant inter-collection differences in aggregated values of effective radius due to changes to the precomputed retrieval lookup tables (LUTs for ocean scenes, changes to retrieved cloud-top pressure, solar irradiance, or above-cloud thermal emission

  17. An Integrated Cloud-Aerosol-Radiation Product Using CERES, MODIS, CALIPSO and CloudSat Data

    Science.gov (United States)

    Sun-Mack, S.; Gibson, S.; Chen, Y.; Wielicki, B.; Minnis, P.

    2006-12-01

    The goal of this paper is to provide the first integrated data set of global vertical profiles of aerosols, clouds, and radiation using the combined NASA A-Train data from Aqua CERES and MODIS, CALIPSO, and CloudSat. All of these instruments are flying in formation as part of the Aqua Train, or A-Train. This paper will present the preliminary results of merging aerosol and cloud data from the CALIPSO active lidar, cloud data from CloudSat, integrated column aerosol and cloud data from the MODIS CERES analyses, and surface and top-of-atmosphere broadband radiation fluxes from CERES. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

  18. Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

    2007-10-01

    This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

  19. Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Platnick, Steven

    2004-01-01

    MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

  20. Comparasion of Cloud Cover restituted by POLDER and MODIS

    Science.gov (United States)

    Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

    2009-04-01

    PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part

  1. Evaluating the impact of above-cloud aerosols on cloud optical depth retrievals from MODIS

    Science.gov (United States)

    Alfaro, Ricardo

    Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-cloud absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-cloud particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain cloud phase and provide contextual above-cloud AOD values. The frequency of occurrence of above-cloud aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20--50% in boreal summer. We find a corresponding low COD bias of 10--20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of

  2. MODIS/Terra Aerosol Cloud Water Vapor Ozone 8-Day L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  3. MODIS/Aqua Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  4. MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  5. MODIS/Terra Aerosol Cloud Water Vapor Ozone Daily L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS...

  6. MODIS/Aqua Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  7. Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

    Science.gov (United States)

    Alfaro-Contreras, Ricardo; Zhang, Jianglong; Campbell, James R.; Holz, Robert E.; Reid, Jeffrey S.

    2014-05-01

    Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.

  8. Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

    OpenAIRE

    Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

    2007-01-01

    International audience; This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liqui...

  9. Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

    Science.gov (United States)

    Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

    2009-01-01

    Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

  10. Shortwave Direct Radiative Effects of Above-Cloud Aerosols Over Global Oceans Derived From 8 Years of CALIOP and MODIS Observations

    Science.gov (United States)

    Zhang, Zhibo; Meyer, Kerry; Yu, Hongbin; Platnick, Steven; Colarco, Peter; Liu, Zhaoyan; Oraiopoulos, Lazaros

    2016-01-01

    In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007-2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asia. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m(exp. -2) [range of -0.03 to 0.06 W m (exp. -2)] at TOA. The DREs at surface and within the atmosphere are -0.015 W m(exp. -2) [range of -0.09 to -0.21 W m(exp. -2)], and 0.17 W m(exp. -2) [range of 0.11 to 0.24 W m(exp. -2)], respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July-August) seasonal mean cloudy-sky DRE is about 0.7 W m(exp. -2) [range of 0.2 to 1.2 W m(exp. -2)] at TOA. All our DRE computations are publicly available. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and

  11. Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

    Science.gov (United States)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

    2017-05-27

    Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

  12. Analysis of co-located MODIS and CALIPSO observations near clouds

    Directory of Open Access Journals (Sweden)

    T. Várnai

    2012-02-01

    Full Text Available This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the MODIS (MODerate resolution Imaging Spectroradiometer imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization lidar measurements about the systematic aerosol changes that occur near clouds.

    The statistical analysis of a yearlong dataset of co-located global maritime observations from the Aqua and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellites reveals that MODIS's multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on Aqua and CALIPSO yield very similar pictures, and that the discrepancies – due mainly to wind drift and differences in view angle – do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, MODIS reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in MODIS and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when MODIS cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4–5 km range.

  13. ASTER cloud coverage reassessment using MODIS cloud mask products

    Science.gov (United States)

    Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

    2010-10-01

    In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

  14. Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

    Science.gov (United States)

    Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

    2008-05-01

    CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

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

    Science.gov (United States)

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

    Science.gov (United States)

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

    2012-01-01

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

  17. Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

    Science.gov (United States)

    Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

    2017-08-01

    Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

  18. Exploring the differences in cloud properties observed by the Terra and Aqua MODIS Sensors

    Directory of Open Access Journals (Sweden)

    N. Meskhidze

    2009-05-01

    Full Text Available The aerosol-cloud interaction in different parts of the globe is examined here using multi-year statistics of remotely sensed data from two MODIS sensors aboard NASA's Terra (morning and Aqua (afternoon satellites. Simultaneous retrievals of aerosol loadings and cloud properties by the MODIS sensor allowed us to explore morning-to-afternoon variation of liquid cloud fraction (CF and optical thickness (COT for clean, moderately polluted and heavily polluted clouds in different seasons. Data analysis for seven-years of MODIS retrievals revealed strong temporal and spatial patterns in morning-to-afternoon variation of cloud fraction and optical thickness over different parts of the global oceans and the land. For the vast areas of stratocumulus cloud regions, the data shows that the days with elevated aerosol abundance were also associated with enhanced afternoon reduction of CF and COT pointing to the possible reduction of the indirect climate forcing. A positive correlation between aerosol optical depth and morning-to-afternoon variation of trade wind cumulus cloud cover was also found over the northern Indian Ocean, though no clear relationship between the concentration of Indo-Asian haze and morning-to-afternoon variation of COT was established. Over the Amazon region during wet conditions, aerosols are associated with an enhanced convective process in which morning shallow warm clouds are organized into afternoon deep convection with greater ice cloud coverage. Analysis presented here demonstrates that the new technique for exploring morning-to-afternoon variability in cloud properties by using the differences in data products from the two daily MODIS overpasses is capable of capturing some of the major features of diurnal variations in cloud properties and can be used for better understanding of aerosol radiative effects.

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

    Science.gov (United States)

    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).

  20. Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

    Science.gov (United States)

    Varnai, Tamas; Marshak, Alexander

    2011-01-01

    The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is

  1. Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

    Science.gov (United States)

    Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

    2011-12-01

    Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

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

    Science.gov (United States)

    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; hide

    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.

  3. Investigation of Cloud Properties and Atmospheric Profiles with MODIS

    Science.gov (United States)

    Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; LaPorte, Dan; Wolf, Walter

    1997-01-01

    The WINter Cloud Experiment (WINCE) was directed and supported by personnel from the University of Wisconsin in January and February. Data sets of good quality were collected by the MODIS Airborne Simulator (MAS) and other instruments on the NASA ER2; they will be used to develop and validate cloud detection and cloud property retrievals over winter scenes (especially over snow). Software development focused on utilities needed for all of the UW product executables; preparations for Version 2 software deliveries were almost completed. A significant effort was made, in cooperation with SBRS and MCST, in characterizing and understanding MODIS PFM thermal infrared performance; crosstalk in the longwave infrared channels continues to get considerable attention.

  4. Investigation of Cloud Properties and Atmospheric Profiles with Modis

    Science.gov (United States)

    Menzel, Paul; Ackerman, Steve; Moeller, Chris; Gumley, Liam; Strabala, Kathy; Frey, Richard; Prins, Elaine; Laporte, Dan; Wolf, Walter

    1997-01-01

    A major milestone was accomplished with the delivery of all five University of Wisconsin MODIS Level 2 science production software packages to the Science Data Support Team (SDST) for integration. These deliveries were the culmination of months of design and testing, with most of the work focused on tasks peripheral to the actual science contained in the code. LTW hosted a MODIS infrared calibration workshop in September. Considerable progress has been made by MCST, with help from LTW, in refining the calibration algorithm, and in identifying and characterization outstanding problems. Work continues on characterizing the effects of non-blackbody earth surfaces on atmospheric profile retrievals and modeling radiative transfer through cirrus clouds.

  5. Mapping the Distribution of Cloud Forests Using MODIS Imagery

    Science.gov (United States)

    Douglas, M. W.; Mejia, J.; Murillo, J.; Orozco, R.

    2007-05-01

    Tropical cloud forests - those forests that are frequently immersed in clouds or otherwise very humid, are extremely difficult to map from the ground, and are not easily distinguished in satellite imagery from other forest types, but they have a very different flora and fauna than lowland rainforest. Cloud forests, although found in many parts of the tropics, have a very restricted vertical extent and thus are also restricted horizontally. As a result, they are subject to both human disturbance (coffee growing for example) and the effects of possible climate change. Motivated by a desire to seek meteorological explanations for the distribution of cloud forests, we have begun to map cloudiness using MODIS Terra and Aqua visible imagery. This imagery, at ~1030 LT and 1330 LT, is an approximation for mid-day cloudiness. In tropical regions the amount of mid-day cloudiness strongly controls the shortwave radiation and thus the potential for evaporation (and aridity). We have mapped cloudiness using a simple algorithm that distinguishes between the cloud-free background brightness and the generally more reflective clouds to separate clouds from the underlying background. A major advantage of MODIS imagery over many other sources of satellite imagery is its high spatial resolution (~250m). This, coupled with precisely navigated images, means that detailed maps of cloudiness can be produced. The cloudiness maps can then be related to the underlying topography to further refine the location of the cloud forests. An advantage of this technique is that we are mapping the potential cloud forest, based on cloudiness, rather than the actual cloud forest, which are commonly based on forest estimates from satellite and digital elevation data. We do not derive precipitation, only estimates of daytime cloudiness. Although only a few years of MODIS imagery has been used in our studies, we will show that this is sufficient to describe the climatology of cloudiness with acceptable

  6. Neural network cloud top pressure and height for MODIS

    Science.gov (United States)

    Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

    2018-06-01

    Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found

  7. Multilayered Clouds Identification and Retrieval for CERES Using MODIS

    Science.gov (United States)

    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.

  8. Global distributions of cloud properties for CERES

    Science.gov (United States)

    Sun-Mack, S.; Minnis, P.; Heck, P.; Young, D.

    2003-04-01

    The microphysical and macrophysical properties of clouds play a crucial role in the earth's radiation budget. Simultaneous measurement of the radiation and cloud fields on a global basis has long been recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. With the implementation of the NASA Clouds and Earth's Radiant Energy System (CERES) in 1998, this need is being met. Broadband shortwave and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth from the TRMM Visible Infrared Scanner and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The combined cloud-radiation product has already been used for developing new, highly accurate anisotropic directional models for converting broadband radiances to flux. They also provide a consistent measure of cloud properties at different times of day over the globe since January 1998. These data will be valuable for determining the indirect effects of aerosols and for linking cloud water to cloud radiation. This paper provides an overview of the CERES cloud products from the three satellites including the retrieval methodology, validation, and global distributions. Availability and access to the datasets will also be discussed.

  9. Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

    Science.gov (United States)

    Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

    2017-12-01

    The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for

  10. Developing MODIS-based cloud climatologies to aid species distribution modeling and conservation activities

    Directory of Open Access Journals (Sweden)

    Michael William Douglas

    2016-10-01

    Full Text Available WorldClim (Hijmans et al. 2005 has been the de-facto source of basic climatological analyses for most species distribution modeling research and conservation science applications because of its global coverage and fine (<1 km spatial resolution.  However, it has been recognized since its development that there are limitations in data-poor regions, especially with regard to the precipitation analyses.  Here we describe procedures to develop a satellite-based daytime cloudiness climatology that better reflects the variations in vegetation cover in many regions of the globe than do the WorldClim precipitation products.  Moderate Resolution Imaging Spectroradiometer (MODIS imagery from the National Aeronautics and Space Administration (NASA Terra and Aqua sun-synchronous satellites have recently been used to develop multi-year climatologies of cloudiness.  Several procedures exist for developing such climatologies.  We first discuss a simple procedure that uses brightness thresholds to identify clouds.  We compare these results with those from a more complex procedure: the MODIS Cloud Mask product, recently averaged into climatological products by Wilson and Jetz (2016.  We discuss advantages and limitations of both approaches.  We also speculate on further work that will be needed to improve the usefulness of these MODIS-based climatologies of cloudiness. Despite limitations of current MODIS-based climatology products, they have the potential to greatly improve our understanding of the distribution of biota across the globe.  We show examples from oceanic islands and arid coastlines in the subtropics and tropics where the MODIS products should be of special value in predicting the observed vegetation cover.  Some important applications of reliable climatologies based on MODIS imagery products will include 1 helping to restore long-degraded cloud-impacted environments; 2 improving estimations of the spatial distribution of cloud

  11. MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km V006

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km (MYD06_L2) product consists of cloud optical and physical parameters. These parameters are derived using remotely...

  12. Overview of CERES Cloud Properties Derived From VIRS AND MODIS DATA

    Science.gov (United States)

    Minis, Patrick; Geier, Erika; Wielicki, Bruce A.; Sun-Mack, Sunny; Chen, Yan; Trepte, Qing Z.; Dong, Xiquan; Doelling, David R.; Ayers, J. Kirk; Khaiyer, Mandana M.

    2006-01-01

    Simultaneous measurement of radiation and cloud fields on a global basis is recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project (Wielicki et al., 1998) began addressing this issue in 1998 with its first broadband shortwave and longwave scanner on the Tropical Rainfall Measuring Mission (TRMM). This was followed by the launch of two CERES scanners each on Terra and Aqua during late 1999 and early 2002, respectively. When combined, these satellites should provide the most comprehensive global characterization of clouds and radiation to date. Unfortunately, the TRMM scanner failed during late 1998. The Terra and Aqua scanners continue to operate, however, providing measurements at a minimum of 4 local times each day. CERES was designed to scan in tandem with high resolution imagers so that the cloud conditions could be evaluated for every CERES measurement. The cloud properties are essential for converting CERES radiances shortwave albedo and longwave fluxes needed to define the radiation budget (ERB). They are also needed to unravel the impact of clouds on the ERB. The 5-channel, 2-km Visible Infrared Scanner (VIRS) on the TRMM and the 36-channel 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua are analyzed to define the cloud properties for each CERES footprint. To minimize inter-satellite differences and aid the development of useful climate-scale measurements, it was necessary to ensure that each satellite imager is calibrated in a fashion consistent with its counterpart on the other CERES satellites (Minnis et al., 2006) and that the algorithms are as similar as possible for all of the imagers. Thus, a set of cloud detection and retrieval algorithms were developed that could be applied to all three imagers utilizing as few channels as possible

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

    Science.gov (United States)

    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.

  14. Assessment of MODIS RSB Detector Uniformity Using Deep Convective Clouds

    Science.gov (United States)

    Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Mu, Qiaozhen

    2016-01-01

    For satellite sensor, the striping observed in images is typically associated with the relative multiple detector gain difference derived from the calibration. A method using deep convective cloud (DCC) measurements to assess the difference among detectors after calibration is proposed and demonstrated for select reflective solar bands (RSBs) of the Moderate Resolution Imaging Spectroradiometer (MODIS). Each detector of MODIS RSB is calibrated independently using a solar diffuser (SD). Although the SD is expected to accurately characterize detector response, the uncertainties associated with the SD degradation and characterization result in inadequacies in the estimation of each detector's gain. This work takes advantage of the DCC technique to assess detector uniformity and scan mirror side difference for RSB. The detector differences for Terra MODIS Collection 6 are less than 1% for bands 1, 3-5, and 18 and up to 2% for bands 6, 19, and 26. The largest difference is up to 4% for band 7. Most Aqua bands have detector differences less than 0.5% except bands 19 and 26 with up to 1.5%. Normally, large differences occur for edge detectors. The long-term trending shows seasonal oscillations in detector differences for some bands, which are correlated with the instrument temperature. The detector uniformities were evaluated for both unaggregated and aggregated detectors for MODIS band 1 and bands 3-7, and their consistencies are verified. The assessment results were validated by applying a direct correction to reflectance images. These assessments can lead to improvements to the calibration algorithm and therefore a reduction in striping observed in the calibrated imagery.

  15. Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

    Science.gov (United States)

    Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan; Rutan, David A.; Stephens, Graeme L.; Loeb, Norman G.; Minnis, Patrick; Wielicki, Bruce A.; Winker, David M.; Charlock, Thomas P.; Stackhouse, Paul W., Jr.; Xu, Kuan-Man; Collins, William D.

    2011-10-01

    One year of instantaneous top-of-atmosphere (TOA) and surface shortwave and longwave irradiances are computed using cloud and aerosol properties derived from instruments on the A-Train Constellation: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the CloudSat Cloud Profiling Radar (CPR), and the Aqua Moderate Resolution Imaging Spectrometer (MODIS). When modeled irradiances are compared with those computed with cloud properties derived from MODIS radiances by a Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm, the global and annual mean of modeled instantaneous TOA irradiances decreases by 12.5 W m-2 (5.0%) for reflected shortwave and 2.5 W m-2 (1.1%) for longwave irradiances. As a result, the global annual mean of instantaneous TOA irradiances agrees better with CERES-derived irradiances to within 0.5W m-2 (out of 237.8 W m-2) for reflected shortwave and 2.6W m-2 (out of 240.1 W m-2) for longwave irradiances. In addition, the global annual mean of instantaneous surface downward longwave irradiances increases by 3.6 W m-2 (1.0%) when CALIOP- and CPR-derived cloud properties are used. The global annual mean of instantaneous surface downward shortwave irradiances also increases by 8.6 W m-2 (1.6%), indicating that the net surface irradiance increases when CALIOP- and CPR-derived cloud properties are used. Increasing the surface downward longwave irradiance is caused by larger cloud fractions (the global annual mean by 0.11, 0.04 excluding clouds with optical thickness less than 0.3) and lower cloud base heights (the global annual mean by 1.6 km). The increase of the surface downward longwave irradiance in the Arctic exceeds 10 W m-2 (˜4%) in winter because CALIOP and CPR detect more clouds in comparison with the cloud detection by the CERES cloud algorithm during polar night. The global annual mean surface downward longwave irradiance of

  16. Consistency of two global MODIS aerosol products over ocean on Terra and Aqua CERES SSF datasets

    Science.gov (United States)

    Ignatov, Alexander; Minnis, Patrick; Wielicki, Bruce; Loeb, Norman G.; Remer, Lorraine A.; Kaufman, Yoram J.; Miller, Walter F.; Sun-Mack, Sunny; Laszlo, Istvan; Geier, Erika B.

    2004-12-01

    MODIS aerosol retrievals over ocean from Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side by side. The primary M product is generated by subsetting and remapping the multi-spectral (0.44 - 2.1 μm) MOD04 aerosols onto CERES footprints. MOD04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary (AVHRR-like) A product is generated in only two MODIS bands: 1 and 6 on Terra, and ` and 7 on Aqua. The A processing uses NASA/LaRC cloud-screening and NOAA/NESDIS single channel aerosol algorthm. The M and A products have been documented elsewhere and preliminarily compared using two weeks of global Terra CERES SSF (Edition 1A) data in December 2000 and June 2001. In this study, the M and A aerosol optical depths (AOD) in MODIS band 1 and (0.64 μm), τ1M and τ1A, are further checked for cross-platform consistency using 9 days of global Terra CERES SSF (Edition 2A) and Aqua CERES SSF (Edition 1A) data from 13 - 21 October 2002.

  17. A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

    Science.gov (United States)

    Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

    2014-01-01

    This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

  18. Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky; hide

    2015-01-01

    The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

  19. Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

    Science.gov (United States)

    Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

    2017-12-01

    Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

  20. Cloud vector mapping using MODIS 09 Climate Modeling Grid (CMG) for the year 2010 and 2011

    International Nuclear Information System (INIS)

    Jah, Asjad Asif; Farrukh, Yousaf Bin; Ali, Rao Muhammad Saeed

    2013-01-01

    An alternate use for MODIS images was sought by mapping cloud movement directions and dissipation time during the 2010 and 2011 floods. MODIS Level-02 daily CMG (Climate Modelling Grid) land-cover images were downloaded and subsequently rectified and clipped to the study area. These images were then put together to observe the direction of cloud movement and vectorize the observed paths. Initial findings suggest that usually cloud does not have a prolonged coverage period over the northern humid region of the country and dissipates within less than 24-hours. Additionally, this led to the development of a robust methodology for cloud motion analysis using FOSS and market leading GIS utilities

  1. Estimating Global Cropland Extent with Multi-year MODIS Data

    Directory of Open Access Journals (Sweden)

    Christopher O. Justice

    2010-07-01

    Full Text Available This study examines the suitability of 250 m MODIS (MODerate Resolution Imaging Spectroradiometer data for mapping global cropland extent. A set of 39 multi-year MODIS metrics incorporating four MODIS land bands, NDVI (Normalized Difference Vegetation Index and thermal data was employed to depict cropland phenology over the study period. Sub-pixel training datasets were used to generate a set of global classification tree models using a bagging methodology, resulting in a global per-pixel cropland probability layer. This product was subsequently thresholded to create a discrete cropland/non-cropland indicator map using data from the USDA-FAS (Foreign Agricultural Service Production, Supply and Distribution (PSD database describing per-country acreage of production field crops. Five global land cover products, four of which attempted to map croplands in the context of multiclass land cover classifications, were subsequently used to perform regional evaluations of the global MODIS cropland extent map. The global probability layer was further examined with reference to four principle global food crops: corn, soybeans, wheat and rice. Overall results indicate that the MODIS layer best depicts regions of intensive broadleaf crop production (corn and soybean, both in correspondence with existing maps and in associated high probability matching thresholds. Probability thresholds for wheat-growing regions were lower, while areas of rice production had the lowest associated confidence. Regions absent of agricultural intensification, such as Africa, are poorly characterized regardless of crop type. The results reflect the value of MODIS as a generic global cropland indicator for intensive agriculture production regions, but with little sensitivity in areas of low agricultural intensification. Variability in mapping accuracies between areas dominated by different crop types also points to the desirability of a crop-specific approach rather than attempting

  2. Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

    Science.gov (United States)

    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.

  3. Global variability of cloud condensation nuclei concentrations

    Science.gov (United States)

    Makkonen, Risto; Krüger, Olaf

    2017-04-01

    Atmospheric aerosols can influence cloud optical and dynamical processes by acting as cloud condensation nuclei (CCN). Globally, these indirect aerosol effects are significant to the radiative budget as well as a source of high uncertainty in anthropogenic radiative forcing. While historically many global climate models have fixed CCN concentrations to a certain level, most state-of-the-art models calculate aerosol-cloud interactions with sophisticated methodologies based on interactively simulated aerosol size distributions. However, due to scarcity of atmospheric observations simulated global CCN concentrations remain poorly constrained. Here we assess global CCN variability with a climate model, and attribute potential trends during 2000-2010 to changes in emissions and meteorological fields. Here we have used ECHAM5.5-HAM2 with model M7 microphysical aerosol model. The model has been upgraded with a secondary organic aerosol (SOA) scheme including ELVOCs. Dust and sea salt emissions are calculated online, based on wind speed and hydrology. Each experiment is 11 years, analysed after a 6-month spin-up period. The MODIS CCN product (Terra platform) is used to evaluate model performance throughout 2000-2010. While optical remote observation of CCN column includes several deficiencies, the products serves as a proxy for changes during the simulation period. In our analysis we utilize the observed and simulated vertical column integrated CCN concentration, and limit our analysis only over marine regions. Simulated annual CCN column densities reach 2ṡ108 cm-2 near strong source regions in central Africa, Arabian Sea, Bay of Bengal and China sea. The spatial concentration gradient in CCN(0.2%) is steep, and column densities drop to coasts. While the spatial distribution of CCN at 0.2% supersaturation is closer to that of MODIS proxy, as opposed to 1.0% supersaturation, the overall column integrated CCN are too low. Still, we can compare the relative response of CCN

  4. Validation of quasi-invariant ice cloud radiative quantities with MODIS satellite-based cloud property retrievals

    International Nuclear Information System (INIS)

    Ding, Jiachen; Yang, Ping; Kattawar, George W.; King, Michael D.; Platnick, Steven; Meyer, Kerry G.

    2017-01-01

    Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If τ(1–ϖ) and τ(1–ϖg) are conserved where τ is optical thickness, ϖ the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection 5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1–ϖg) factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1–ϖ)/(1–ϖg)]"1"/"2, also tend to be similar. - Highlights: • Similarity relations are theoretically analyzed and validated. • Similarity relations are verified with the MODIS Level 2 Collection 5 and 6 ice cloud property products. • The product of ice cloud optical thickness and (1–ϖg) is approximately invariant. • The similarity parameter derived from the MODIS ice cloud effective radius retrieval tends to be invariant.

  5. A method for daily global solar radiation estimation from two instantaneous values using MODIS atmospheric products

    International Nuclear Information System (INIS)

    Xu, Xiaojun; Du, Huaqiang; Zhou, Guomo; Mao, Fangjie; Li, Pingheng; Fan, Weiliang; Zhu, Dien

    2016-01-01

    Accurate information on the temporal and spatial distributions of solar radiation is very important in many scientific fields. In this study, instantaneous solar irradiances on a horizontal surface at 10:30 and 13:30 local time (LT) were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric data products with relatively high spatial resolution using a solar radiation model. These solar irradiances were combined to derive half-hourly averages of solar irradiance (HASI) and daily global solar radiation (GSR) on a horizontal surface using linear interpolation, piecewise linear regression, and quadratic polynomial regression. Compared with field observations, the HASI were estimated accurately when the total cloud fraction (TCF) was 0.6. Overall, the daily GSR estimated in this study was better than that estimated by the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis of NASA. The daily GSR estimated in this study was underestimated, whereas it was overestimated by MERRA. The combination of the daily GSR estimates of this study and MERRA offers a simple and feasible technique for reducing uncertainty in daily GSR estimates. - Highlights: • Daily GSR is integrated from two observations from the MODIS products. • Daily GSR from the MODIS products is underestimated. • Biases were attributed primarily to variations in the total cloud percent. • Combining daily GSR estimates from the MODIS and the MERRA increases accuracy.

  6. Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements

    Science.gov (United States)

    Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

    2006-11-01

    To provide more accurate ice cloud microphysical properties, the multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems globally over oceans using combined instrument data from Aqua. The liquid water path (LWP) of lower-layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. The properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements by matching simulated radiances from a two-cloud-layer radiative transfer model. The results show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and IWP retrievals for ice-over-water cloud systems. The mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over oceans from Aqua are 7.6 and 146.4 gm-2, respectively, down from the initial single-layer retrievals of 17.3 and 322.3 gm-2. The mean IWP for actual single-layer clouds is 128.2 gm-2.

  7. Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

    Science.gov (United States)

    Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

    2016-05-01

    Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

  8. The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua

    Science.gov (United States)

    Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.; Yang, Ping; Ridgway, William L.; Riedi, Jérôme

    2018-01-01

    The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases–daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel’s retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant. PMID:29657349

  9. Detection of Daytime Arctic Clouds using MISR and MODIS Data

    National Research Council Canada - National Science Library

    Shi, Tao; Clothiaux, Eugene E; Yu, Bin; Braverman, Amy J; Groff, David N

    2006-01-01

    ...) 7 are used operationally for detection of clouds in daytime polar regions. While the information content of clouds inherent in spectral radiances is familiar, the information content of clouds contained in angular radiances (i.e...

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

    Science.gov (United States)

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

    2007-01-01

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

  11. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  12. Spatial Feature Reconstruction of Cloud-Covered Areas in Daily MODIS Composites

    Directory of Open Access Journals (Sweden)

    Stephan Paul

    2015-04-01

    Full Text Available The opacity of clouds is the main problem for optical and thermal space-borne sensors, like the Moderate-Resolution Imaging Spectroradiometer (MODIS. Especially during polar nighttime, the low thermal contrast between clouds and the underlying snow/ice results in deficiencies of the MODIS cloud mask and affected products. There are different approaches to retrieve information about frequently cloud-covered areas, which often operate with large amounts of days aggregated into single composites for a long period of time. These approaches are well suited for static-nature, slow changing surface features (e.g., fast-ice extent. However, this is not applicable to fast-changing features, like sea-ice polynyas. Therefore, we developed a spatial feature reconstruction to derive information for cloud-covered sea-ice areas based on the surrounding days weighted directly proportional with their temporal proximity to the initial day of interest. Its performance is tested based on manually-screened and artificially cloud-covered case studies of MODIS-derived polynya area data for the polynya in the Brunt Ice Shelf region of Antarctica. On average, we are able to completely restore the artificially cloud-covered test areas with a spatial correlation of 0.83 and a mean absolute spatial deviation of 21%.

  13. Considering polarization in MODIS-based cloud property retrievals by using a vector radiative transfer code

    International Nuclear Information System (INIS)

    Yi, Bingqi; Huang, Xin; Yang, Ping; Baum, Bryan A.; Kattawar, George W.

    2014-01-01

    In this study, a full-vector, adding–doubling radiative transfer model is used to investigate the influence of the polarization state on cloud property retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. Two sets of lookup tables (LUTs) are developed for the retrieval purposes, both of which provide water cloud and ice cloud reflectivity functions at two wavelengths in various sun-satellite viewing geometries. However, only one of the LUTs considers polarization. The MODIS reflectivity observations at 0.65 μm (band 1) and 2.13 μm (band 7) are used to infer the cloud optical thickness and particle effective diameter, respectively. Results indicate that the retrievals for both water cloud and ice cloud show considerable sensitivity to polarization. The retrieved water and ice cloud effective diameter and optical thickness differences can vary by as much as ±15% due to polarization state considerations. In particular, the polarization state has more influence on completely smooth ice particles than on severely roughened ice particles. - Highlights: • Impact of polarization on satellite-based retrieval of water/ice cloud properties is studied. • Inclusion of polarization can change water/ice optical thickness and effective diameter values by up to ±15%. • Influence of polarization on cloud property retrievals depends on sun-satellite viewing geometries

  14. Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

    Science.gov (United States)

    Wilson, Michael J.; Oreopoulos, Lazarous

    2011-01-01

    The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

  15. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  16. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  17. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  18. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2A)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  19. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  20. CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  1. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  2. Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

    2010-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

  3. MODIS/Terra Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  4. MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  5. MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  6. MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  7. MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  8. MODIS/Aqua Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  9. A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

    Science.gov (United States)

    Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

    2013-01-01

    This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

  10. Intercomparison between CMIP5 model and MODIS satellite-retrieved data of aerosol optical depth, cloud fraction, and cloud-aerosol interactions

    Science.gov (United States)

    Sockol, Alyssa; Small Griswold, Jennifer D.

    2017-08-01

    Aerosols are a critical component of the Earth's atmosphere and can affect the climate of the Earth through their interactions with solar radiation and clouds. Cloud fraction (CF) and aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used with analogous cloud and aerosol properties from Historical Phase 5 of the Coupled Model Intercomparison Project (CMIP5) model runs that explicitly include anthropogenic aerosols and parameterized cloud-aerosol interactions. The models underestimate AOD by approximately 15% and underestimate CF by approximately 10% overall on a global scale. A regional analysis is then used to evaluate model performance in two regions with known biomass burning activity and absorbing aerosol (South America (SAM) and South Africa (SAF)). In SAM, the models overestimate AOD by 4.8% and underestimate CF by 14%. In SAF, the models underestimate AOD by 35% and overestimate CF by 13.4%. Average annual cycles show that the monthly timing of AOD peaks closely match satellite data in both SAM and SAF for all except the Community Atmosphere Model 5 and Geophysical Fluid Dynamics Laboratory (GFDL) models. Monthly timing of CF peaks closely match for all models (except GFDL) for SAM and SAF. Sorting monthly averaged 2° × 2.5° model or MODIS CF as a function of AOD does not result in the previously observed "boomerang"-shaped CF versus AOD relationship characteristic of regions with absorbing aerosols from biomass burning. Cloud-aerosol interactions, as observed using daily (or higher) temporal resolution data, are not reproducible at the spatial or temporal resolution provided by the CMIP5 models.

  11. Smoke, Clouds and Radiation Brazil NASA ER-2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) Data

    Data.gov (United States)

    National Aeronautics and Space Administration — SCARB_ER2_MAS data are Smoke, Clouds and Radiation Brazil (SCARB) NASA ER2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS)...

  12. Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

    Science.gov (United States)

    Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

    2017-12-01

    The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

  13. Comparison of CERES Cloud Properties Derived from Aqua and Terra MODIS Data and TRMM VIRS Radiances

    Science.gov (United States)

    Minnis, P.; Young, D. F.; Sun-Mack, S.; Trepte, Q. Z.; Chen, Y.; Heck, P. W.; Wielicki, B. A.

    2003-12-01

    The Clouds and Earth's Radiant Energy System (CERES) Project is obtaining Earth radiation budget measurements of unprecedented accuracy as a result of improved instruments and an analysis system that combines simultaneous, high-resolution cloud property retrievals with the broadband radiance data. The cloud properties are derived from three different satellite imagers: the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) and the Moderate Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites. A single set of consistent algorithms using the 0.65, 1.6 or 2.1, 3.7, 10.8, and 12.0-æm channels are applied to all three imagers. The cloud properties include, cloud coverage, height, thickness, temperature, optical depth, phase, effective particle size, and liquid or ice water path. Because each satellite is in a different orbit, the results provide information on the diurnal cycle of cloud properties. Initial intercalibrations show excellent consistency between the three images except for some differences of ~ 1K between the 3.7-æm channel on Terra and those on VIRS and Aqua. The derived cloud properties are consistent with the known diurnal characteristics of clouds in different areas. These datasets should be valuable for exploring the role of clouds in the radiation budget and hydrological cycle.

  14. GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

    Directory of Open Access Journals (Sweden)

    K. Fukue

    2016-06-01

    Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

  15. Improvement in the cloud mask for Terra MODIS mitigated by electronic crosstalk correction in the 6.7 μm and 8.5 μm channels

    Science.gov (United States)

    Sun, Junqiang; Madhavan, S.; Wang, M.

    2016-09-01

    MODerate resolution Imaging Spectroradiometer (MODIS), a remarkable heritage sensor in the fleet of Earth Observing System for the National Aeronautics and Space Administration (NASA) is in space orbit on two spacecrafts. They are the Terra (T) and Aqua (A) platforms which tracks the Earth in the morning and afternoon orbits. T-MODIS has continued to operate over 15 years easily surpassing the 6 year design life time on orbit. Of the several science products derived from MODIS, one of the primary derivatives is the MODIS Cloud Mask (MOD035). The cloud mask algorithm incorporates several of the MODIS channels in both reflective and thermal infrared wavelengths to identify cloud pixels from clear sky. Two of the thermal infrared channels used in detecting clouds are the 6.7 μm and 8.5 μm. Based on a difference threshold with the 11 μm channel, the 6.7 μm channel helps in identifying thick high clouds while the 8.5 μm channel being useful for identifying thin clouds. Starting 2010, it had been observed in the cloud mask products that several pixels have been misclassified due to the change in the thermal band radiometry. The long-term radiometric changes in these thermal channels have been attributed to the electronic crosstalk contamination. In this paper, the improvement in cloud detection using the 6.7 μm and 8.5 μm channels are demonstrated using the electronic crosstalk correction. The electronic crosstalk phenomena analysis and characterization were developed using the regular moon observation of MODIS and reported in several works. The results presented in this paper should significantly help in improving the MOD035 product, maintaining the long term dataset from T-MODIS which is important for global change monitoring.

  16. Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

    Science.gov (United States)

    Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

    2005-01-01

    A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

  17. Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

    Science.gov (United States)

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

    2016-01-01

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

  18. The impact of horizontal heterogeneities, cloud fraction, and cloud dynamics on warm cloud effective radii and liquid water path from CERES-like Aqua MODIS retrievals

    OpenAIRE

    D. Painemal; P. Minnis; S. Sun-Mack

    2013-01-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES Edition 4 algorithms are averaged at the CERES footprint resolution (~ 20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean...

  19. 3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

    Science.gov (United States)

    Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

    2007-01-01

    3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

  20. Aerosol Indirect Effect on Warm Clouds over Eastern China Using Combined CALIOP and MODIS Observations

    Science.gov (United States)

    Guo, Jianping; Wang, Fu; Huang, Jingfeng; Li, Xiaowen

    2015-04-01

    Aerosol, one of key components of the climate system, is highly variable, both temporally and spatially. It often exerts great influences on the cloud-precipitation chain processes by serving as CCN/IN, altering cloud microphysics and its life cycle. Yet, the aerosol indirect effect on clouds remains largely unknown, because the initial changes in clouds due to aerosols may be enhanced or dampened by such feedback processes as modified cloud dynamics, or evaporation of the smaller droplets due to the competition for water vapor. In this study, we attempted to quantify the aerosol effects on warm cloud over eastern China, based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO and CPR/CLOUDSAT during the period 2006 to 2010. The seasonality of aerosol from ground-based PM10 is quite different from that estimated from MODIS AOD. This result is corroborated by lower level profile of aerosol occurrence frequency from CALIOP, indicating the significant role CALIOP could play in aerosol-cloud interaction. The combined use of CALIOP and CPR facilitate the process to exactly determine the (vertical) position of warm cloud relative to aerosol, out of six scenarios in terms of aerosol-cloud mixing status in terms of aerosol-cloud mixing status, which shows as follows: AO (Aerosol only), CO (Cloud only), SASC (Single aerosol-single cloud), SADC (single aerosol-double cloud), DASC (double aerosol-single cloud), and others. Results shows that about 54% of all the cases belong to mixed status, among all the collocated aerosol-cloud cases. Under mixed condition, a boomerang shape is observed, i.e., reduced cloud droplet radius (CDR) is associated with increasing aerosol at moderate aerosol pollution (AODcases. We categorize dataset into warm-season and cold-season subsets to figure out how the boomerang shape varies with season. For moderate aerosol loading (AODMixed" cases is greater during cold season (denoted by a large slope), as compared with that during warm

  1. The Effect of Asian Dust Aerosols on Cloud Properties and Radiative Forcing from MODIS and CERES

    Science.gov (United States)

    Huang, Jianping; Minnis, Patrick; Lin, Bing; Wang, Tianhe; Yi, Yuhong; Hu, Yongxiang; Sun-Mack, Sunny; Ayers, Kirk

    2005-01-01

    The effects of dust storms on cloud properties and radiative forcing are analyzed over northwestern China from April 2001 to June 2004 using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of the cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. The humidity differences are larger in the dusty region than in the dust-free region, and may be caused by removal of moisture by wet dust precipitation. Due to changes in cloud microphysics, the instantaneous net radiative forcing is reduced from -71.2 W/m2 for dust contaminated clouds to -182.7 W/m2 for dust-free clouds. The reduced cooling effects of dusts may lead to a net warming of 1 W/m2, which, if confirmed, would be the strongest aerosol forcing during later winter and early spring dust storm seasons over the studied region.

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

    Science.gov (United States)

    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%).

  3. MODIS-derived daily PAR simulation from cloud-free images and its validation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Liangfu; Gu, Xingfa; Tian, Guoliang [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); The Center for National Spaceborne Demonstration, Beijing 100101 (China); Gao, Yanhua [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China); Yang, Lei [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China); Jilin University, Changchun 130026 (China); Liu, Qinhuo [State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101 (China)

    2008-06-15

    In this paper, a MODIS-derived daily PAR (photosynthetically active radiation) simulation model from cloud-free image over land surface has been developed based on Bird and Riordan's model. In this model, the total downwelling spectral surface irradiance is divided into two parts: one is beam irradiance, and another is diffuse irradiance. The attenuation of solar beam irradiance comprises scattering by the gas mixture, absorption by ozone, the gas mixture and water vapor, and scattering and absorption by aerosols. The diffuse irradiance is scattered out of the direct beam and towards the surface. The multiple ground-air interactions have been taken into account in the diffuse irradiance model. The parameters needed in this model are atmospheric water vapor content, aerosol optical thickness and spectral albedo ranging from 400 nm to 700 nm. They are all retrieved from MODIS data. Then, the instantaneous photosynthetically available radiation (IPAR) is integrated by using a weighted sum at each of the visible MODIS wavebands. Finally, a daily PAR is derived by integration of IPAR. In order to validate the MODIS-derived PAR model, we compared the field PAR measurements in 2003 and 2004 against the simulated PAR. The measurements were made at the Qianyanzhou ecological experimental station, Chinese Ecosystem Research Network. A total of 54 days of cloud-free MODIS L1B level images were used for the PAR simulation. Our results show that the simulated PAR is consistent with field measurements, where the correlation coefficient of linear regression between calculated PAR and measured PAR is 0.93396. However, there were some uncertainties in the comparison of 1 km pixel PAR with the tower flux stand measurement. (author)

  4. Assessment of MODIS On-Orbit Calibration Using a Deep Convective Cloud Technique

    Science.gov (United States)

    Mu, Qiaozhen; Wu, Aisheng; Chang, Tiejun; Angal, Amit; Link, Daniel; Xiong, Xiaoxiong; Doelling, David R.; Bhatt, Rajendra

    2016-01-01

    The MODerate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Terra and Aqua satellites are calibrated on-orbit with a solar diffuser (SD) for the reflective solar bands (RSB). The MODIS sensors are operating beyond their designed lifetime and hence present a major challenge to maintain the calibration accuracy. The degradation of the onboard SD is tracked by a solar diffuser stability monitor (SDSM) over a wavelength range from 0.41 to 0.94 micrometers. Therefore, any degradation of the SD beyond 0.94 micrometers cannot be captured by the SDSM. The uncharacterized degradation at wavelengths beyond this limit could adversely affect the Level 1B (L1B) product. To reduce the calibration uncertainties caused by the SD degradation, invariant Earth-scene targets are used to monitor and calibrate the MODIS L1B product. The use of deep convective clouds (DCCs) is one such method and particularly significant for the short-wave infrared (SWIR) bands in assessing their long-term calibration stability. In this study, we use the DCC technique to assess the performance of the Terra and Aqua MODIS Collection-6 L1B for RSB 1 3- 7, and 26, with spectral coverage from 0.47 to 2.13 micrometers. Results show relatively stable trends in Terra and Aqua MODIS reflectance for most bands. Careful attention needs to be paid to Aqua band 1, Terra bands 3 and 26 as their trends are larger than 1% during the study time period. We check the feasibility of using the DCC technique to assess the stability in MODIS bands 17-19. The assessment test on response versus scan angle (RVS) calibration shows substantial trend difference for Aqua band 1between different angles of incidence (AOIs). The DCC technique can be used to improve the RVS calibration in the future.

  5. Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

    Science.gov (United States)

    Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

    2014-12-01

    Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

  6. Comparison of CERES-MODIS cloud microphysical properties with surface observations over Loess Plateau

    Science.gov (United States)

    Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.

    2015-03-01

    To enhance the utility of satellite-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and Aqua generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for Aqua are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of satellite retrievals are discussed through statistical analysis and case studies. Generally, the CERES-MODIS cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.

  7. MODIS Collection 6 Clear Sky Restoral (CSR): Filtering Cloud Mast 'Not Clear' Pixels

    Science.gov (United States)

    Meyer, Kerry G.; Platnick, Steven Edward; Wind, Galina; Riedi, Jerome

    2014-01-01

    Correctly identifying cloudy pixels appropriate for the MOD06 cloud optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km cloud mask tests (note there are also two 250m subpixel cloud mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it identifies "not clear" pixels), certain situations exist in which pixels identified by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of clouds or within broken cloud fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be identified by MOD35 as "cloudy" for reasons other than the presence of clouds, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as clouds. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to identify pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.

  8. The MODIS Cloud Optical and Microphysical Products: Collection 6 Up-dates and Examples From Terra and Aqua

    Science.gov (United States)

    Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin G.; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.; hide

    2016-01-01

    The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties(optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations.The C6 algorithm changes collectively can result in significant changes relative to C5,though the magnitude depends on the dataset and the pixels retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud opticalproperty datasets, other MODIS cloud datasets are discussed when relevant.

  9. The impact of horizontal heterogeneities, cloud fraction, and cloud dynamics on warm cloud effective radii and liquid water path from CERES-like Aqua MODIS retrievals

    Science.gov (United States)

    Painemal, D.; Minnis, P.; Sun-Mack, S.

    2013-05-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES Edition 4 algorithms are averaged at the CERES footprint resolution (~ 20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8 - re2.1 differences are positive ( 50 g m-2, and negative (up to -4 μm) for larger Hσ. Thus, re3.8 - re2.1 differences are more likely to reflect biases associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

  10. Global Surface Net-Radiation at 5 km from MODIS Terra

    Directory of Open Access Journals (Sweden)

    Manish Verma

    2016-09-01

    Full Text Available Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years from the FLUXNET and Surface Radiation budget network (SURFRAD showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott’s index ranged from 0.74 for boreal to 0.63 for Mediterranean sites. Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W∙m−2 in boreal to 72.0 ± 4.1 W∙m−2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° × 1° but high temporal resolution gridded net-radiation product from the Clouds and Earth’s Radiant Energy System (CERES. Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W·m−2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the

  11. OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km (OMMYDCLD) is a Level-2 orbital product that combines cloud parameters retrieved by the...

  12. OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km V003 (OMMYDCLD) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — The OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km (OMMYDCLD) is a Level-2 orbital product that combines cloud parameters retrieved by the...

  13. Global simulations of aerosol processing in clouds

    Directory of Open Access Journals (Sweden)

    C. Hoose

    2008-12-01

    Full Text Available An explicit and detailed representation of in-droplet and in-crystal aerosol particles in stratiform clouds has been introduced in the global aerosol-climate model ECHAM5-HAM. The new scheme allows an evaluation of the cloud cycling of aerosols and an estimation of the relative contributions of nucleation and collision scavenging, as opposed to evaporation of hydrometeors in the global aerosol processing by clouds. On average an aerosol particle is cycled through stratiform clouds 0.5 times. The new scheme leads to important changes in the simulated fraction of aerosol scavenged in clouds, and consequently in the aerosol wet deposition. In general, less aerosol is scavenged into clouds with the new prognostic treatment than what is prescribed in standard ECHAM5-HAM. Aerosol concentrations, size distributions, scavenged fractions and cloud droplet concentrations are evaluated and compared to different observations. While the scavenged fraction and the aerosol number concentrations in the marine boundary layer are well represented in the new model, aerosol optical thickness, cloud droplet number concentrations in the marine boundary layer and the aerosol volume in the accumulation and coarse modes over the oceans are overestimated. Sensitivity studies suggest that a better representation of below-cloud scavenging, higher in-cloud collision coefficients, or a reduced water uptake by seasalt aerosols could reduce these biases.

  14. Global Software Development with Cloud Platforms

    Science.gov (United States)

    Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya

    Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. Clouds promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a cloud-based platform that addresses some of these core problems. We outline a generic cloud architecture, its design and our first implementation results for three cloud forms - a compute cloud, a storage cloud and a cloud-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful cloud service. We note some of the use cases for clouds in GSD, the lessons learned with our prototypes and identify challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these cloud computing platforms and see clouds as a means to supporting a ecosystem of clients, developers and other key stakeholders.

  15. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MYD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  16. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MOD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  17. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MYD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  18. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MOD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  1. Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD)

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Annual PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD) data set represents a series of annual average grids (2001-2010) of fine particulate matter...

  2. MODIS/Terra Vegetation Continuous Fields Yearly L3 Global 500m SIN Grid V051

    Data.gov (United States)

    National Aeronautics and Space Administration — The Terra MODIS Vegetation Continuous Fields (VCF) product is a sub-pixel-level representation of surface vegetation cover estimates globally. Designed to...

  3. Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD)

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Annual PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD) data sets represent a series of annual average grids (2001-2010) of fine particulate matter...

  4. Possible influences of Asian dust aerosols on cloud properties and radiative forcing observed from MODIS and CERES

    Science.gov (United States)

    Huang, Jianping; Minnis, Patrick; Lin, Bing; Wang, Tianhe; Yi, Yuhong; Hu, Yongxiang; Sun-Mack, Sunny; Ayers, Kirk

    2006-03-01

    The effects of dust storms on cloud properties and Radiative Forcing (RF) are analyzed over Northwestern China from April 2001 to June 2004 using data collected by the MODerate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. Due to changes in cloud microphysics, the instantaneous net RF is increased from -161.6 W/m2 for dust-free clouds to -118.6 W/m2 for dust-contaminated clouds.

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

    Science.gov (United States)

    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

  6. Retrieval of Cirrus Cloud Optical Depth under Day and Night Conditions from MODIS Collection 6 Cloud Property Data

    Directory of Open Access Journals (Sweden)

    Andrew K. Heidinger

    2015-06-01

    Full Text Available This paper presents a technique to generate cirrus optical depth and particle effective size estimates from the cloud emissivities at 8.5, 11 and 12 μm contained in the Collection-6 (C6 MYD06 cloud product. This technique employs the latest scattering models and scattering radiative transfer approximations to estimate cloud optical depth and particle effective size using efficient analytical formulae. Two scattering models are tested. The first is the same scattering model as that used in the C6 MYD06 solar reflectance products. The second model is an empirical model derived from radiometric consistency. Both models are shown to generate optical depths that compare well to those from constrained CALIPSO retrievals and MYD06. In terms of effective radius retrievals, the results from the radiometric empirical model agree more closely with MYD06 than those from the C6 model. This analysis is applied to AQUA/MODIS data collocated with CALIPSO/CALIOP during January 2010.

  7. MODIS 3km Aerosol Product: Algorithm and Global Perspective

    Science.gov (United States)

    Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.

    2013-01-01

    After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

  8. Formation of giant molecular clouds in global spiral structures: the role of orbital dynamics and cloud-cloud collisions

    International Nuclear Information System (INIS)

    Roberts, W.W. Jr.; Stewart, G.R.

    1987-01-01

    The different roles played by orbital dynamics and dissipative cloud-cloud collisions in the formation of giant molecular clouds (GMCs) in a global spiral structure are investigated. The interstellar medium (ISM) is simulated by a system of particles, representing clouds, which orbit in a spiral-perturbed, galactic gravitational field. The overall magnitude and width of the global cloud density distribution in spiral arms is very similar in the collisional and collisionless simulations. The results suggest that the assumed number density and size distribution of clouds and the details of individual cloud-cloud collisions have relatively little effect on these features. Dissipative cloud-cloud collisions play an important steadying role for the cloud system's global spiral structure. Dissipative cloud-cloud collisions also damp the relative velocity dispersion of clouds in massive associations and thereby aid in the effective assembling of GMC-like complexes

  9. The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

    Science.gov (United States)

    Oreopoulos, Lazaros

    2004-01-01

    The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

  10. Microphysical and radiative effects of aerosols on warm clouds during the Amazon biomass burning season as observed by MODIS: impacts of water vapor and land cover

    Directory of Open Access Journals (Sweden)

    J. E. Ten Hoeve

    2011-04-01

    Full Text Available Aerosol, cloud, water vapor, and temperature profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondônia, Brazil. It is found that increasing background column water vapor (CWV throughout this transition season between the Amazon dry and wet seasons likely exerts a strong effect on cloud properties. As a result, proper analysis of aerosol-cloud relationships requires that data be stratified by CWV to account better for the influence of background meteorological variation. Many previous studies of aerosol-cloud interactions over Amazonia have ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction (CF is shown to increase or remain constant with aerosol optical depth (AOD, depending on the value of CWV, whereas the relationship between cloud optical depth (COD and AOD is quite different. COD increases with AOD until AOD ~ 0.3, which is assumed to be due to the first indirect (microphysical effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1 the inhibition of cloud development by absorbing aerosols (radiative effect/semi-direct effect and/or (2 a possible retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols within or above clouds or subpixel dark surface contamination in the measured cloud reflectance. If (1 is a contributing mechanism, as we suspect, then an empirically-derived increasing function between cloud drop number and aerosol concentration, assumed in a majority of global climate models, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The relationship between

  11. The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

    OpenAIRE

    Painemal, D.; Minnis, P.; Sun-Mack, S.

    2013-01-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. ...

  12. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    Science.gov (United States)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

  13. Uncertainty Estimate of Surface Irradiances Computed with MODIS-, CALIPSO-, and CloudSat-Derived Cloud and Aerosol Properties

    Science.gov (United States)

    Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan

    2012-07-01

    Differences of modeled surface upward and downward longwave and shortwave irradiances are calculated using modeled irradiance computed with active sensor-derived and passive sensor-derived cloud and aerosol properties. The irradiance differences are calculated for various temporal and spatial scales, monthly gridded, monthly zonal, monthly global, and annual global. Using the irradiance differences, the uncertainty of surface irradiances is estimated. The uncertainty (1σ) of the annual global surface downward longwave and shortwave is, respectively, 7 W m-2 (out of 345 W m-2) and 4 W m-2 (out of 192 W m-2), after known bias errors are removed. Similarly, the uncertainty of the annual global surface upward longwave and shortwave is, respectively, 3 W m-2 (out of 398 W m-2) and 3 W m-2 (out of 23 W m-2). The uncertainty is for modeled irradiances computed using cloud properties derived from imagers on a sun-synchronous orbit that covers the globe every day (e.g., moderate-resolution imaging spectrometer) or modeled irradiances computed for nadir view only active sensors on a sun-synchronous orbit such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation and CloudSat. If we assume that longwave and shortwave uncertainties are independent of each other, but up- and downward components are correlated with each other, the uncertainty in global annual mean net surface irradiance is 12 W m-2. One-sigma uncertainty bounds of the satellite-based net surface irradiance are 106 W m-2 and 130 W m-2.

  14. Diurnal spatial distributions of aerosol optical and cloud micro-macrophysics properties in Africa based on MODIS observations

    Science.gov (United States)

    Ntwali, Didier; Chen, Hongbin

    2018-06-01

    The diurnal spatial distribution of both natural and anthropogenic aerosols, as well as liquid and ice cloud micro-macrophysics have been evaluated over Africa using Terra and Aqua MODIS collection 6 products. The variability of aerosol optical depth (AOD), Ångström exponent (AE), liquid and ice cloud microphysics (Liquid cloud effective radius LCER, Ice cloud effective radius ICER) and cloud macrophysics (Liquid cloud optical thickness LCOT, Liquid cloud water path LCWP, Ice cloud optical thickness ICOT, Ice cloud water path ICWP) parameters were investigated from the morning to afternoon over Africa from 2010 to 2014. In both the morning (Terra) and afternoon (Aqua) heavy pollution (AOD ≥ 0.6) occurs in the coastal and central areas (between 120 N-170 N and 100 E-150 E) of West of Africa (WA), Central of Africa (CA) (0.50 S-70S and 100 E-250 E),. Moderate pollution (0.3 1.2) aerosols. The mixture of dust and biomass burning aerosols (0.7 improve aerosol and cloud remote sensing retrieval.

  15. MODIS/Terra Land Water Mask Derived from MODIS and SRTM L3 Global 250m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS 250 m land-water mask (Short Name: MOD44W) is an improvement over the existing MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted...

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

    Science.gov (United States)

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

    2018-01-01

    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 datasets (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. PMID:29707470

  17. Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

    Science.gov (United States)

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

    2016-01-01

    An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), 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.

  18. Cloud Compute for Global Climate Station Summaries

    Science.gov (United States)

    Baldwin, R.; May, B.; Cogbill, P.

    2017-12-01

    Global Climate Station Summaries are simple indicators of observational normals which include climatic data summarizations and frequency distributions. These typically are statistical analyses of station data over 5-, 10-, 20-, 30-year or longer time periods. The summaries are computed from the global surface hourly dataset. This dataset totaling over 500 gigabytes is comprised of 40 different types of weather observations with 20,000 stations worldwide. NCEI and the U.S. Navy developed these value added products in the form of hourly summaries from many of these observations. Enabling this compute functionality in the cloud is the focus of the project. An overview of approach and challenges associated with application transition to the cloud will be presented.

  19. Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

    Science.gov (United States)

    Yi, Y.; Minnis, P.; Winker, D.; Huang, J.; Sun-Mack, S.; Ayers, K.

    2007-12-01

    Understanding the effects of clouds on Earth's radiation balance, especially on longwave fluxes within the atmosphere, depends on having accurate knowledge of cloud vertical location within the atmosphere. The Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite mission provides the opportunity to measure the vertical distribution of clouds at a greater detail than ever before possible. The CALIPSO cloud layer products from June 2006 to June 2007 are analyzed to determine the occurrence frequency and thickness of clouds as functions of time, latitude, and altitude. In particular, the latitude-longitude and vertical distributions of single- and multi-layer clouds and the latitudinal movement of cloud cover with the changing seasons are examined. The seasonal variablities of cloud frequency and geometric thickness are also analyzed and compared with similar quantities derived from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) using the Clouds and the Earth's Radiant Energy System (CERES) cloud retrieval algorithms. The comparisons provide an estimate of the errors in cloud fraction, top height, and thickness incurred by passive algorithms.

  20. The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

    Science.gov (United States)

    Painemal, D.; Minnis, P.; Sun-Mack, S.

    2013-10-01

    The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8-re2.1 differences are positive ( 45 gm-2, and negative (up to -4 μm) for larger Hσ. While re3.8-re2.1 differences in homogeneous scenes are qualitatively consistent with in situ microphysical observations over the region of study, negative differences - particularly evinced in mean regional maps - are more likely to reflect the dominant bias associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

  1. Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

    Directory of Open Access Journals (Sweden)

    Adam M Wilson

    2016-03-01

    Full Text Available Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

  2. Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

    Directory of Open Access Journals (Sweden)

    Xiwei Fan

    2015-04-01

    Full Text Available Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST retrieval error of 11.0 K when using the generalized split-window (GSW algorithm with a cirrus optical depth (COD at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies.

  3. MODIS-based global terrestrial estimates of gross primary productivity and evapotranspiration

    Science.gov (United States)

    Ryu, Y.; Baldocchi, D. D.; Kobayashi, H.; Li, J.; van Ingen, C.; Agarwal, D.; Jackson, K.; Humphrey, M.

    2010-12-01

    We propose a novel approach to quantify gross primary productivity (GPP) and evapotranspiration (ET) at global scale (5 km resolution with 8-day interval). The MODIS-based, process-oriented approach couples photosynthesis, evaporation, two-leaf energy balance and nitrogen, which are different from the previous satellite-based approaches. We couple information from MODIS with flux towers to assess the drivers and parameters of GPP and ET. Incoming shortwave radiation components (direct and diffuse PAR, NIR) under all sky condition are modeled using a Monte-Carlo based atmospheric radiative transfer model. The MODIS Level 2 Atmospheric products are gridded and overlaid with MODIS Land products to produce spatially compatible forcing variables. GPP is modeled using a two-leaf model (sunlit and shaded leaf) and the maximum carboxylation rate is estimated using albedo-Nitrogen-leaf trait relations. The GPP is used to calculate canopy conductance via Ball-Berry model. Then, we apply Penman-Monteith equation to calculate evapotranspiration. The process-oriented approach allows us to investigate the main drivers of GPP and ET at global scale. Finally we explore the spatial and temporal variability of GPP and ET at global scale.

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

    Science.gov (United States)

    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.

  5. MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid (MYD21A2.006). A new suite of MODIS Land Surface Temperature (LST) and Emissivity...

  6. MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid (MOD21A2.006). A new suite of MODIS Land Surface Temperature (LST) and Emissivity...

  7. Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

    Science.gov (United States)

    Yuan, W.; Liu, S.; Yu, G.; Bonnefond, J.-M.; Chen, J.; Davis, K.; Desai, A.R.; Goldstein, Allen H.; Gianelle, D.; Rossi, F.; Suyker, A.E.; Verma, S.B.

    2010-01-01

    The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively.Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000–2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed

  8. Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3-D Radiative Effects, and Cloud Inhomogeneity

    Science.gov (United States)

    Zhou, Yongbo; Sun, Xuejin; Mielonen, Tero; Li, Haoran; Zhang, Riwei; Li, Yan; Zhang, Chuanliang

    2018-01-01

    For inhomogeneous cirrus clouds, cloud optical thickness (COT) and effective diameter (De) provided by the Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 cloud products are associated with errors due to the single habit assumption (SHA), independent pixel assumption (IPA), photon absorption effect (PAE), and plane-parallel assumption (PPA). SHA means that every cirrus cloud is assumed to have the same shape habit of ice crystals. IPA errors are caused by three-dimensional (3D) radiative effects. PPA and PAE errors are caused by cloud inhomogeneity. We proposed a method to single out these different errors. These errors were examined using the Spherical Harmonics Discrete Ordinate Method simulations done for the MODIS 0.86 μm and 2.13 μm bands. Four midlatitude and tropical cirrus cases were studied. For the COT retrieval, the impacts of SHA and IPA were especially large for optically thick cirrus cases. SHA errors in COT varied distinctly with scattering angles. For the De retrieval, SHA decreased De under most circumstances. PAE decreased De for optically thick cirrus cases. For the COT and De retrievals, the dominant error source was SHA for overhead sun whereas for oblique sun, it could be any of SHA, IPA, and PAE, varying with cirrus cases and sun-satellite viewing geometries. On the domain average, the SHA errors in COT (De) were within -16.1%-42.6% (-38.7%-2.0%), whereas the 3-D radiative effects- and cloud inhomogeneity-induced errors in COT (De) were within -5.6%-19.6% (-2.9%-8.0%) and -2.6%-0% (-3.7%-9.8%), respectively.

  9. A Comparison of MODIS/VIIRS Cloud Masks over Ice-Bearing River: On Achieving Consistent Cloud Masking and Improved River Ice Mapping

    Directory of Open Access Journals (Sweden)

    Simon Kraatz

    2017-03-01

    Full Text Available The capability of frequently and accurately monitoring ice on rivers is important, since it may be possible to timely identify ice accumulations corresponding to ice jams. Ice jams are dam-like structures formed from arrested ice floes, and may cause rapid flooding. To inform on this potential hazard, the CREST River Ice Observing System (CRIOS produces ice cover maps based on MODIS and VIIRS overpass data at several locations, including the Susquehanna River. CRIOS uses the respective platform’s automatically produced cloud masks to discriminate ice/snow covered grid cells from clouds. However, since cloud masks are produced using each instrument’s data, and owing to differences in detector performance, it is quite possible that identical algorithms applied to even nearly identical instruments may produce substantially different cloud masks. Besides detector performance, cloud identification can be biased due to local (e.g., land cover, viewing geometry, and transient conditions (snow and ice. Snow/cloud confusions and large view angles can result in substantial overestimates of clouds and ice. This impacts algorithms, such as CRIOS, since false cloud cover precludes the determination of whether an otherwise reasonably cloud free grid consists of water or ice. Especially for applications aiming to frequently classify or monitor a location it is important to evaluate cloud masking, including false cloud detections. We present an assessment of three cloud masks via the parameter of effective revisit time. A 100 km stretch of up to 1.6 km wide river was examined with daily data sampled at 500 m resolution, examined over 317 days during winter. Results show that there are substantial differences between each of the cloud mask products, especially while the river bears ice. A contrast-based cloud screening approach was found to provide improved and consistent cloud and ice identification within the reach (95%–99% correlations, and 3%–7% mean

  10. MODIS/Aqua Clear Radiance Statistics Indexed to Global Grid 5-Min L2 Swath 10km V006

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS/Aqua Clear Radiance Statistics Indexed to Global Grid 5-Min L2 Swath 10km (MYDCSR_G) provides a variety of statistical measures that characterize observed...

  11. Global dust sources detection using MODIS Deep Blue Collection 6 aerosol products

    Science.gov (United States)

    Pérez García-Pando, C.; Ginoux, P. A.

    2015-12-01

    Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Remote sensing sensors are the most useful tool to locate dust sources. These sensors include microwaves, visible channels, and lidar. On the global scale, major dust source regions have been identified using polar orbiting satellite instruments. The MODIS Deep Blue algorithm has been particularly useful to detect small-scale sources such as floodplains, alluvial fans, rivers, and wadis , as well as to identify anthropogenic sources from agriculture. The recent release of Collection 6 MODIS aerosol products allows to extend dust source detection to the entire land surfaces, which is quite useful to identify mid to high latitude dust sources and detect not only dust from agriculture but fugitive dust from transport and industrial activities. This presentation will overview the advantages and drawbacks of using MODIS Deep Blue for dust detection, compare to other instruments (polar orbiting and geostationary). The results of Collection 6 with a new dust screening will be compared against AERONET. Applications to long range transport of anthropogenic dust will be presented.

  12. The impact of horizontal heterogeneities, cloud fraction, and liquid water path on warm cloud effective radii from CERES-like Aqua MODIS retrievals

    Directory of Open Access Journals (Sweden)

    D. Painemal

    2013-10-01

    Full Text Available The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E, and cloud fraction (CF on MODIS cloud effective radius (re, retrieved from the 2.1 μm (re2.1 and 3.8 μm (re3.8 channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km, while heterogeneities (Hσ are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8–re2.1 differences are positive (Hσ 45 gm−2, and negative (up to −4 μm for larger Hσ. While re3.8–re2.1 differences in homogeneous scenes are qualitatively consistent with in situ microphysical observations over the region of study, negative differences – particularly evinced in mean regional maps – are more likely to reflect the dominant bias associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

  13. Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

    Science.gov (United States)

    Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

    2017-06-01

    Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

  14. Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

    Science.gov (United States)

    Gacal, G. F. B.; Lagrosas, N.

    2017-12-01

    Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds

  15. The Global Influence of Cloud Optical Thickness on Terrestrial Carbon Uptake

    Science.gov (United States)

    Zhu, P.; Cheng, S. J.; Keppel-Aleks, G.; Butterfield, Z.; Steiner, A. L.

    2016-12-01

    Clouds play a critical role in regulating Earth's climate. One important way is by changing the type and intensity of solar radiation reaching the Earth's surface, which impacts plant photosynthesis. Specifically, the presence of clouds modifies photosynthesis rates by influencing the amount of diffuse radiation as well as the spectral distribution of solar radiation. Satellite-derived cloud optical thickness (COT) may provide the observational constraint necessary to assess the role of clouds on ecosystems and terrestrial carbon uptake across the globe. Previous studies using ground-based observations at individual sites suggest that below a COT of 7, there is a greater increase in light use efficiency than at higher COT values, providing evidence for higher carbon uptake rates than expected given the reduction in radiation by clouds. However, the strength of the COT-terrestrial carbon uptake correlation across the globe remains unknown. In this study, we investigate the influence of COT on terrestrial carbon uptake on a global scale, which may provide insights into cloud conditions favorable for plant photosynthesis and improve our estimates of the land carbon sink. Global satellite-derived MODIS data show that tropical and subtropical regions tend to have COT values around or below the threshold during growing seasons. We find weak correlations between COT and GPP with Fluxnet MTE global GPP data, which may be due to the uncertainty of upscaling GPP from individual site measurements. Analysis with solar-induced fluorescence (SIF) as a proxy for GPP is also evaluated. Overall, this work constructs a global picture of the role of COT on terrestrial carbon uptake, including its temporal and spatial variations.

  16. Influences of cloud heterogeneity on cirrus optical properties retrieved from the visible and near-infrared channels of MODIS/SEVIRI for flat and optically thick cirrus clouds

    International Nuclear Information System (INIS)

    Zhou, Yongbo; Sun, Xuejin; Zhang, Riwei; Zhang, Chuanliang; Li, Haoran; Zhou, Junhao; Li, Shaohui

    2017-01-01

    The influences of three-dimensional radiative effects and horizontal heterogeneity effects on the retrieval of cloud optical thickness (COT) and effective diameter (De) for cirrus clouds are explored by the SHDOM radiative transfer model. The stochastic cirrus clouds are generated by the Cloudgen model based on the Atmospheric Radiation Measurement program data. Incorporating a new ice cloud spectral model, we evaluate the retrieval errors for two solar zenith angles (SZAs) (30° and 60°), four solar azimuth angles (0°, 45°, 90°, and 180°), and two sensor settings (Moderate Resolution Imaging Spectrometer (MODIS) onboard Aqua and Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard METEOSAT-8). The domain-averaged relative error of COT (μ) ranges from −24.1 % to -1.0 % (SZA = 30°) and from −11.6 % to 3.3 % (SZA = 60°), with the uncertainty within 7.5 % to –12.5 % (SZA = 30°) and 20.0 % - 27.5 % (SZA = 60°). For the SZA of 60° only, the relative error and uncertainty are parameterized by the retrieved COT by linear functions, providing bases to correct the retrieved COT and estimate their uncertainties. Besides, De is overestimated by 0.7–15.0 μm on the domain average, with the corresponding uncertainty within 6.7–26.5 μm. The retrieval errors show no discernible dependence on solar azimuth angle due to the flat tops and full coverage of the cirrus samples. The results are valid only for the two samples and for the specific spatial resolution of the radiative transfer simulations. - Highlights: • The retrieved cloud optical properties for 3-D cirrus clouds are evaluated. • The cloud optical thickness and uncertainty could be corrected and estimated. • On the domain average, the effective diameter of ice crystal is overestimated. • The optical properties show non-obvious dependence on the solar azimuth angle.

  17. Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

    Science.gov (United States)

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

    2016-01-01

    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 NASAs 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 match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with 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.

  18. Methanogenesis, Mesospheric Clouds, and Global Habitability

    Science.gov (United States)

    Pueschel, Rudolf F.; Condon, Estelle P. (Technical Monitor)

    2000-01-01

    Hyperthermophilic methanogens can exist in a deep hot biosphere up to 110 C, or 10 km deep. Methane (CH4) itself is thermodynamically stable to depths of 300 km. Geologic (microbial plus abiogenic thermal) methane is transported upward, attested to by its association with helium, to form petroleum pools. Near or at the surface, geologic CH4 mixes with other natural and with anthropogenic CH4 yielding annual emissions into the atmosphere of 500 Tg, of which 200 Tg are natural and 300 Tg are man-made. The atmospheric lifetime of CH4, a greenhouse gas 20 times more effective than CO2 in raising global temperatures, is approximately 10 years. It is removed from the atmosphere mainly by reactions with hydroxyl radical (OH) to form CO2, but also by dry soil and by conversion to H2O in the stratosphere and middle atmosphere. A sudden rise in atmospheric temperatures by 9-12 C some 55 million years ago has been explained by the release in a few thousand years of three trillion tons of CH4 out of 15 trillion tons that had formed beneath the sea floor. What prevented this CH4-induced greenhouse effect from running away? An analog to the CH4-burp of 55 million years ago is the CH4-doubling over the past century which resulted in a increase in upper level H2O from 4.3 ppmv to 6 ppmv. This 30% increase in H2O vapor yielded a tenfold increase in brightness of polar mesospheric clouds because of a strong dependence of the ice particle nucleation rate on the water saturation ratios. Models show that at a given temperature the optical depth of mesospheric clouds scales as [H2O]beta with beta varying between 4 and 8. Radiative transfer tools applied to mesospheric particles suggest that an optical depth of approximately one, or 1000 times the current mesospheric cloud optical depth, would result in tropospheric cooling of about 10 K. Assuming beta=6, a thousandfold increase in optical thickness would require a three-fold increase of H2O, or a 20-fold increase of CH4. At the current

  19. Global Performance of a Fast Parameterization Scheme for Estimating Surface Solar Radiation from MODIS data

    Science.gov (United States)

    Tang, W.; Yang, K.; Sun, Z.; Qin, J.; Niu, X.

    2016-12-01

    A fast parameterization scheme named SUNFLUX is used in this study to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the Surface Radiation Budget Network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the Baseline Surface Radiation Network (BSRN). The statistical results for evaluation against these three datasets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16% and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations and 90 China Meteorological Administration (CMA) radiation stations.

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

    Science.gov (United States)

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

    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.

  1. Developing a Random Forest Algorithm for MODIS Global Burned Area Classification

    Directory of Open Access Journals (Sweden)

    Rubén Ramo

    2017-11-01

    Full Text Available This paper aims to develop a global burned area (BA algorithm for MODIS BRDF-corrected images based on the Random Forest (RF classifier. Two RF models were generated, including: (1 all MODIS reflective bands; and (2 only the red (R and near infrared (NIR bands. Active fire information, vegetation indices and auxiliary variables were taken into account as well. Both RF models were trained using a statistically designed sample of 130 reference sites, which took into account the global diversity of fire conditions. For each site, fire perimeters were obtained from multitemporal pairs of Landsat TM/ETM+ images acquired in 2008. Those fire perimeters were used to extract burned and unburned areas to train the RF models. Using the standard MD43A4 resolution (500 × 500 m, the training dataset included 48,365 burned pixels and 6,293,205 unburned pixels. Different combinations of number of trees and number of parameters were tested. The final RF models included 600 trees and 5 attributes. The RF full model (considering all bands provided a balanced accuracy of 0.94, while the RF RNIR model had 0.93. As a first assessment of these RF models, they were used to classify daily MCD43A4 images in three test sites for three consecutive years (2006–2008. The selected sites included different ecosystems: Australia (Tropical, Boreal (Canada and Temperate (California, and extended coverage (totaling more than 2,500,000 km2. Results from both RF models for those sites were compared with national fire perimeters, as well as with two existing BA MODIS products; the MCD45 and MCD64. Considering all three years and three sites, commission error for the RF Full model was 0.16, with an omission error of 0.23. For the RF RNIR model, these errors were 0.19 and 0.21, respectively. The existing MODIS BA products had lower commission errors, but higher omission errors (0.09 and 0.33 for the MCD45 and 0.10 and 0.29 for the MCD64 than those obtained with the RF models, and

  2. Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI

    Directory of Open Access Journals (Sweden)

    R. Alfaro-Contreras

    2016-01-01

    Full Text Available Seven and a half years (June 2006 to November 2013 of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP aerosol and cloud layer products are compared with collocated Ozone Monitoring Instrument (OMI aerosol index (AI data and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS cloud products in order to investigate variability in estimates of biannual and monthly above-cloud aerosol (ACA events globally. The active- (CALIOP and passive-based (OMI-MODIS techniques have their advantages and caveats for ACA detection, and thus both are used to derive a thorough and robust comparison of daytime cloudy-sky ACA distribution and climatology. For the first time, baseline above-cloud aerosol optical depth (ACAOD and AI thresholds are derived and examined (AI  =  1.0, ACAOD  =  0.015 for each sensor. Both OMI-MODIS and CALIOP-based daytime spatial distributions of ACA events show similar patterns during both study periods (December–May and (June–November. Divergence exists in some regions, however, such as Southeast Asia during June through November, where daytime cloudy-sky ACA frequencies of up to 10 % are found from CALIOP yet are non-existent from the OMI-based method. Conversely, annual cloudy-sky ACA frequencies of 20–30 % are reported over northern Africa from the OMI-based method yet are largely undetected by the CALIOP-based method. Using a collocated OMI-MODIS-CALIOP data set, our study suggests that the cloudy-sky ACA frequency differences between the OMI-MODIS- and CALIOP-based methods are mostly due to differences in cloud detection capability between MODIS and CALIOP as well as QA flags used. An increasing interannual variability of  ∼  0.3–0.4 % per year (since 2009 in global monthly cloudy-sky ACA daytime frequency of occurrence is found using the OMI-MODIS-based method. Yet, CALIOP-based global daytime ACA frequencies exhibit a near-zero interannual variability. Further analysis suggests

  3. The Global and Local Characters of Mars Perihelion Cloud Trails

    Science.gov (United States)

    Clancy, R. T.; Wolff, M. J.; Smith, M. D.; Cantor, B. A.; Spiga, A.

    2014-12-01

    We present the seasonal and spatial distribution of Mars perihelion cloud trails as mapped from Mars Reconnaissance Orbiter (MRO) MARCI (Mars Color Imager) imaging observations in 2 ultraviolet and 3 visible filters. The extended 2007-2013 period of MARCI daily global image maps reveals the widespread distribution of these high altitude clouds, which are somewhat paradoxically associated with specific surface regions. They appear as longitudinally extended (300-700 km) cloud trails with distinct leading plumes of substantial ice cloud optical depths (0.02-0.2) for such high altitudes of occurrence (40-50 km, from cloud surface shadow measurements). These plumes generate small ice particles (Reff~1 to reflect locally elevated mesospheric water ice formation that may impact the global expression of mesospheric water ice aerosols.

  4. Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

    Science.gov (United States)

    Cescatti, Alessandro; Marcolla, Barbara; Vannan, Suresh K. Santhana; Pan, Jerry Yun; Roman, Miguel O.; Yang, Xiaoyuan; Ciais, Philippe; Cook, Robert B.; Law, Beverly E.; Matteucci, Girogio; hide

    2012-01-01

    Surface albedo is a key parameter in the Earth's energy balance since it affects the amount of solar radiation directly absorbed at the planet surface. Its variability in time and space can be globally retrieved through the use of remote sensing products. To evaluate and improve the quality of satellite retrievals, careful intercomparisons with in situ measurements of surface albedo are crucial. For this purpose we compared MODIS albedo retrievals with surface measurements taken at 53 FLUXNET sites that met strict conditions of land cover homogeneity. A good agreement between mean yearly values of satellite retrievals and in situ measurements was found (R(exp 2)= 0.82). The mismatch is correlated to the spatial heterogeneity of surface albedo, stressing the relevance of land cover homogeneity when comparing point to pixel data. When the seasonal patterns of MODIS albedo is considered for different plant functional types, the match with surface observation is extremely good at all forest sites. On the contrary, in non-forest sites satellite retrievals underestimate in situ measurements across the seasonal cycle. The mismatch observed at grasslands and croplands sites is likely due to the extreme fragmentation of these landscapes, as confirmed by geostatistical attributes derived from high resolution scenes.

  5. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products

    International Nuclear Information System (INIS)

    Qin, Jun; Chen, Zhuoqi; Yang, Kun; Liang, Shunlin; Tang, Wenjun

    2011-01-01

    Global solar radiation (GSR) is required in a large number of fields. Many parameterization schemes are developed to estimate it using routinely measured meteorological variables, since GSR is directly measured at a limited number of stations. Even so, meteorological stations are sparse, especially, in remote areas. Satellite signals (radiance at the top of atmosphere in most cases) can be used to estimate continuous GSR in space. However, many existing remote sensing products have a relatively coarse spatial resolution and these inversion algorithms are too complicated to be mastered by experts in other research fields. In this study, the artificial neural network (ANN) is utilized to build the mathematical relationship between measured monthly-mean daily GSR and several high-level remote sensing products available for the public, including Moderate Resolution Imaging Spectroradiometer (MODIS) monthly averaged land surface temperature (LST), the number of days in which the LST retrieval is performed in 1 month, MODIS enhanced vegetation index, Tropical Rainfall Measuring Mission satellite (TRMM) monthly precipitation. After training, GSR estimates from this ANN are verified against ground measurements at 12 radiation stations. Then, comparisons are performed among three GSR estimates, including the one presented in this study, a surface data-based estimate, and a remote sensing product by Japan Aerospace Exploration Agency (JAXA). Validation results indicate that the ANN-based method presented in this study can estimate monthly-mean daily GSR at a spatial resolution of about 5 km with high accuracy.

  6. Assessment of Global Carbon Dioxide Concentration Using MODIS and GOSAT Data

    Directory of Open Access Journals (Sweden)

    Hiroshi Tani

    2012-11-01

    Full Text Available Carbon dioxide (CO2 is the most important greenhouse gas (GHG in the atmosphere and is the greatest contributor to global warming. CO2 concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO2 concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR or Moderate Resolution Imaging Spectroradiometer (MODIS data can overcome these problems, particularly in areas with low densities of CO2 concentration watch stations. A model based on temperature (MOD11C3, vegetation cover (MOD13C2 and MOD15A2 and productivity (MOD17A2 of MODIS (which we have named the TVP model was developed in the current study to assess CO2 concentrations on a global scale. We assumed that CO2 concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO aboard the Greenhouse gases Observing SATellite (GOSAT are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson’s correlation coefficient (R2 was 0.75 in Eurasia (RMSE = 1.16 and South America (RMSE = 1.17; the lowest R2 was 0.57 in Australia (RMSE = 0.73. Compared with the TANSO-observed CO2 concentration (XCO2, we found that the accuracy throughout the World is between −2.56~3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified.

  7. Assessment of global carbon dioxide concentration using MODIS and GOSAT data.

    Science.gov (United States)

    Guo, Meng; Wang, Xiufeng; Li, Jing; Yi, Kunpeng; Zhong, Guosheng; Tani, Hiroshi

    2012-11-26

    Carbon dioxide (CO(2)) is the most important greenhouse gas (GHG) in the atmosphere and is the greatest contributor to global warming. CO(2) concentration data are usually obtained from ground observation stations or from a small number of satellites. Because of the limited number of observations and the short time series of satellite data, it is difficult to monitor CO(2) concentrations on regional or global scales for a long time. The use of the remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) or Moderate Resolution Imaging Spectroradiometer (MODIS) data can overcome these problems, particularly in areas with low densities of CO(2) concentration watch stations. A model based on temperature (MOD11C3), vegetation cover (MOD13C2 and MOD15A2) and productivity (MOD17A2) of MODIS (which we have named the TVP model) was developed in the current study to assess CO(2) concentrations on a global scale. We assumed that CO(2) concentration from the Thermal And Near infrared Sensor for carbon Observation (TANSO) aboard the Greenhouse gases Observing SATellite (GOSAT) are the true values and we used these values to check the TVP model accuracy. The results indicate that the accuracy of the TVP model is different in different continents: the greatest Pearson's correlation coefficient (R2) was 0.75 in Eurasia (RMSE = 1.16) and South America (RMSE = 1.17); the lowest R2 was 0.57 in Australia (RMSE = 0.73). Compared with the TANSO-observed CO(2) concentration (XCO(2)), we found that the accuracy throughout the World is between -2.56~3.14 ppm. Potential sources of TVP model uncertainties were also analyzed and identified.

  8. Role of orbital dynamics and cloud-cloud collisions in the formation of giant molecular clouds in global spiral structures

    International Nuclear Information System (INIS)

    Roberts, W.W. Jr.; Stewart, G.R.

    1987-01-01

    The role of orbit crowding and cloud-cloud collisions in the formation of GMCs and their organization in global spiral structure is investigated. Both N-body simulations of the cloud system and a detailed analysis of individual particle orbits are used to develop a conceptual understanding of how individual clouds participate in the collective density response. Detailed comparisons are made between a representative cloud-particle simulation in which the cloud particles collide inelastically with one another and give birth to and subsequently interact with young star associations and stripped down simulations in which the cloud particles are allowed to follow ballistic orbits in the absence of cloud-cloud collisions or any star formation processes. Orbit crowding is then related to the behavior of individual particle trajectories in the galactic potential field. The conceptual picture of how GMCs are formed in the clumpy ISMs of spiral galaxies is formulated, and the results are compared in detail with those published by other authors. 68 references

  9. Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

    Science.gov (United States)

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

    2017-01-01

    The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

  10. MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km V5.1

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS was launched aboard the Aqua satellite on May 04, 2002 (1:30 pm equator crossing time) as part of NASA's Earth Observing System (EOS) mission. MODIS with its...

  11. Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site

    Science.gov (United States)

    Dong, Xiquan; Minnis, Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

    2008-02-01

    Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-h interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30 km × 30 km box centered on the ARM SGP site. Two data sets were analyzed: all of the data (ALL), which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 ± 0.542 km and 0.108 ± 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 ± 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km-1. On the basis of a total of 43 samples, the means and standard deviations of the differences between the daytime

  12. Frequency of Deep Convective Clouds and Global Warming

    Science.gov (United States)

    Aumann, Hartmut H.; Teixeira, Joao

    2008-01-01

    This slide presentation reviews the effect of global warming on the formation of Deep Convective Clouds (DCC). It concludes that nature responds to global warming with an increase in strong convective activity. The frequency of DCC increases with global warming at the rate of 6%/decade. The increased frequency of DCC with global warming alone increases precipitation by 1.7%/decade. It compares the state of the art climate models' response to global warming, and concludes that the parametrization of climate models need to be tuned to more closely emulate the way nature responds to global warming.

  13. The role of clouds and oceans in global greenhouse warming

    International Nuclear Information System (INIS)

    Hoffert, M.I.

    1992-12-01

    During the past three years we have conducted several studies using models and a combination of satellite data, in situ meteorological and oceanic data, and paleoclimate reconstructions, under the DoE program, ''Quantifying the Link Between Change in Radiative Balance and Atmospheric Temperature''. Our goals were to investigate effects of global cloudiness variations on global climate and their implications for cloud feedback and continue development and application of NYU transient climate/ocean models, with emphasis on coupled effects of greenhouse warming and feedbacks by both the clouds and oceans. Our original research plan emphasized the use of cloud, surface temperature and ocean data sets interpreted by focused climate/ocean models to develop a cloud radiative forcing scenario for the past 100 years and to assess the transient climate response; to narrow key uncertainties in the system; and to identify those aspects of the climate system most likely to be affected by greenhouse warming over short, medium and long time scales

  14. Variations of Global Terrestrial Primary Production Observed by Moderate Resolution Imaging Spectroradiometer (MODIS) From 2000 to 2005

    Science.gov (United States)

    Zhao, M.; Running, S.; Heinsch, F. A.

    2006-12-01

    Since the first Earth Observing System (EOS) satellite Terra was launched in December 1999 and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra began to provide data in February 2000, we have had six-year MODIS global 1-km terrestrial Gross and Net Primary Production (GPP &NPP) datasets. In this article, we present the variations (seasonality and inter-annual variability) of global GPP/NPP from the latest improved Collection 4.8 (C4.8) MODIS datasets for the past six-year (2000 - 2005), as well as improvements of the algorithm, validations of GPP and NPP. Validation results show that the C4.8 data have higher accuracy and quality than the previous version. Analyses of the variations in GPP/NPP show that GPP not only can reflect strong seasonality of photosynthesis activities by plants in mid- and high-latitude, but importantly, can reveal enhanced growth of Amazon rainforests during dry season, consistent with the reports by Huete et al. (2006) on GRL. Spatially, plants over mid- and high-latitude (north to 22.5°N) are the major contributor of global GPP seasonality. Inter-annual variability of MODIS NPP for 2000 - 2005 reveals the negative effects of major droughts on carbon sequestration at the regional and continental scales. A striking phenomenon is that the severe drought in 2005 over Amazon reduced NPP, indicating water availability becomes the dominant limiting factor rather than solar radiation under normal conditions. GMAO and NCEP driven global total NPPs have the similar interannual anomalies, and they generally follow the inverted CO2 growth rate anomaly with correlation of 0.85 and 0.91, respectively, which are higher than the correlation of 0.7 found by Nemani et al. (2003) on Science. Though there are only 6 years of MODIS data, results show that global NPP decreased from 2000 to 2005, and spatially most decreased NPP areas are in tropic and south hemisphere.

  15. CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2B)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  16. CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2A

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  17. Aerosol-cloud interactions from urban, regional to global scales

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yuan [California Institute of Technology, Pasadena, CA (United States). Seismological Lab.

    2015-10-01

    The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

  18. Aerosol-cloud interactions from urban, regional to global scales

    International Nuclear Information System (INIS)

    Wang, Yuan

    2015-01-01

    The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

  19. A new map of global urban extent from MODIS satellite data

    International Nuclear Information System (INIS)

    Schneider, A; Friedl, M A; Potere, D

    2009-01-01

    Although only a small percentage of global land cover, urban areas significantly alter climate, biogeochemistry, and hydrology at local, regional, and global scales. To understand the impact of urban areas on these processes, high quality, regularly updated information on the urban environment-including maps that monitor location and extent-is essential. Here we present results from efforts to map the global distribution of urban land use at 500 m spatial resolution using remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our approach uses a supervised decision tree classification algorithm that we process using region-specific parameters. An accuracy assessment based on sites from a stratified random sample of 140 cities shows that the new map has an overall accuracy of 93% (k = 0.65) at the pixel level and a high level of agreement at the city scale (R 2 = 0.90). Our results (available at http://sage.wisc.edu/urbanenvironment.html) also reveal that the land footprint of cities occupies less than 0.5% of the Earth's total land area.

  20. Study on generation and sharing of on-demand global seamless data—Taking MODIS NDVI as an example

    Science.gov (United States)

    Shen, Dayong; Deng, Meixia; Di, Liping; Han, Weiguo; Peng, Chunming; Yagci, Ali Levent; Yu, Genong; Chen, Zeqiang

    2013-04-01

    By applying advanced Geospatial Data Abstraction Library (GDAL) and BigTIFF technology in a Geographical Information System (GIS) with Service Oriented Architecture (SOA), this study has derived global datasets using tile-based input data and implemented Virtual Web Map Service (VWMS) and Virtual Web Coverage Service (VWCS) to provide software tools for visualization and acquisition of global data. Taking MODIS Normalized Difference Vegetation Index (NDVI) as an example, this study proves the feasibility, efficiency and features of the proposed approach.

  1. Cloud manufacturing distributed computing technologies for global and sustainable manufacturing

    CERN Document Server

    Mehnen, Jörn

    2013-01-01

    Global networks, which are the primary pillars of the modern manufacturing industry and supply chains, can only cope with the new challenges, requirements and demands when supported by new computing and Internet-based technologies. Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing introduces a new paradigm for scalable service-oriented sustainable and globally distributed manufacturing systems.   The eleven chapters in this book provide an updated overview of the latest technological development and applications in relevant research areas.  Following an introduction to the essential features of Cloud Computing, chapters cover a range of methods and applications such as the factors that actually affect adoption of the Cloud Computing technology in manufacturing companies and new geometrical simplification method to stream 3-Dimensional design and manufacturing data via the Internet. This is further supported case studies and real life data for Waste Electrical ...

  2. Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

    Science.gov (United States)

    Zhang, Ping; Imhoff, Marc L.; Wolfe, Robert E.; Bounoua, Lahouari

    2010-01-01

    Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship with development intensity, size, and ecological setting for more than 3000 urban settlements globally. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby nonurban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to ensure objective intercomparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass shrubs biomes; and only a weak UHI or sometimes an urban heat sink (UHS) in cities in arid and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) with the difference in vegetation density between urban and rural zones represented by the MODIS normalized difference vegetation index (NDVI). Globally averaged, the daytime UHI amplitude for all settlements is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers compared with 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude, with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variance is explained by ISA for urban settlements within forests at mid to high latitudes. This

  3. Some Technical Aspects of a CALIOP and MODIS Data Analysis that Examines Near-Cloud Aerosol Properties as a Function of Cloud Fraction

    Science.gov (United States)

    Varnai, Tamas; Yang, Weidong; Marshak, Alexander

    2016-01-01

    CALIOP shows stronger near-cloud changes in aerosol properties at higher cloud fractions. Cloud fraction variations explain a third of near-cloud changes in overall aerosol statistics. Cloud fraction and aerosol particle size distribution have a complex relationship.

  4. Comparison of Marine Boundary Layer Cloud Properties from CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

    Science.gov (United States)

    Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

    2014-01-01

    Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km×30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R(sup 2) = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km× 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 micrometers is 1.3 micrometers larger than that from the ARM retrievals (12.8 micrometers), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm( exp -2) less than its ARM counterpart (114.2 gm( exp-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50

  5. Comparison of Marine Boundary Layer Cloud Properties From CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

    Science.gov (United States)

    Dong, X.; Xi, B.; Minnis, P.; Sun-Mack, S.

    2014-12-01

    Marine Boundary Layer (MBL) cloud properties derived for the NASA CERES Project using Terra and Aqua MODIS data are compared with observations taken at DOE ARM Mobile Facility at the Azores site from Jun. 2009 to Dec. 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1-hour interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30×30 km2 grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud-top/base heights (Htop/Hbase) were determined from cloud-top/base temperatures (Ttop/Tbase) using a regional boundary-layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2=0.82 and 0.84, respectively). In general, the cloud-top comparisons agree better than cloud-base comparisons because the CM Tbase and Hbase are secondary product determined from Ttop and Htop. No significant day-night difference was found in the analyses. The comparisons of microphysical properties reveal that, when averaged over a 30x30 km2 area, the CM-retrieved cloud-droplet effective radius (re) is 1.3 µm larger than that from the ARM retrievals (12.8 µm). While the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (τ, 9.6 vs. 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using effective radius retrieved at 2.1-µm channel to calculate LWP can reduce the difference between the CM and ARM from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CM LWP and re

  6. Global cloud condensation nuclei influenced by carbonaceous combustion aerosol

    Directory of Open Access Journals (Sweden)

    D. V. Spracklen

    2011-09-01

    Full Text Available Black carbon in carbonaceous combustion aerosol warms the climate by absorbing solar radiation, meaning reductions in black carbon emissions are often perceived as an attractive global warming mitigation option. However, carbonaceous combustion aerosol can also act as cloud condensation nuclei (CCN so they also cool the climate by increasing cloud albedo. The net radiative effect of carbonaceous combustion aerosol is uncertain because their contribution to CCN has not been evaluated on the global scale. By combining extensive observations of CCN concentrations with the GLOMAP global aerosol model, we find that the model is biased low (normalised mean bias = −77 % unless carbonaceous combustion aerosol act as CCN. We show that carbonaceous combustion aerosol accounts for more than half (52–64 % of global CCN with the range due to uncertainty in the emitted size distribution of carbonaceous combustion particles. The model predicts that wildfire and pollution (fossil fuel and biofuel carbonaceous combustion aerosol causes a global mean cloud albedo aerosol indirect effect of −0.34 W m−2, with stronger cooling if we assume smaller particle emission size. We calculate that carbonaceous combustion aerosol from pollution sources cause a global mean aerosol indirect effect of −0.23 W m−2. The small size of carbonaceous combustion particles from fossil fuel sources means that whilst pollution sources account for only one-third of the emitted mass they cause two-thirds of the cloud albedo aerosol indirect effect that is due to carbonaceous combustion aerosol. This cooling effect must be accounted for, along with other cloud effects not studied here, to ensure that black carbon emissions controls that reduce the high number concentrations of fossil fuel particles have the desired net effect on climate.

  7. Atlantic Multidecadal Oscillation footprint on global high cloud cover

    Science.gov (United States)

    Vaideanu, Petru; Dima, Mihai; Voiculescu, Mirela

    2017-12-01

    Due to the complexity of the physical processes responsible for cloud formation and to the relatively short satellite database of continuous data records, cloud behavior in a warming climate remains uncertain. Identifying physical links between climate modes and clouds would contribute not only to a better understanding of the physical processes governing their formation and dynamics, but also to an improved representation of the clouds in climate models. Here, we identify the global footprint of the Atlantic Multidecadal Oscillation (AMO) on high cloud cover, with focus on the tropical and North Atlantic, tropical Pacific and on the circum-Antarctic sector. In the tropical band, the sea surface temperature (SST) and high cloud cover (HCC) anomalies are positively correlated, indicating a dominant role played by convection in mediating the influence of the AMO-related SST anomalies on the HCC field. The negative SST-HCC correlation observed in North Atlantic could be explained by the reduced meridional temperature gradient induced by the AMO positive phase, which would be reflected in less storms and negative HCC anomalies. A similar negative SST-HCC correlation is observed around Antarctica. The corresponding negative correlation around Antarctica could be generated dynamically, as a response to the intensified upward motion in the Ferrel cell. Despite the inherent imperfection of the observed and reanalysis data sets, the AMO footprint on HCC is found to be robust to the choice of dataset, statistical method, and specific time period considered.

  8. MODIS-Derived 1.64 micron white-sky albedo on a global, 1-minute equal angle grid (Collection 004 and 005)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Filled Land Surface Albedo Product is a global data set of spatially complete albedo maps. It was derived from the MODIS MOD43B3 Land product and includes both...

  9. Clouds and the extratropical circulation response to global warming in a hierarchy of global atmosphere models

    Science.gov (United States)

    Voigt, A.

    2017-12-01

    Climate models project that global warming will lead to substantial changes in extratropical jet streams. Yet, many quantitative aspects of warming-induced jet stream changes remain uncertain, and recent work has indicated an important role of clouds and their radiative interactions. Here, I will investigate how cloud-radiative changes impact the zonal-mean extratropical circulation response under global warming using a hierarchy of global atmosphere models. I will first focus on aquaplanet setups with prescribed sea-surface temperatures (SSTs), which reproduce the model spread found in realistic simulations with interactive SSTs. Simulations with two CMIP5 models MPI-ESM and IPSL-CM5A and prescribed clouds show that half of the circulation response can be attributed to cloud changes. The rise of tropical high-level clouds and the upward and poleward movement of midlatitude high-level clouds lead to poleward jet shifts. High-latitude low-level cloud changes shift the jet poleward in one model but not in the other. The impact of clouds on the jet operates via the atmospheric radiative forcing that is created by the cloud changes and is qualitatively reproduced in a dry Held-Suarez model, although the latter is too sensitive because of its simplified treatment of diabatic processes. I will then show that the aquaplanet results also hold when the models are used in a realistic setup that includes continents and seasonality. I will further juxtapose these prescribed-SST simulations with interactive-SST simulations and show that atmospheric and surface cloud-radiative interactions impact the jet poleward jet shifts in about equal measure. Finally, I will discuss the cloud impact on regional and seasonal circulation changes.

  10. Global two-channel AVHRR aerosol climatology: effects of stratospheric aerosols and preliminary comparisons with MODIS and MISR retrievals

    International Nuclear Information System (INIS)

    Geogdzhayev, Igor V.; Mishchenko, Michael I.; Liu Li; Remer, Lorraine

    2004-01-01

    We present an update on the status of the global climatology of the aerosol column optical thickness and Angstrom exponent derived from channel-1 and -2 radiances of the Advanced Very High Resolution Radiometer (AVHRR) in the framework of the Global Aerosol Climatology Project (GACP). The latest version of the climatology covers the period from July 1983 to September 2001 and is based on an adjusted value of the diffuse component of the ocean reflectance as derived from extensive comparisons with ship sun-photometer data. We use the updated GACP climatology and Stratospheric Aerosol and Gas Experiment (SAGE) data to analyze how stratospheric aerosols from major volcanic eruptions can affect the GACP aerosol product. One possible retrieval strategy based on the AVHRR channel-1 and -2 data alone is to infer both the stratospheric and the tropospheric aerosol optical thickness while assuming fixed microphysical models for both aerosol components. The second approach is to use the SAGE stratospheric aerosol data in order to constrain the AVHRR retrieval algorithm. We demonstrate that the second approach yields a consistent long-term record of the tropospheric aerosol optical thickness and Angstrom exponent. Preliminary comparisons of the GACP aerosol product with MODerate resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectro-Radiometer aerosol retrievals show reasonable agreement, the GACP global monthly optical thickness being lower than the MODIS one by approximately 0.03. Larger differences are observed on a regional scale. Comparisons of the GACP and MODIS Angstrom exponent records are less conclusive and require further analysis

  11. Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

    Science.gov (United States)

    Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

    2018-03-07

    Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

  12. SST, Aqua MODIS, NPP, 0.05 degrees, Global, Nighttime (4 microns), Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides SST data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard...

  13. Global NOAA CoastWatch Chlorophyll Frontal Product from MODIS/Aqua (NCEI Accession 0110333)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS/Aqua chlorophyll frontal products: the NOAA Okeanos operational production system produces near real-time chlorophyll frontal products (magnitude and...

  14. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  15. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Chlorophyll (CHL) Global Mapped Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  16. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index Land Reflectance Global Binned Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  17. Remote Sensing Reflectance at 667 nm, Aqua MODIS, NPP, 0.05 degrees, Global, Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures the remote sensing reflectance (Rrs) at 667nm. This can be used to view very high concentrations of phytoplankton in the very surface of the water.

  18. SST, Terra MODIS, NPP, 0.05 degrees, Global, Nighttime (4 microns), Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides SST data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard...

  19. SST, Aqua MODIS, NPP, 0.05 degrees, Global, Daytime, Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch provides SST data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard...

  20. Primary Productivity, NASA Aqua MODIS and GOES Imager, 0.1 degrees, Global, EXPERIMENTAL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Primary Productivity is calculated from NASA Aqua MODIS Chl a and NOAA GOES Imager SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for scientific...

  1. Chromophoric Dissolved Organic Material, Aqua MODIS, NPP, 0.05 degrees, Global, Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS data is used to develop an index of the amount of chromophoric dissolved organic material (CDOM) in the surface waters. CDOM absorbs heavily in the blue...

  2. Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Photosynthetically Available Radiation (PAR) Global Binned Data, reprocesing v2018

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  3. Primary Productivity, NASA Aqua MODIS, 4.4 km, Global, EXPERIMENTAL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Primary Productivity is calculated from NASA Aqua MODIS Chl a SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for scientific evaluation by professional...

  4. Photosynthetically Available Radiation, Aqua MODIS, NPP, 0.05 degrees, Global, Science Quality

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — MODIS measures photosynthetically available radiation that may be used to mode primary productivity. THIS IS AN EXPERIMENTAL PRODUCT: intended strictly for...

  5. Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel

    OpenAIRE

    Stubenrauch , C.J.; Rossow , W.B.; Kinne , S.; Ackerman , S.; Cesana , G.; Chepfer , H.; Di Girolamo , L.; Getzewich , B.; Guignard , A.; Heidinger , A.; Maddux , B.C.; Menzel , W.P.; Minnis , P.; Pearl , C.; Platnick , S.

    2013-01-01

    International audience; The Global Energy and Water Cycle Experiment (GEWEX) Radiation Panel initiated the GEWEX Cloud Assessment in 2005 to compare available, global, long-term cloud data products with the International Satellite Cloud Climatology Project (ISCCP). The GEWEX Cloud Assessment database included cloud properties retrieved from different satellite sensor measurements, taken at various local times and over various time periods. The relevant passive satellite sensors measured radia...

  6. Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

    Science.gov (United States)

    Famiglietti, C.; Fisher, J.; Halverson, G. H.

    2017-12-01

    This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

  7. Application-Ready Expedited MODIS Data for Operational Land Surface Monitoring of Vegetation Condition

    Directory of Open Access Journals (Sweden)

    Jesslyn F. Brown

    2015-12-01

    Full Text Available Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1, the eMODIS Normalized Difference Vegetation Index (NDVI maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra or afternoon (Aqua orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

  8. Local to Global Scale Time Series Analysis of US Dryland Degradation Using Landsat, AVHRR, and MODIS

    Science.gov (United States)

    Washington-Allen, R. A.; Ramsey, R. D.; West, N. E.; Kulawardhana, W.; Reeves, M. C.; Mitchell, J. E.; Van Niel, T. G.

    2011-12-01

    Drylands cover 41% of the terrestrial land surface and annually generate $1 trillion in ecosystem goods and services for 38% of the global population, yet estimates of the global extent of Dryland degradation is uncertain with a range of 10 - 80%. It is currently understood that Drylands exhibit topological complexity including self-organization of parameters of different levels-of-organization, e.g., ecosystem and landscape parameters such as soil and vegetation pattern and structure, that gradually or discontinuously shift to multiple basins of attraction in response to herbivory, fire, and climatic drivers at multiple spatial and temporal scales. Our research has shown that at large geographic scales, contemporaneous time series of 10 to 20 years for response and driving variables across two or more spatial scales is required to replicate and differentiate between the impact of climate and land use activities such as commercial grazing. For example, the Pacific Decadal Oscillation (PDO) is a major driver of Dryland net primary productivity (NPP), biodiversity, and ecological resilience with a 10-year return interval, thus 20 years of data are required to replicate its impact. Degradation is defined here as a change in physiognomic composition contrary to management goals, a persistent reduction in vegetation response, e.g., NPP, accelerated soil erosion, a decline in soil quality, and changes in landscape configuration and structure that lead to a loss of ecosystem function. Freely available Landsat, Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradimeter (MODIS) archives of satellite imagery exist that provide local to global spatial coverage and time series between 1972 to the present from which proxies of land degradation can be derived. This paper presents time series assessments between 1972 and 2011 of US Dryland degradation including early detection of dynamic regime shifts in the Mojave and landscape pattern and

  9. Land cover in Upper Egypt assessed using regional and global land cover products derived from MODIS imagery.

    Science.gov (United States)

    Fuller, Douglas O; Parenti, Michael S; Gad, Adel M; Beier, John C

    2012-01-01

    Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of MODIS 250 m NDVI data and Landsat imagery to identify areas that changed from 2001-2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby water bodies. We used two different methods of time series analysis -- principal components (PCA) and harmonic decomposition (HD), applied to the MODIS 250 m NDVI images to derive simple three-class land cover maps and then assessed their accuracy using a set of reference polygons derived from 30 m Landsat 5 and 7 imagery. We analyzed our MODIS 250 m maps against a new MODIS global land cover product (MOD12Q1 collection 5) to assess whether regionally specific mapping approaches are superior to a standard global product. Results showed that the accuracy of the PCA-based product was greater than the accuracy of either the HD or MOD12Q1 products for the years 2001, 2003, and 2008. However, the accuracy of the PCA product was only slightly better than the MOD12Q1 for 2001 and 2003. Overall, the results suggest that our PCA-based approach produces a high level of user and producer accuracies, although the MOD12Q1 product also showed consistently high accuracy. Overlay of 2001-2008 PCA-based maps showed a net increase of 12 129 ha of irrigated vegetation, with the largest increase found from 2006-2008 around the Districts of Edfu and Kom Ombo. This result was unexpected in light of ambitious government plans to develop 336 000 ha of irrigated agriculture around the Toshka Lakes.

  10. Validation of the MODIS Collection 6 MCD64 Global Burned Area Product

    Science.gov (United States)

    Boschetti, L.; Roy, D. P.; Giglio, L.; Stehman, S. V.; Humber, M. L.; Sathyachandran, S. K.; Zubkova, M.; Melchiorre, A.; Huang, H.; Huo, L. Z.

    2017-12-01

    The research, policy and management applications of satellite products place a high priority on rigorously assessing their accuracy. A number of NASA, ESA and EU funded global and continental burned area products have been developed using coarse spatial resolution satellite data, and have the potential to become part of a long-term fire Essential Climate Variable. These products have usually been validated by comparison with reference burned area maps derived by visual interpretation of Landsat or similar spatial resolution data selected on an ad hoc basis. More optimally, a design-based validation method should be adopted, characterized by the selection of reference data via probability sampling. Design based techniques have been used for annual land cover and land cover change product validation, but have not been widely used for burned area products, or for other products that are highly variable in time and space (e.g. snow, floods, other non-permanent phenomena). This has been due to the challenge of designing an appropriate sampling strategy, and to the cost and limited availability of independent reference data. This paper describes the validation procedure adopted for the latest Collection 6 version of the MODIS Global Burned Area product (MCD64, Giglio et al, 2009). We used a tri-dimensional sampling grid that allows for probability sampling of Landsat data in time and in space (Boschetti et al, 2016). To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat WRS path/rows is used. The TSA grid is then combined with the 16-day Landsat acquisition calendar to provide tri-dimensonal elements (voxels). This allows the implementation of a sampling design where not only the location but also the time interval of the reference data is explicitly drawn through stratified random sampling. The novel sampling approach was used for the selection of a reference dataset consisting of 700

  11. Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET

    Science.gov (United States)

    Mishchenko, Michael I.; Liu, Li; Geogdzhayev, Igor V.; Travis, Larry D.; Cairns, Brian; Lacis, Andrew A.

    2010-01-01

    We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

  12. Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis

    Science.gov (United States)

    Moore, R. T.; Hansen, M. C.

    2011-12-01

    Google Earth Engine is a new technology platform that enables monitoring and measurement of changes in the earth's environment, at planetary scale, on a large catalog of earth observation data. The platform offers intrinsically-parallel computational access to thousands of computers in Google's data centers. Initial efforts have focused primarily on global forest monitoring and measurement, in support of REDD+ activities in the developing world. The intent is to put this platform into the hands of scientists and developing world nations, in order to advance the broader operational deployment of existing scientific methods, and strengthen the ability for public institutions and civil society to better understand, manage and report on the state of their natural resources. Earth Engine currently hosts online nearly the complete historical Landsat archive of L5 and L7 data collected over more than twenty-five years. Newly-collected Landsat imagery is downloaded from USGS EROS Center into Earth Engine on a daily basis. Earth Engine also includes a set of historical and current MODIS data products. The platform supports generation, on-demand, of spatial and temporal mosaics, "best-pixel" composites (for example to remove clouds and gaps in satellite imagery), as well as a variety of spectral indices. Supervised learning methods are available over the Landsat data catalog. The platform also includes a new application programming framework, or "API", that allows scientists access to these computational and data resources, to scale their current algorithms or develop new ones. Under the covers of the Google Earth Engine API is an intrinsically-parallel image-processing system. Several forest monitoring applications powered by this API are currently in development and expected to be operational in 2011. Combining science with massive data and technology resources in a cloud-computing framework can offer advantages of computational speed, ease-of-use and collaboration, as

  13. Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

    Science.gov (United States)

    Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

    2017-04-01

    The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

  14. Global atmospheric particle formation from CERN CLOUD measurements

    Science.gov (United States)

    Dunne, Eimear M.; Gordon, Hamish; Carslaw, Kenneth S.

    2017-04-01

    New particle formation (or nucleation) is acknowledged as a significant source of climate-relevant aerosol throughout the atmosphere. However, performing atmospherically relevant nucleation experiments in a laboratory setting is extremely challenging. As a result, until now, the parameterisations used to represent new particle formation in global aerosol models were largely based on in-situ observations or theoretical nucleation models, and usually only represented the binary H2SO4-H2O system. Several different chemicals can affect particle formation rates, even at extremely low trace concentrations, which are technically challenging to measure directly. Nucleation rates also respond to environmental changes in e.g. temperature in a highly non-linear fashion. The CERN CLOUD experiment was designed to provide the most controlled and accurate nucleation rate measurements to date, over the full range of free tropospheric temperatures and down to sulphuric acid concentrations of the order of 105 cm-3. We will present a parameterisation of inorganic nucleation rates for use in global models, based on these measurements, which includes four separate nucleation pathways: binary neutral, binary ion-induced, ternary neutral, and ternary ion-induced. Both inorganic and organic nucleation parameterisations derived from CLOUD measurements have been implemented in the GLOMAP global aerosol model. The parameterisations depend on temperature and on concentrations of sulphuric acid, ammonia, organic vapours, and ions. One of CLOUD's main original goals was to determine the sensitivity of atmospheric aerosol to changes in the nucleation rate over a solar cycle. We will show that, in a present-day atmosphere, the changes in climate-relevant aerosol (in the form of cloud-level cloud condensation nuclei) over a solar cycle are on average about 0.1%, with local changes of less than 1%. In contrast, anthropogenic changes in ammonia since pre-industrial times were estimated to have a

  15. The global mean energy balance under cloud-free conditions

    Science.gov (United States)

    Wild, Martin; Hakuba, Maria; Folini, Dois; Ott, Patricia; Long, Charles

    2017-04-01

    A long standing problem of climate models is their overestimation of surface solar radiation not only under all-sky, but also under clear-sky conditions (Wild et al. 1995, Wild et al. 2006). This overestimation reduced over time in consecutive model generations due to the simulation of stronger atmospheric absorption. Here we analyze the clear sky fluxes of the latest climate model generation from the Coupled Model Intercomparison Project Phase 5 (CMIP5) against an expanded and updated set of direct observations from the Baseline Surface Radiation Network (BSRN). Clear sky climatologies from these sites have been composed based on the Long and Ackermann (2000) clear sky detection algorithm (Hakuba et al. 2017), and sampling issues when comparing with model simulated clear sky fluxes have been analyzed in Ott (2017). Overall, the overestimation of clear sky insolation in the CMIP5 models is now merely 1-2 Wm-2 in the multimodel mean, compared to 4 Wm-2 in CMIP3 and 6 Wm-2 in AMIPII (Wild et al. 2006). Still a considerable spread in the individual model biases is apparent, ranging from -2 Wm-2 to 10 Wm-2 when averaged over 53 globally distributed BSRN sites. This bias structure is used to infer best estimates for present day global mean clear sky insolation, following an approach developped in Wild et al. (2013, 2015, Clim. Dyn.) for all sky fluxes. Thereby the flux biases in the various models are linearly related to their respective global means. A best estimate can then be inferred from the linear regression at the intersect where the bias against the surface observations becomes zero. This way we obtain a best estimate of 247 Wm-2 for the global mean insolation at the Earth surface under cloud free conditions, and a global mean absorbed solar radiation of 214 Wm-2 in the cloud-free atmosphere, assuming a global mean surface albedo of 13.5%. Combined with a best estimate for the net influx of solar radiation at the Top of Atmosphere under cloud free conditions

  16. Evaluating the Accuracy of MODIS Products in the Southern Scean Using Tagged Marine Predators, and Measuring Significant Change in 12 Years of [Chl-a], Zeu and Cloud Fraction Data.

    Science.gov (United States)

    Biermann, L.; Boehme, L.; Guinet, C.

    2016-02-01

    The Southern Ocean is vital to the functioning of our global atmospheric and marine systems. However, this key ocean is also measurably responsive to the Southern Annular Mode (SAM), the dominant mode of atmospheric variability in the Southern Hemisphere. Decreased ozone and increases in greenhouse gases appear to be forcing the SAM towards its positive phase, significantly changing wind patterns and, thus, altering mixing and circulation regimes of Southern Ocean waters. Inevitably, these changes must impact on patterns of phytoplankton abundance and distribution. Using remotely sensed data that have been evaluated alongside in situ data collected by tagged southern elephant seals, this work investigates if changes to summer phytoplankton abundance and distribution in the Southern Ocean can already be measured in the 12-year MODIS record. Patterns and trends in surface chlorophyll-a concentration ([Chl-a]), the depth of the 1% light level (Zeu) and mean cloud fraction are examined over time, as well as relative to the SAM. Trends in [Chl-a] and Zeu over the months of October, November and December suggest overall declines in surface phytoplankton, and shifts in timing of blooms. Indeed, by January and February over the 12-year timeseries, trends reverse to suggest increases in phytoplankton abundance. Relative to the increasingly positive SAM, trends of overall decline in phytoplankton abundance are significant only over Decembers. Trends in cloud cover are more difficult to interpret but the Atlantic Ocean appears to be becoming less cloudy, the southern sector of the Pacific Ocean appears to be becoming cloudier, and that the southern sector of the Indian Ocean is most variable over time. Only the increase in cloud over the southern Pacific in Decembers appears to be significantly related to changes to the SAM. Interestingly, in no cases were the changes to [Chl-a], Zeu or cloud cover strictly zonal. The asymmetry of these results reinforces findings from

  17. Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

    Science.gov (United States)

    Geogdzhayev, Igor V.; Mishchenko, Michael I.

    2015-01-01

    A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995-2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003-2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the

  18. Modification of cirrus clouds to reduce global warming

    International Nuclear Information System (INIS)

    Mitchell, David L; Finnegan, William

    2009-01-01

    Greenhouse gases and cirrus clouds regulate outgoing longwave radiation (OLR) and cirrus cloud coverage is predicted to be sensitive to the ice fall speed which depends on ice crystal size. The higher the cirrus, the greater their impact is on OLR. Thus by changing ice crystal size in the coldest cirrus, OLR and climate might be modified. Fortunately the coldest cirrus have the highest ice supersaturation due to the dominance of homogeneous freezing nucleation. Seeding such cirrus with very efficient heterogeneous ice nuclei should produce larger ice crystals due to vapor competition effects, thus increasing OLR and surface cooling. Preliminary estimates of this global net cloud forcing are more negative than -2.8 W m -2 and could neutralize the radiative forcing due to a CO 2 doubling (3.7 W m -2 ). A potential delivery mechanism for the seeding material is already in place: the airline industry. Since seeding aerosol residence times in the troposphere are relatively short, the climate might return to its normal state within months after stopping the geoengineering experiment. The main known drawback to this approach is that it would not stop ocean acidification. It does not have many of the drawbacks that stratospheric injection of sulfur species has.

  19. Modification of cirrus clouds to reduce global warming

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, David L; Finnegan, William, E-mail: david.mitchell@dri.ed [Desert Research Institute, Reno, NV 89512-1095 (United States)

    2009-10-15

    Greenhouse gases and cirrus clouds regulate outgoing longwave radiation (OLR) and cirrus cloud coverage is predicted to be sensitive to the ice fall speed which depends on ice crystal size. The higher the cirrus, the greater their impact is on OLR. Thus by changing ice crystal size in the coldest cirrus, OLR and climate might be modified. Fortunately the coldest cirrus have the highest ice supersaturation due to the dominance of homogeneous freezing nucleation. Seeding such cirrus with very efficient heterogeneous ice nuclei should produce larger ice crystals due to vapor competition effects, thus increasing OLR and surface cooling. Preliminary estimates of this global net cloud forcing are more negative than -2.8 W m{sup -2} and could neutralize the radiative forcing due to a CO{sub 2} doubling (3.7 W m{sup -2}). A potential delivery mechanism for the seeding material is already in place: the airline industry. Since seeding aerosol residence times in the troposphere are relatively short, the climate might return to its normal state within months after stopping the geoengineering experiment. The main known drawback to this approach is that it would not stop ocean acidification. It does not have many of the drawbacks that stratospheric injection of sulfur species has.

  20. Global atmospheric particle formation from CERN CLOUD measurements.

    Science.gov (United States)

    Dunne, Eimear M; Gordon, Hamish; Kürten, Andreas; Almeida, João; Duplissy, Jonathan; Williamson, Christina; Ortega, Ismael K; Pringle, Kirsty J; Adamov, Alexey; Baltensperger, Urs; Barmet, Peter; Benduhn, Francois; Bianchi, Federico; Breitenlechner, Martin; Clarke, Antony; Curtius, Joachim; Dommen, Josef; Donahue, Neil M; Ehrhart, Sebastian; Flagan, Richard C; Franchin, Alessandro; Guida, Roberto; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Jokinen, Tuija; Kangasluoma, Juha; Kirkby, Jasper; Kulmala, Markku; Kupc, Agnieszka; Lawler, Michael J; Lehtipalo, Katrianne; Makhmutov, Vladimir; Mann, Graham; Mathot, Serge; Merikanto, Joonas; Miettinen, Pasi; Nenes, Athanasios; Onnela, Antti; Rap, Alexandru; Reddington, Carly L S; Riccobono, Francesco; Richards, Nigel A D; Rissanen, Matti P; Rondo, Linda; Sarnela, Nina; Schobesberger, Siegfried; Sengupta, Kamalika; Simon, Mario; Sipilä, Mikko; Smith, James N; Stozkhov, Yuri; Tomé, Antonio; Tröstl, Jasmin; Wagner, Paul E; Wimmer, Daniela; Winkler, Paul M; Worsnop, Douglas R; Carslaw, Kenneth S

    2016-12-02

    Fundamental questions remain about the origin of newly formed atmospheric aerosol particles because data from laboratory measurements have been insufficient to build global models. In contrast, gas-phase chemistry models have been based on laboratory kinetics measurements for decades. We built a global model of aerosol formation by using extensive laboratory measurements of rates of nucleation involving sulfuric acid, ammonia, ions, and organic compounds conducted in the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber. The simulations and a comparison with atmospheric observations show that nearly all nucleation throughout the present-day atmosphere involves ammonia or biogenic organic compounds, in addition to sulfuric acid. A considerable fraction of nucleation involves ions, but the relatively weak dependence on ion concentrations indicates that for the processes studied, variations in cosmic ray intensity do not appreciably affect climate through nucleation in the present-day atmosphere. Copyright © 2016, American Association for the Advancement of Science.

  1. Sensitivity to deliberate sea salt seeding of marine clouds - observations and model simulations

    OpenAIRE

    Alterskjaer, K.; Kristjansson, J. E.; Seland, O.

    2012-01-01

    Sea salt seeding of marine clouds to increase their albedo is a proposed technique to counteract or slow global warming. In this study, we first investigate the susceptibility of marine clouds to sea salt injections, using observational data of cloud droplet number concentration, cloud optical depth, and liquid cloud fraction from the MODIS (Moderate Resolution Imaging Spectroradiometer) instruments on board the Aqua and Terra satellites. We then compare the derived susceptibility function to...

  2. A GLOBAL REGISTRATION ALGORITHM OF THE SINGLE-CLOSED RING MULTI-STATIONS POINT CLOUD

    Directory of Open Access Journals (Sweden)

    R. Yang

    2018-04-01

    Full Text Available Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

  3. Combining observations and models to reduce uncertainty in the cloud response to global warming

    Science.gov (United States)

    Norris, J. R.; Myers, T.; Chellappan, S.

    2017-12-01

    Currently there is large uncertainty on how subtropical low-level clouds will respond to global warming and whether they will act as a positive feedback or negative feedback. Global climate models substantially agree on what changes in atmospheric structure and circulation will occur with global warming but greatly disagree over how clouds will respond to these changes in structure and circulation. An examination of models with the most realistic simulations of low-level cloudiness indicates that the model cloud response to atmospheric changes associated with global warming is quantitatively similar to the model cloud response to atmospheric changes at interannual time scales. For these models, the cloud response to global warming predicted by multilinear regression using coefficients derived from interannual time scales is quantitatively similar to the cloud response to global warming directly simulated by the model. Since there is a large spread among cloud response coefficients even among models with the most realistic cloud simulations, substitution of coefficients derived from satellite observations reduces the uncertainty range of the low-level cloud feedback. Increased sea surface temperature associated with global warming acts to reduce low-level cloudiness, which is partially offset by increased lower tropospheric stratification that acts to enhance low-level cloudiness. Changes in free-tropospheric relative humidity, subsidence, and horizontal advection have only a small impact on low-level cloud. The net reduction in subtropical low-level cloudiness increases absorption of solar radiation by the climate system, thus resulting in a weak positive feedback.

  4. Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

    Science.gov (United States)

    Putman, William M.

    2010-01-01

    NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

  5. MODIS/Aqua Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  6. MODIS/Aqua Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  7. MODIS/Terra Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  8. MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of...

  9. Quantitative Evaluation of MODIS Fire Radiative Power Measurement for Global Smoke Emissions Assessment

    Science.gov (United States)

    Ichoku, Charles; Ellison, Luke

    2011-01-01

    Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the MODIS sensors aboard the polar orbiting Terra and Aqua satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has steadily gained increasing recognition as an important parameter for facilitating the development of various scientific studies and applications relating to the quantitative characterization of biomass burning and their emissions. To establish the scientific integrity of the FRP as a stable quantity that can be measured consistently across a variety of sensors and platforms, with the potential of being utilized to develop a unified long-term climate data record of fire activity and impacts, it needs to be thoroughly evaluated, calibrated, and validated. Therefore, we are conducting a detailed analysis of the FRP products from MODIS to evaluate the uncertainties associated with them, such as those due to the effects of satellite variable observation geometry and other factors, in order to establish their error budget for use in diverse scientific research and applications. In this presentation, we will show recent results of the MODIS FRP uncertainty analysis and error mitigation solutions, and demonstrate

  10. Modification of cirrus clouds to reduce global warming

    Science.gov (United States)

    Mitchell, D. L.

    2009-12-01

    Since both greenhouse gases and cirrus clouds strongly affect outgoing longwave radiation (OLR) with no affect or less affect on solar radiation, respectively, an attempt to delay global warming to buy time for emission reduction strategies to work might naturally target cirrus clouds. Cirrus having optical depths competition effects, thus increasing OLR and surface cooling. Preliminary estimates of this global net cloud forcing via GCM simulations are more negative than -2.8 W m-2 and could neutralize the radiative forcing due to a CO2 doubling (3.7 W m-2). This cirrus engineered net forcing is due to (1) reduced cirrus coverage and (2) reduced upper tropospheric water vapor, due to enhanced ice sedimentation. The implementation of this climate engineering could use the airline industry to disperse the seeding material. Commercial airliners typically fly at temperatures between -40 and -60 deg. C (where homogeneous freezing nucleation dominates). Weather modification research has developed ice nucleating substances that are extremely effective at these cold temperatures, are non-toxic and are relatively inexpensive. The seeding material could be released in both clear and cloudy conditions to build up a background concentration of efficient ice nuclei so that non-contrail cirrus will experience these nuclei and grow larger ice crystals. Flight corridors are denser in the high- and mid-latitudes where global warming is more severe. A risk with any geoengineering experiment is that it could affect climate in unforeseen ways, causing more harm than good. Since seeding aerosol residence times in the troposphere are 1-2 weeks, the climate might return back to its normal state within a few months after stopping the geoengineering. A drawback to this approach is that it would not stop ocean acidification. It may not have many of the draw-backs that stratospheric injection of sulfur species has, such as ozone destruction, decreased solar radiation possibly altering the

  11. A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts over the Global Oceans

    Science.gov (United States)

    Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

    2015-01-01

    The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the post frontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime post frontal precipitation.

  12. Effects of aerosol/cloud interactions on the global radiation budget

    International Nuclear Information System (INIS)

    Chuang, C.C.; Penner, J.E.

    1994-01-01

    Aerosols may modify the microphysics of clouds by acting as cloud condensation nuclei (CCN), thereby enhancing the cloud reflectivity. Aerosols may also alter precipitation development by affecting the mean droplet size, thereby influencing cloud lifetimes and modifying the hydrological cycle. Clouds have a major effect on climate, but aerosol/cloud interactions have not been accounted for in past climate model simulations. However, the worldwide steady rise of global pollutants and emissions makes it imperative to investigate how atmospheric aerosols affect clouds and the global radiation budget. In this paper, the authors examine the relationship between aerosol and cloud drop size distributions by using a detailed micro-physical model. They parameterize the cloud nucleation process in terms of local aerosol characteristics and updraft velocity for use in a coupled climate/chemistry model to predict the magnitude of aerosol cloud forcing. Their simulations indicate that aerosol/cloud interactions may result in important increases in reflected solar radiation, which would mask locally the radiative forcing from increased greenhouse gases. This work is aimed at improving the assessment of the effects of anthropogenic aerosols on cloud optical properties and the global radiation budget

  13. Global synthesis of long-term cloud condensation nuclei observations

    Science.gov (United States)

    Schmale, Julia; Henning, Silvia; Stratmann, Frank; Henzing, Bas; Schlag, Patrick; Aalto, Pasi; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Krüger, Mira; Jefferson, Anne; Whitehead, James; Carslaw, Ken; Yum, Seong Soo; Kristensson, Adam; Baltensperger, Urs; Gysel, Martin

    2016-04-01

    Cloud condensation nuclei (CCN) are aerosol particles with the ability to activate into droplets at a given super saturation and therefore influence the microphysical and optical properties of clouds. To predict cloud radiative properties understanding the spatial and temporal variability of CCN concentrations in different environments is important. However, currently, the effects of atmospheric particles on changes in cloud radiative forcing are still the largest contribution of uncertainty in climate forcing prediction (IPCC, 2013). Numerous intensive field campaigns have already explored detailed characteristics of CCN in many locations around the world. However, these rather short-term observations can generally not address seasonal or inter-annual variations and a comparison between campaign sites is difficult due to the higher influence of specific environmental circumstances on short-term measurements results. Here, we present results of more long-term CCN and aerosol number concentrations as well as size distribution data covering at least one full year between 2006 and 2014. The 12 locations include ACTRIS stations (http://www.actris.net/) in Europe, and further sites in North America, Brazil and Korea. The sites are located in different environments allowing for temporal and spatial characterization of CCN variability in different atmospheric regimes. Those include marine, remote-continental, boreal forest, rain forest, Arctic and monsoon-influenced environments, as well as boundary layer and free tropospheric conditions. The aerosol populations and their activation behavior show significant differences across the stations. While peak concentrations of CCN are observed in summer at the high altitude sites, in the Arctic the highest concentrations occur during the Haze period in spring. The rural-marine and rural-continental sites exhibit similar CCN concentration characteristics with a relatively flat annual cycle. At some stations, e.g. in the boreal

  14. Cloud Statistics and Discrimination in the Polar Regions

    Science.gov (United States)

    Chan, M.; Comiso, J. C.

    2012-12-01

    Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice

  15. Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

    2006-12-01

    During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

  16. A long-term time series of global and diffuse photosynthetically active radiation in the Mediterranean: interannual variability and cloud effects

    Directory of Open Access Journals (Sweden)

    P. Trisolino

    2018-06-01

    to produce small radiative effects on PAR in summer. The cloud radiative effect has been deseasonalized to remove the influence of annual irradiance variations. The monthly mean normalized CRE for global PAR can be well represented by a multi-linear regression with respect to monthly cloud fraction, cloud top pressure, and cloud optical thickness, as determined from satellite MODIS observations. The behaviour of the normalized CRE for diffuse PAR can not be satisfactorily described by a simple multi-linear model with respect to the cloud properties, due to its non-linear dependency, in particular on the cloud optical depth. The analysis suggests that about 77 % of the global PAR interannual variability may be ascribed to cloud variability in winter.

  17. Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

    Science.gov (United States)

    Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.; hide

    2012-01-01

    Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

  18. Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Hyelim [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Li, Zhanqing [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing (China)

    2012-12-15

    Knowledge of cloud properties and their vertical structure is important for meteorological studies due to their impact on both the Earth's radiation budget and adiabatic heating within the atmosphere. The objective of this study is to evaluate bulk cloud properties and vertical distribution simulated by the US National Oceanic and Atmospheric Administration National Centers for Environmental Prediction Global Forecast System (GFS) using three global satellite products. Cloud variables evaluated include the occurrence and fraction of clouds in up to three layers, cloud optical depth, liquid water path, and ice water path. Cloud vertical structure data are retrieved from both active (CloudSat/CALIPSO) and passive sensors and are subsequently compared with GFS model results. In general, the GFS model captures the spatial patterns of hydrometeors reasonably well and follows the general features seen in satellite measurements, but large discrepancies exist in low-level cloud properties. More boundary layer clouds over the interior continents were generated by the GFS model whereas satellite retrievals showed more low-level clouds over oceans. Although the frequencies of global multi-layer clouds from observations are similar to those from the model, latitudinal variations show discrepancies in terms of structure and pattern. The modeled cloud optical depth over storm track region and subtropical region is less than that from the passive sensor and is overestimated for deep convective clouds. The distributions of ice water path (IWP) agree better with satellite observations than do liquid water path (LWP) distributions. Discrepancies in LWP/IWP distributions between observations and the model are attributed to differences in cloud water mixing ratio and mean relative humidity fields, which are major control variables determining the formation of clouds. (orig.)

  19. Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products

    Science.gov (United States)

    Ginoux, Paul; Prospero, Joseph M.; Gill, Thomas E.; Hsu, N. Christina; Zhao, Ming

    2012-01-01

    Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

  20. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global Cloud-Permiting Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chidong [Univ. of Miami, Coral Gables, FL (United States)

    2016-08-14

    Motivated by the success of the AMIE/DYNAMO field campaign, which collected unprecedented observations of cloud and precipitation from the tropical Indian Ocean in Octber 2011 – March 2012, this project explored how such observations can be applied to assist the development of global cloud-permitting models through evaluating and correcting model biases in cloud statistics. The main accomplishment of this project were made in four categories: generating observational products for model evaluation, using AMIE/DYNAMO observations to validate global model simulations, using AMIE/DYNAMO observations in numerical studies of cloud-permitting models, and providing leadership in the field. Results from this project provide valuable information for building a seamless bridge between DOE ASR program’s component on process level understanding of cloud processes in the tropics and RGCM focus on global variability and regional extremes. In particular, experience gained from this project would be directly applicable to evaluation and improvements of ACME, especially as it transitions to a non-hydrostatic variable resolution model.

  1. A GLOBAL MAGNETIC TOPOLOGY MODEL FOR MAGNETIC CLOUDS. II

    Energy Technology Data Exchange (ETDEWEB)

    Hidalgo, M. A., E-mail: miguel.hidalgo@uah.es [Departamento de Fisica, Universidad de Alcala, Apartado 20, E-28871 Alcala de Henares, Madrid (Spain)

    2013-04-01

    In the present work, we extensively used our analytical approach to the global magnetic field topology of magnetic clouds (MCs), introduced in a previous paper, in order to show its potential and to study its physical consistency. The model assumes toroidal topology with a non-uniform (variable maximum radius) cross-section along them. Moreover, it has a non-force-free character and also includes the expansion of its cross-section. As is shown, the model allows us, first, to analyze MC magnetic structures-determining their physical parameters-with a variety of magnetic field shapes, and second, to reconstruct their relative orientation in the interplanetary medium from the observations obtained by several spacecraft. Therefore, multipoint spacecraft observations give the opportunity to infer the structure of this large-scale magnetic flux rope structure in the solar wind. For these tasks, we use data from Helios (A and B), STEREO (A and B), and Advanced Composition Explorer. We show that the proposed analytical model can explain quite well the topology of several MCs in the interplanetary medium and is a good starting point for understanding the physical mechanisms under these phenomena.

  2. A global examination of the response of ecosystem water-use efficiency to drought based on MODIS data.

    Science.gov (United States)

    Huang, Ling; He, Bin; Han, Le; Liu, Junjie; Wang, Haiyan; Chen, Ziyue

    2017-12-01

    Ecosystem water-use efficiency (WUE) plays an important role in carbon and water cycles. Currently, the response of WUE to drought disturbance remains controversial. Based on the global ecosystem gross primary productivity (GPP) product and the evapotranspiration product (ET), both of which were retrieved from the moderate resolution imaging spectroradiometer (MODIS), as well as the drought index, this study comprehensively examined the relationship between ecosystem WUE (WUE=GPP/ET) and drought at the global scale. The response of WUE to drought showed large differences in various regions and biomes. WUE for arid ecosystems typically showed a negative response to drought, whereas WUE for humid ecosystems showed both positive and negative response to drought. Legacy effects of drought on ecosystem WUE were observed. Furthermore, ecosystems showed a sensitive response to abrupt changes in hydrological climatic conditions. The transition from wet to dry years should increase ecosystem WUE, and the opposite change in WUE should occur when an ecosystem experiences a transition from dry to wet years. This indicates the resilience of ecosystems to drought disturbance. Knowledge from this study should provide an in-depth understanding of ecosystem strategies for coping with drought. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Validation and empirical correction of MODIS AOT and AE over ocean

    Directory of Open Access Journals (Sweden)

    N. A. J. Schutgens

    2013-09-01

    Full Text Available We present a validation study of Collection 5 MODIS level 2 Aqua and Terra AOT (aerosol optical thickness and AE (Ångström exponent over ocean by comparison to coastal and island AERONET (AErosol RObotic NETwork sites for the years 2003–2009. We show that MODIS (MODerate-resolution Imaging Spectroradiometer AOT exhibits significant biases due to wind speed and cloudiness of the observed scene, while MODIS AE, although overall unbiased, exhibits less spatial contrast on global scales than the AERONET observations. The same behaviour can be seen when MODIS AOT is compared against Maritime Aerosol Network (MAN data, suggesting that the spatial coverage of our datasets does not preclude global conclusions. Thus, we develop empirical correction formulae for MODIS AOT and AE that significantly improve agreement of MODIS and AERONET observations. We show these correction formulae to be robust. Finally, we study random errors in the corrected MODIS AOT and AE and show that they mainly depend on AOT itself, although small contributions are present due to wind speed and cloud fraction in AOT random errors and due to AE and cloud fraction in AE random errors. Our analysis yields significantly higher random AOT errors than the official MODIS error estimate (0.03 + 0.05 τ, while random AE errors are smaller than might be expected. This new dataset of bias-corrected MODIS AOT and AE over ocean is intended for aerosol model validation and assimilation studies, but also has consequences as a stand-alone observational product. For instance, the corrected dataset suggests that much less fine mode aerosol is transported across the Pacific and Atlantic oceans.

  4. MODIS Snow Cover Recovery Using Variational Interpolation

    Science.gov (United States)

    Tran, H.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Cloud obscuration is one of the major problems that limit the usages of satellite images in general and in NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) global Snow-Covered Area (SCA) products in particular. Among the approaches to resolve the problem, the Variational Interpolation (VI) algorithm method, proposed by Xia et al., 2012, obtains cloud-free dynamic SCA images from MODIS. This method is automatic and robust. However, computational deficiency is a main drawback that degrades applying the method for larger scales (i.e., spatial and temporal scales). To overcome this difficulty, this study introduces an improved version of the original VI. The modified VI algorithm integrates the MINimum RESidual (MINRES) iteration (Paige and Saunders., 1975) to prevent the system from breaking up when applied to much broader scales. An experiment was done to demonstrate the crash-proof ability of the new algorithm in comparison with the original VI method, an ability that is obtained when maintaining the distribution of the weights set after solving the linear system. After that, the new VI algorithm was applied to the whole Contiguous United States (CONUS) over four winter months of 2016 and 2017, and validated using the snow station network (SNOTEL). The resulting cloud free images have high accuracy in capturing the dynamical changes of snow in contrast with the MODIS snow cover maps. Lastly, the algorithm was applied to create a Cloud free images dataset from March 10, 2000 to February 28, 2017, which is able to provide an overview of snow trends over CONUS for nearly two decades. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institute for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

  5. Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

    Science.gov (United States)

    Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

    2015-01-01

    To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

  6. High-Resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems

    Energy Technology Data Exchange (ETDEWEB)

    Bogenschutz, Peter [National Center for Atmospheric Research, Boulder, CO (United States); Moeng, Chin-Hoh [National Center for Atmospheric Research, Boulder, CO (United States)

    2015-10-13

    The PI’s at the National Center for Atmospheric Research (NCAR), Chin-Hoh Moeng and Peter Bogenschutz, have primarily focused their time on the implementation of the Simplified-Higher Order Turbulence Closure (SHOC; Bogenschutz and Krueger 2013) to the Multi-scale Modeling Framework (MMF) global model and testing of SHOC on deep convective cloud regimes.

  7. Using satellites and global models to investigate aerosol-cloud interactions

    Science.gov (United States)

    Gryspeerdt, E.; Quaas, J.; Goren, T.; Sourdeval, O.; Mülmenstädt, J.

    2017-12-01

    Aerosols are known to impact liquid cloud properties, through both microphysical and radiative processes. Increasing the number concentration of aerosol particles can increase the cloud droplet number concentration (CDNC). Through impacts on precipitation processes, this increase in CDNC may also be able to impact the cloud fraction (CF) and the cloud liquid water path (LWP). Several studies have looked into the effect of aerosols on the CDNC, but as the albedo of a cloudy scene depends much more strongly on LWP and CF, an aerosol influence on these properties could generate a significant radiative forcing. While the impact of aerosols on cloud properties can be seen in case studies involving shiptracks and volcanoes, producing a global estimate of these effects remains challenging due to the confounding effect of local meteorology. For example, relative humidity significantly impacts the aerosol optical depth (AOD), a common satellite proxy for CCN, as well as being a strong control on cloud properties. This can generate relationships between AOD and cloud properties, even when there is no impact of aerosol-cloud interactions. In this work, we look at how aerosol-cloud interactions can be distinguished from the effect of local meteorology in satellite studies. With a combination global climate models and multiple sources of satellite data, we show that the choice of appropriate mediating variables and case studies can be used to develop constraints on the aerosol impact on CF and LWP. This will lead to improved representations of clouds in global climate models and help to reduce the uncertainty in the global impact of anthropogenic aerosols on cloud properties.

  8. CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM1-MODIS_Edition2C)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator)

    The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  9. CERES) Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM2-MODIS_Edition2C)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator)

    The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  10. Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia

    Science.gov (United States)

    Loboda, Tatiana V.; Giglio, Louis; Boschetti, Luigi; Justice, Christopher O.

    2012-06-01

    Central Asian dry lands are grass- and desert shrub-dominated ecosystems stretching across Northern Eurasia. This region supports a population of more than 100 million which continues to grow at an average rate of 1.5% annually. Dry steppes are the primary grain and cattle growing zone within Central Asia. Degradation of this ecosystem through burning and overgrazing directly impacts economic growth and food supply in the region. Fire is a recurrent disturbance agent in dry lands contributing to soil erosion and air pollution. Here we provide an overview of inter-annual and seasonal fire dynamics in Central Asia obtained from remotely sensed data. We evaluate the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) global fire products within Central Asian dry lands and use these products to characterize fire occurrence between 2001 and 2009. The results show that on average ˜15 million ha of land burns annually across Central Asia with the majority of the area burned in August and September in grasslands. Fire is used as a common crop residue management practice across the region. Nearly 89% of all burning occurs in Kazakhstan, where 5% and 3% of croplands and grasslands, respectively, are burned annually.

  11. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [Lawrence Livermore National Laboratory, Livermore, California; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Marchand, Roger [University of Washington, Seattle, Washington; Kollias, Pavlos [Stony Brook University, Stony Brook, New York; Clothiaux, Eugene E. [The Pennsylvania State University, University Park, Pennsylvania; Lin, Wuyin [Brookhaven National Laboratory, Upton, New York; Johnson, Karen [Brookhaven National Laboratory, Upton, New York; Swales, Dustin [CIRES and NOAA/Earth System Research Laboratory, Boulder, Colorado; Bodas-Salcedo, Alejandro [Met Office Hadley Centre, Exeter, United Kingdom; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California; Haynes, John M. [Cooperative Institute for Research in the Atmosphere/Colorado State University, Fort Collins, Colorado; Collis, Scott [Argonne National Laboratory, Argonne, Illinois; Jensen, Michael [Brookhaven National Laboratory, Upton, New York; Bharadwaj, Nitin [Pacific Northwest National Laboratory, Richland, Washington; Hardin, Joseph [Pacific Northwest National Laboratory, Richland, Washington; Isom, Bradley [Pacific Northwest National Laboratory, Richland, Washington

    2018-01-01

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are

  12. The role of aerosols in cloud drop parameterizations and its applications in global climate models

    Energy Technology Data Exchange (ETDEWEB)

    Chuang, C.C.; Penner, J.E. [Lawrence Livermore National Lab., CA (United States)

    1996-04-01

    The characteristics of the cloud drop size distribution near cloud base are initially determined by aerosols that serve as cloud condensation nuclei and the updraft velocity. We have developed parameterizations relating cloud drop number concentration to aerosol number and sulfate mass concentrations and used them in a coupled global aerosol/general circulation model (GCM) to estimate the indirect aerosol forcing. The global aerosol model made use of our detailed emissions inventories for the amount of particulate matter from biomass burning sources and from fossil fuel sources as well as emissions inventories of the gas-phase anthropogenic SO{sub 2}. This work is aimed at validating the coupled model with the Atmospheric Radiation Measurement (ARM) Program measurements and assessing the possible magnitude of the aerosol-induced cloud effects on climate.

  13. Aerosol activation and cloud processing in the global aerosol-climate model ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    G. J. Roelofs

    2006-01-01

    Full Text Available A parameterization for cloud processing is presented that calculates activation of aerosol particles to cloud drops, cloud drop size, and pH-dependent aqueous phase sulfur chemistry. The parameterization is implemented in the global aerosol-climate model ECHAM5-HAM. The cloud processing parameterization uses updraft speed, temperature, and aerosol size and chemical parameters simulated by ECHAM5-HAM to estimate the maximum supersaturation at the cloud base, and subsequently the cloud drop number concentration (CDNC due to activation. In-cloud sulfate production occurs through oxidation of dissolved SO2 by ozone and hydrogen peroxide. The model simulates realistic distributions for annually averaged CDNC although it is underestimated especially in remote marine regions. On average, CDNC is dominated by cloud droplets growing on particles from the accumulation mode, with smaller contributions from the Aitken and coarse modes. The simulations indicate that in-cloud sulfate production is a potentially important source of accumulation mode sized cloud condensation nuclei, due to chemical growth of activated Aitken particles and to enhanced coalescence of processed particles. The strength of this source depends on the distribution of produced sulfate over the activated modes. This distribution is affected by uncertainties in many parameters that play a direct role in particle activation, such as the updraft velocity, the aerosol chemical composition and the organic solubility, and the simulated CDNC is found to be relatively sensitive to these uncertainties.

  14. MODIS/Aqua Near Real Time (NRT) Surface Reflectance Daily L2G Global 250m SIN Grid

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Near Real Time (NRT) Surface Reflectance products are an estimate of the surface spectral reflectance as it would be measured at ground level in the...

  15. MODIS/Terra+Aqua BRDF/Albedo Model Parameters 16-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODerate-resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters product (MCD43B1) contains three-dimensional (3D) data sets providing users...

  16. Combined ASTER and MODIS Emissivity database over Land (CAMEL) Emissivity Monthly Global 0.05Deg V001

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined ASTER and MODIS Emissivity database over Land (CAMEL) dataset provides...

  17. MODIS/Terra Gross Primary Productivity 8-Day L4 Global 1km SIN Grid V055

    Data.gov (United States)

    National Aeronautics and Space Administration — The Terra/MODIS Gross Primary Productivity (GPP) product (MOD17A2) is a cumulative composite of GPP values based on the radiation-use efficiency concept that is...

  18. MODIS/Aqua Land Surface Temperature/Emissivity 8-Day L3 Global 0.05Deg CMG V041

    Data.gov (United States)

    National Aeronautics and Space Administration — The MYD11C2.041 dataset was decommissioned as of March 1, 2018. Users are encouraged to use Version 6 of MODIS/Aqua Land Surface Temperature and Emissivity Daily L3...

  19. Combined ASTER and MODIS Emissivity database over Land (CAMEL) Coefficient Monthly Global 0.05Deg V001

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Combined ASTER and MODIS Emissivity database over Land (CAMEL) dataset provides...

  20. Construction of a Matched Global Cloud and Radiance Product from LEO/GEO and EPIC Observations to Estimate Daytime Earth Radiation Budget from DSCOVR

    Science.gov (United States)

    Duda, D. P.; Khlopenkov, K. V.; Palikonda, R.; Khaiyer, M. M.; Minnis, P.; Su, W.; Sun-Mack, S.

    2016-12-01

    With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and

  1. Construction of a Matched Global Cloud and Radiance Product from LEO/GEO and EPIC Observations to Estimate Daytime Earth Radiation Budget from DSCOVR

    Science.gov (United States)

    Duda, David P.; Khlopenkov, Konstantin V.; Thiemann, Mandana; Palikonda, Rabindra; Sun-Mack, Sunny; Minnis, Patrick; Su, Wenying

    2016-01-01

    With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can be computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and

  2. The global atmospheric electric circuit and its effects on cloud microphysics

    International Nuclear Information System (INIS)

    Tinsley, B A

    2008-01-01

    This review is an overview of progress in understanding the theory and observation of the global atmospheric electric circuit, with the focus on its dc aspects, and its short and long term variability. The effects of the downward ionosphere-earth current density, J z , on cloud microphysics, with its variability as an explanation for small observed changes in weather and climate, will also be reviewed. The global circuit shows responses to external as well as internal forcing. External forcing arises from changes in the distribution of conductivity due to changes in the cosmic ray flux and other energetic space particle fluxes, and at high magnetic latitudes from solar wind electric fields. Internal forcing arises from changes in the generators and changes in volcanic and anthropogenic aerosols in the troposphere and stratosphere. All these result in spatial and temporal variation in J z . Variations in J z affect the production of space charge in layer clouds, with the charges being transferred to droplets and aerosol particles. New observations and new analyses are consistent with non-negligible effects of the charges on the microphysics of such clouds. Observed effects are small, but of high statistical significance for cloud cover and precipitation changes, with resulting atmospheric temperature, pressure and dynamics changes. These effects are detectable on the day-to-day timescale for repeated J z changes of order 10%, and are thus second order electrical effects. The implicit first order effects have not, as yet, been incorporated into basic cloud and aerosol physics. Long term (multidecadal through millennial) global circuit changes, due to solar activity modulating the galactic cosmic ray flux, are an order of magnitude greater at high latitudes and in the stratosphere, as can be inferred from geological cosmogenic isotope records. Proxies for climate change in the same stratified depositories show strong correlations of climate with the inferred global

  3. The global atmospheric electric circuit and its effects on cloud microphysics

    Energy Technology Data Exchange (ETDEWEB)

    Tinsley, B A [Physics Department and Center for Space Sciences, WT15, University of Texas at Dallas, 800 W Campbell Road, Richardson, TX, 75080-3021 (United States)], E-mail: Tinsley@UTDallas.edu

    2008-06-15

    This review is an overview of progress in understanding the theory and observation of the global atmospheric electric circuit, with the focus on its dc aspects, and its short and long term variability. The effects of the downward ionosphere-earth current density, J{sub z}, on cloud microphysics, with its variability as an explanation for small observed changes in weather and climate, will also be reviewed. The global circuit shows responses to external as well as internal forcing. External forcing arises from changes in the distribution of conductivity due to changes in the cosmic ray flux and other energetic space particle fluxes, and at high magnetic latitudes from solar wind electric fields. Internal forcing arises from changes in the generators and changes in volcanic and anthropogenic aerosols in the troposphere and stratosphere. All these result in spatial and temporal variation in J{sub z}. Variations in J{sub z} affect the production of space charge in layer clouds, with the charges being transferred to droplets and aerosol particles. New observations and new analyses are consistent with non-negligible effects of the charges on the microphysics of such clouds. Observed effects are small, but of high statistical significance for cloud cover and precipitation changes, with resulting atmospheric temperature, pressure and dynamics changes. These effects are detectable on the day-to-day timescale for repeated J{sub z} changes of order 10%, and are thus second order electrical effects. The implicit first order effects have not, as yet, been incorporated into basic cloud and aerosol physics. Long term (multidecadal through millennial) global circuit changes, due to solar activity modulating the galactic cosmic ray flux, are an order of magnitude greater at high latitudes and in the stratosphere, as can be inferred from geological cosmogenic isotope records. Proxies for climate change in the same stratified depositories show strong correlations of climate with the

  4. Brightening of the global cloud field by nitric acid and the associated radiative forcing

    Directory of Open Access Journals (Sweden)

    R. Makkonen

    2012-08-01

    Full Text Available Clouds cool Earth's climate by reflecting 20% of the incoming solar energy, while also trapping part of the outgoing radiation. The effect of human activities on clouds is poorly understood, but the present-day anthropogenic cooling via changes of cloud albedo and lifetime could be of the same order as warming from anthropogenic addition in CO2. Soluble trace gases can increase water condensation to particles, possibly leading to activation of smaller aerosols and more numerous cloud droplets. We have studied the effect of nitric acid on the aerosol indirect effect with the global aerosol-climate model ECHAM5.5-HAM2. Including the nitric acid effect in the model increases cloud droplet number concentrations globally by 7%. The nitric acid contribution to the present-day cloud albedo effect was found to be −0.32 W m−2 and to the total indirect effect −0.46 W m−2. The contribution to the cloud albedo effect is shown to increase to −0.37 W m−2 by the year 2100, if considering only the reductions in available cloud condensation nuclei. Overall, the effect of nitric acid can play a large part in aerosol cooling during the following decades with decreasing SO2 emissions and increasing NOx and greenhouse gases.

  5. Global Validation of MODIS C6 and C6.1 Merged Aerosol Products over Diverse Vegetated Surfaces

    Directory of Open Access Journals (Sweden)

    Muhammad Bilal

    2018-03-01

    Full Text Available In this study, the MODerate resolution Imaging Spectroradiometer (MODIS Collections 6 and 6.1 merged Dark Target (DT and Deep Blue (DB aerosol products (DTBC6 and DTBC6.1 at 0.55 µm were validated from 2004–2014 against Aerosol Robotic Network (AERONET Version 2 Level 2.0 AOD obtained from 68 global sites located over diverse vegetated surfaces. These surfaces were categorized by static values of monthly Normalized Difference Vegetation Index (NDVI observations obtained for the same time period from the MODIS level-3 monthly NDVI product (MOD13A3, i.e., partially/non–vegetated (NDVIP ≤ 0.3, moderately–vegetated (0.3 < NDVIM ≤ 0.5 and densely–vegetated (NDVID > 0.5 surfaces. The DTBC6 and DTBC6.1 AOD products are accomplished by the NDVI criteria: (i use the DT AOD retrievals for NDVI > 0.3, (ii use the DB AOD retrievals for NDVI < 0.2, and (iii use an average of the DT and DB AOD retrievals or the available one with highest quality assurance flag (DT: QAF = 3; DB: QAF ≥ 2 for 0.2 ≤ NDVI ≤ 0.3. For comparison purpose, the DTBSMS AOD retrievals were included which were accomplished using the Simplified Merge Scheme, i.e., use an average of the DTC6.1 and DBC6.1 AOD retrievals or the available one for all the NDVI values. For NDVIP surfaces, results showed that the DTBC6 and DTBC6.1 AOD retrievals performed poorly over North and South America in terms of the agreement with AERONET AOD, and over Asian region in terms of retrievals quality as the small percentage of AOD retrievals were within the expected error (EE = ± (0.05 + 0.15 × AOD. For NDVIM surfaces, retrieval errors and poor quality in DTBC6 and DTBC6.1 were observed for Asian, North American and South American sites, whereas good performance, was observed for European and African sites. For NDVID surfaces, DTBC6 does not perform well over the Asian and North American sites, although it contains retrievals only from the DT algorithm which was developed for dark surfaces

  6. Using latency as a QoS indicator for global cloud computing services

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Riaz, Tahir; Dubalski, Bozydar

    2013-01-01

    Many globally distributed cloud computing (CC) applications and services running over the Internet, between globally dispersed clients and servers, will require certain levels of QoS in order to deliver and give a sufficiently smooth user experience. This would be essential for real-time streaming...

  7. Assessing Measurements of QoS for global Cloud Computing Services

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Riaz, M. Tahir; Júnior, Joaquim Celestino

    2011-01-01

    Many global distributed cloud computing applications and services running over the Internet, between globally dispersed clients and servers, will require certain levels of Quality of Service (QoS) in order to deliver and give a sufficiently smooth user experience. This would be essential for real......-time streaming multimedia applications like online gaming and watching movies on a pay as you use basis hosted in a cloud computing environment. However, guaranteeing or even predicting QoS in global and diverse networks supporting complex hosting of application services is a very challenging issue that needs...... a stepwise refinement approach to be solved as the technology of cloud computing matures. In this paper, we investigate if latency in terms of simple Ping measurements can be used as an indicator for other QoS parameters such as jitter and throughput. The experiments were carried out on a global scale...

  8. Influence which masses of clouds have on the global solar radiation at Salamanca (Spain)

    International Nuclear Information System (INIS)

    Pablo-Davila, F. de; Labajo, J.L.; Tomas-Sanchez, C.

    1991-01-01

    It has been shown the influence which masses of clouds, (and more specifically for each group of cloud types: high, middle and low clauds), has on the global solar radiation recorded at Matacan (Salamanca), within the period 1977-1985. For this purpose, cloud observation were made every three hours; daily records of sunshine and solar radiation were continually taken too. It has also been, both graphically and numerically, the influence of each cloud type for monthly and seasonal periods. Futhermore, different statistical parameters have been presented in order to describe the method developed. Finally, the results have been analysed and evaluated. They have been explaines according to the composition, structure and radiative properties of clouds.(Author)

  9. Albedo enhancement of marine clouds to counteract global warming: impacts on the hydrological cycle

    Energy Technology Data Exchange (ETDEWEB)

    Bala, G. [Indian Institute of Science, Divecha Center for Climate Change, Bangalore (India); Indian Institute of Science, Center for Atmospheric and Oceanic Sciences, Bangalore (India); Caldeira, Ken; Cao, Long; Ban-Weiss, George; Shin, Ho-Jeong [Carnegie Institution, Department of Global Ecology, Stanford, CA (United States); Nemani, Rama [NASA Ames Research Center, Moffett Field, CA (United States)

    2011-09-15

    Recent studies have shown that changes in solar radiation affect the hydrological cycle more strongly than equivalent CO{sub 2} changes for the same change in global mean surface temperature. Thus, solar radiation management ''geoengineering'' proposals to completely offset global mean temperature increases by reducing the amount of absorbed sunlight might be expected to slow the global water cycle and reduce runoff over land. However, proposed countering of global warming by increasing the albedo of marine clouds would reduce surface solar radiation only over the oceans. Here, for an idealized scenario, we analyze the response of temperature and the hydrological cycle to increased reflection by clouds over the ocean using an atmospheric general circulation model coupled to a mixed layer ocean model. When cloud droplets are reduced in size over all oceans uniformly to offset the temperature increase from a doubling of atmospheric CO{sub 2}, the global-mean precipitation and evaporation decreases by about 1.3% but runoff over land increases by 7.5% primarily due to increases over tropical land. In the model, more reflective marine clouds cool the atmospheric column over ocean. The result is a sinking motion over oceans and upward motion over land. We attribute the increased runoff over land to this increased upward motion over land when marine clouds are made more reflective. Our results suggest that, in contrast to other proposals to increase planetary albedo, offsetting mean global warming by reducing marine cloud droplet size does not necessarily lead to a drying, on average, of the continents. However, we note that the changes in precipitation, evaporation and P-E are dominated by small but significant areas, and given the highly idealized nature of this study, a more thorough and broader assessment would be required for proposals of altering marine cloud properties on a large scale. (orig.)

  10. CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM1-MODIS_Edition2B)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  11. CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2A)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  12. CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition2A)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  13. CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2C)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

  14. Global vertical mass transport by clouds - A two-dimensional model study

    International Nuclear Information System (INIS)

    Olofsson, Mats

    1988-05-01

    A two-dimensional global dispersion model, where vertical transport in the troposphere carried out by convective as well as by frontal cloud systems is explicitly treated, is developed from an existing diffusion model. A parameterization scheme for the cloud transport, based on global cloud statistics, is presented. The model has been tested by using Kr-85, Rn-222 and SO 2 as tracers. Comparisons have been made with observed distributions of these tracers, but also with model results without the cloud transport, using eddy diffusion as the primary means of vertical transport. The model results indicate that for trace species with a turnover time of days to weeks, the introduction of cloud-transport gives much more realistic simulations of their vertical distribution. Layers of increased mixing ratio with height, which can be found in real atmosphere, are reproduced in our cloud-transport model profiles, but can never be simulated with a pure eddy diffusion model. The horizontal transport in the model, by advection and eddy diffusion, gives a realistic distribution between the hemispheres of the more long-lived tracers (Kr-85). A combination of vertical transport by convective and frontal cloud systems is shown to improve the model simulations, compared to limiting it to convective transport only. The importance of including cumulus clouds in the convective transport scheme, in addition to the efficient transport by cumulonimbus clouds, is discussed. The model results are shown to be more sensitive to the vertical detrainment distribution profile than to the absolute magnitude of the vertical mass transport. The scavenging processes for SO 2 are parameterized without the introduction of detailed chemistry. An enhanced removal, due to the increased contact with droplets in the in-cloud lifting process, is introduced in the model. (author)

  15. From One Pixel to One Earth: Building a Living Atlas in the Cloud to Analyze and Monitor Global Patterns

    Science.gov (United States)

    Moody, D.; Brumby, S. P.; Chartrand, R.; Franco, E.; Keisler, R.; Kelton, T.; Kontgis, C.; Mathis, M.; Raleigh, D.; Rudelis, X.; Skillman, S.; Warren, M. S.; Longbotham, N.

    2016-12-01

    The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Historical, multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes per year of high-resolution imagery with daily global coverage. Cloud computing and storage, combined with recent advances in machine learning and open software, are enabling understanding of the world at an unprecedented scale and detail. We have assembled all available satellite imagery from the USGS Landsat, NASA MODIS, and ESA Sentinel programs, as well as commercial PlanetScope and RapidEye imagery, and have analyzed over 2.8 quadrillion multispectral pixels. We leveraged the commercial cloud to generate a tiled, spatio-temporal mosaic of the Earth for fast iteration and development of new algorithms combining analysis techniques from remote sensing, machine learning, and scalable compute infrastructure. Our data platform enables processing at petabytes per day rates using multi-source data to produce calibrated, georeferenced imagery stacks at desired points in time and space that can be used for pixel level or global scale analysis. We demonstrate our data platform capability by using the European Space Agency's (ESA) published 2006 and 2009 GlobCover 20+ category label maps to train and test a Land Cover Land Use (LCLU) classifier, and generate current self-consistent LCLU maps in Brazil. We train a standard classifier on 2006 GlobCover categories using temporal imagery stacks, and we validate our results on co-registered 2009 Globcover LCLU maps and 2009 imagery. We then extend the derived LCLU model to current imagery stacks to generate an updated, in-season label map. Changes in LCLU labels can now be seamlessly monitored for a given location across the years in order to track, for example, cropland expansion, forest growth, and urban developments. An example of change

  16. Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

    Science.gov (United States)

    Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

    2016-12-01

    Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general

  17. ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [North Carolina State Univ., Raleigh, NC (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-05-01

    It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model output and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP

  18. Seven years of global retrieval of cloud properties using space-borne data of GOME

    Directory of Open Access Journals (Sweden)

    L. Lelli

    2012-07-01

    Full Text Available We present a global and regional multi-annual (June 1996–May 2003 analysis of cloud properties (spherical cloud albedo – CA, cloud optical thickness – COT and cloud top height – CTH of optically thick (COT > 5 clouds, derived using measurements from the GOME instrument on board the ESA ERS-2 space platform. We focus on cloud top height, which is obtained from top-of-atmosphere backscattered solar light measurements in the O2 A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer. The dataset has been validated against independent ground- and satellite-based retrievals and is aimed to support trace-gases retrievals as well as to create a robust long-term climatology together with SCIAMACHY and GOME-2 ensuing retrievals. We observed the El Niño-Southern Oscillation anomaly in the 1997–1998 record through CTH values over the Pacific Ocean. The global average CTH as derived from GOME is 5.6 ± 3.2 km, for a corresponding average COT of 19.1 ± 13.9.

  19. Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

    Science.gov (United States)

    Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

    2004-01-01

    The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

  20. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

    Science.gov (United States)

    Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

  1. Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

    Science.gov (United States)

    Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

    2016-01-01

    Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

  2. MISR Aerosol Product Attributes and Statistical Comparisons with MODIS

    Science.gov (United States)

    Kahn, Ralph A.; Nelson, David L.; Garay, Michael J.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Paradise, Susan R.; Hansen, Earl G.; Remer, Lorraine A.

    2009-01-01

    In this paper, Multi-angle Imaging SpectroRadiometer (MISR) aerosol product attributes are described, including geometry and algorithm performance flags. Actual retrieval coverage is mapped and explained in detail using representative global monthly data. Statistical comparisons are made with coincident aerosol optical depth (AOD) and Angstrom exponent (ANG) retrieval results from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The relationship between these results and the ones previously obtained for MISR and MODIS individually, based on comparisons with coincident ground-truth observations, is established. For the data examined, MISR and MODIS each obtain successful aerosol retrievals about 15% of the time, and coincident MISR-MODIS aerosol retrievals are obtained for about 6%-7% of the total overlap region. Cloud avoidance, glint and oblique-Sun exclusions, and other algorithm physical limitations account for these results. For both MISR and MODIS, successful retrievals are obtained for over 75% of locations where attempts are made. Where coincident AOD retrievals are obtained over ocean, the MISR-MODIS correlation coefficient is about 0.9; over land, the correlation coefficient is about 0.7. Differences are traced to specific known algorithm issues or conditions. Over-ocean ANG comparisons yield a correlation of 0.67, showing consistency in distinguishing aerosol air masses dominated by coarse-mode versus fine-mode particles. Sampling considerations imply that care must be taken when assessing monthly global aerosol direct radiative forcing and AOD trends with these products, but they can be used directly for many other applications, such as regional AOD gradient and aerosol air mass type mapping and aerosol transport model validation. Users are urged to take seriously the published product data-quality statements.

  3. THE GLOBAL EVOLUTION OF GIANT MOLECULAR CLOUDS. II. THE ROLE OF ACCRETION

    International Nuclear Information System (INIS)

    Goldbaum, Nathan J.; Krumholz, Mark R.; Matzner, Christopher D.; McKee, Christopher F.

    2011-01-01

    We present virial models for the global evolution of giant molecular clouds (GMCs). Focusing on the presence of an accretion flow and accounting for the amount of mass, momentum, and energy supplied by accretion and star formation feedback, we are able to follow the growth, evolution, and dispersal of individual GMCs. Our model clouds reproduce the scaling relations observed in both galactic and extragalactic clouds. We find that accretion and star formation contribute roughly equal amounts of turbulent kinetic energy over the lifetime of the cloud. Clouds attain virial equilibrium and grow in such a way as to maintain roughly constant surface densities, with typical surface densities of order 50-200 M sun pc -2 , in good agreement with observations of GMCs in the Milky Way and nearby external galaxies. We find that as clouds grow, their velocity dispersion and radius must also increase, implying that the linewidth-size relation constitutes an age sequence. Lastly, we compare our models to observations of GMCs and associated young star clusters in the Large Magellanic Cloud and find good agreement between our model clouds and the observed relationship between H II regions, young star clusters, and GMCs.

  4. The role of clouds and oceans in global greenhouse warming. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Hoffert, M.I.

    1996-10-01

    This research focuses on assessing connections between anthropogenic greenhouse gas emissions and global climatic change. it has been supported since the early 1990s in part by the DOE ``Quantitative Links`` Program (QLP). A three-year effort was originally proposed to the QLP to investigate effects f global cloudiness on global climate and its implications for cloud feedback; and to continue the development and application of climate/ocean models, with emphasis on coupled effects of greenhouse warming and feedbacks by clouds and oceans. It is well-known that cloud and ocean processes are major sources of uncertainty in the ability to predict climatic change from humankind`s greenhouse gas and aerosol emissions. And it has always been the objective to develop timely and useful analytical tools for addressing real world policy issues stemming from anthropogenic climate change.

  5. Surface spectral emissivity derived from MODIS data

    Science.gov (United States)

    Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

    2003-04-01

    Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

  6. The potential negative impacts of global climate change on tropical montane cloud forests

    Science.gov (United States)

    Foster, Pru

    2001-10-01

    Nearly every aspect of the cloud forest is affected by regular cloud immersion, from the hydrological cycle to the species of plants and animals within the forest. Since the altitude band of cloud formation on tropical mountains is limited, the tropical montane cloud forest occurs in fragmented strips and has been likened to island archipelagoes. This isolation and uniqueness promotes explosive speciation, exceptionally high endemism, and a great sensitivity to climate. Global climate change threatens all ecosystems through temperature and rainfall changes, with a typical estimate for altitude shifts in the climatic optimum for mountain ecotones of hundreds of meters by the time of CO 2 doubling. This alone suggests complete replacement of many of the narrow altitude range cloud forests by lower altitude ecosystems, as well as the expulsion of peak residing cloud forests into extinction. However, the cloud forest will also be affected by other climate changes, in particular changes in cloud formation. A number of global climate models suggest a reduction in low level cloudiness with the coming climate changes, and one site in particular, Monteverde, Costa Rica, appears to already be experiencing a reduction in cloud immersion. The coming climate changes appear very likely to upset the current dynamic equilibrium of the cloud forest. Results will include biodiversity loss, altitude shifts in species' ranges and subsequent community reshuffling, and possibly forest death. Difficulties for cloud forest species to survive in climate-induced migrations include no remaining location with a suitable climate, no pristine location to colonize, migration rates or establishment rates that cannot keep up with climate change rates and new species interactions. We review previous cloud forest species redistributions in the paleo-record in light of the coming changes. The characteristic epiphytes of the cloud forest play an important role in the light, hydrological and nutrient

  7. Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

    Science.gov (United States)

    Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; hide

    2014-01-01

    The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra- Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on

  8. Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

    Directory of Open Access Journals (Sweden)

    Wei Li

    2015-01-01

    Full Text Available We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

  9. Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

    Science.gov (United States)

    Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

    2018-02-01

    The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

  10. Effect of retreating sea ice on Arctic cloud cover in simulated recent global warming

    Directory of Open Access Journals (Sweden)

    M. Abe

    2016-11-01

    Full Text Available This study investigates the effect of sea ice reduction on Arctic cloud cover in historical simulations with the coupled atmosphere–ocean general circulation model MIROC5. Arctic sea ice has been substantially retreating since the 1980s, particularly in September, under simulated global warming conditions. The simulated sea ice reduction is consistent with satellite observations. On the other hand, Arctic cloud cover has been increasing in October, with about a 1-month lag behind the sea ice reduction. The delayed response leads to extensive sea ice reductions because the heat and moisture fluxes from the underlying open ocean into the atmosphere are enhanced. Sensitivity experiments with the atmospheric part of MIROC5 clearly show that sea ice reduction causes increases in cloud cover. Arctic cloud cover increases primarily in the lower troposphere, but it decreases in the near-surface layers just above the ocean; predominant temperature rises in these near-surface layers cause drying (i.e., decreases in relative humidity, despite increasing moisture flux. Cloud radiative forcing due to increases in cloud cover in autumn brings an increase in the surface downward longwave radiation (DLR by approximately 40–60 % compared to changes in clear-sky surface DLR in fall. These results suggest that an increase in Arctic cloud cover as a result of reduced sea ice coverage may bring further sea ice retreat and enhance the feedback processes of Arctic warming.

  11. Processing of Cloud Databases for the Development of an Automated Global Cloud Climatology

    Science.gov (United States)

    1991-06-30

    cloud amounts in each DOE grid box. The actual population values were coded into one- and two- digit codes primarily for printing purposes. For example...IPIALES 72652 43.07 -95.53 0423 PICKSTOWNE S.D. 80110 6.22 -75.60 1498 MEDELLIN 72424 37.90 -85.97 0233 FT. KNOX KY 80069 7.00 -74.72 0610 AMALFI...12 According to Lund, Grantham, and Davis (1980), the quality of the whole sky photographs used in producing the WSP digital data ensemble was

  12. Mossin, Mody

    DEFF Research Database (Denmark)

    2005-01-01

    Katalog til udstillingen på KA d. 12. - 30. oktober 2005. Kataloget til udstillingen Mossin: Mody, til udstillingens fotografier og til det arkitektoniske udviklingsarbejde, som fotografierne dokumenterer igennem deres formidling af et særligt og kritisk syn på by og bygning.......Katalog til udstillingen på KA d. 12. - 30. oktober 2005. Kataloget til udstillingen Mossin: Mody, til udstillingens fotografier og til det arkitektoniske udviklingsarbejde, som fotografierne dokumenterer igennem deres formidling af et særligt og kritisk syn på by og bygning....

  13. A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

    Science.gov (United States)

    Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

    2007-12-14

    A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

  14. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2017-06-01

    Full Text Available We present a new approach to retrieve Aerosol Optical Depth (AOD using the Moderate Resolution Imaging Spectroradiometer (MODIS over the turbid coastal water. This approach supplements the operational Dark Target (DT aerosol retrieval algorithm that currently does not conduct AOD retrieval in shallow waters that have visible sediments or sea-floor (i.e., Class 2 waters. Over the global coastal water regions in cloud-free conditions, coastal screening leads to ~20% unavailability of AOD retrievals. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 μm to be negligible regardless of water turbidity, and therefore the 2.1 μm reflectance at the top of the atmosphere is sensitive to both change of fine-mode and coarse-mode AODs. By assuming that the aerosol single scattering properties over coastal turbid water are similar to those over the adjacent open-ocean pixels, the new algorithm can derive AOD over these shallow waters. The test algorithm yields ~18% more MODIS-AERONET collocated pairs for six AERONET stations in the coastal water regions. Furthermore, comparison of the new retrieval with these AERONET observations show that the new AOD retrievals have equivalent or better accuracy than those retrieved by the MODIS operational algorithm’s over coastal land and non-turbid coastal water product. Combining the new retrievals with the existing MODIS operational retrievals yields an overall improvement of AOD over those coastal water regions. Most importantly, this refinement extends the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides. This expanded coverage is crucial for better understanding of impact of anthropogenic aerosol particles on coastal air quality and climate.

  15. Interactions Between Atmospheric Aerosols and Marine Boundary Layer Clouds on Regional and Global Scales

    Science.gov (United States)

    Wang, Zhen

    Airborne aerosols are crucial atmospheric constituents that are involved in global climate change and human life qualities. Understanding the nature and magnitude of aerosol-cloud-precipitation interactions is critical in model predictions for atmospheric radiation budget and the water cycle. The interactions depend on a variety of factors including aerosol physicochemical complexity, cloud types, meteorological and thermodynamic regimes and data processing techniques. This PhD work is an effort to quantify the relationships among aerosol, clouds, and precipitation on both global and regional scales by using satellite retrievals and aircraft measurements. The first study examines spatial distributions of conversion rate of cloud water to rainwater in warm maritime clouds over the globe by using NASA A-Train satellite data. This study compares the time scale of the onset of precipitation with different aerosol categories defined by values of aerosol optical depth, fine mode fraction, and Angstrom Exponent. The results indicate that conversion time scales are actually quite sensitive to lower tropospheric static stability (LTSS) and cloud liquid water path (LWP), in addition to aerosol type. Analysis shows that tropical Pacific Ocean is dominated by the highest average conversion rate while subtropical warm cloud regions (far northeastern Pacific Ocean, far southeastern Pacific Ocean, Western Africa coastal area) exhibit the opposite result. Conversion times are mostly shorter for lower LTSS regimes. When LTSS condition is fixed, higher conversion rates coincide with higher LWP and lower aerosol index categories. After a general global view of physical property quantifications, the rest of the presented PhD studies is focused on regional airborne observations, especially bulk cloud water chemistry and aerosol aqueous-phase reactions during the summertime off the California coast. Local air mass origins are categorized into three distinct types (ocean, ships, and land

  16. Snow Cover Monitoring Using MODIS Data in Liaoning Province, Northeastern China

    Directory of Open Access Journals (Sweden)

    Yu Lu

    2010-03-01

    Full Text Available This paper presents the results of snow cover monitoring studies in Liaoning Province, northeastern China, using MODIS data. Snow cover plays an important role in both the regional water balance and soil moisture properties during the early spring in northeastern China. In addition, heavy snowfalls commonly trigger hazards such as flooding, caused by rapid snow melt, or crop failure, resulting from fluctuations in soil temperature associated with changes in the snow cover. The latter is a function of both regional, or global, climatic changes, as well as fluctuations in the albedo resulting from variations in the Snow Covered Area (SCA. These impacts are crucial to human activities, especially to those living in middle-latitude areas such as Liaoning Province. Thus, SCA monitoring is currently an important tool in studies of global climate change, particularly because satellite remote sensing data provide timely and efficient snow cover information for large areas. In this study, MODIS L1B data, MODIS Daily Snow Products (MOD10A1 and MODIS 8-day Snow Products (MOD10A2 were used to monitor the SCA of Liaoning Province over the winter months of November–April, 2006–2008. The effects of cloud masking and forest masking on the snow monitoring results were also assessed. The results show that the SCA percentage derived from MODIS L1B data is relatively consistent, but slightly higher than that obtained from MODIS Snow Products. In situ data from 25 snow stations were used to assess the accuracy of snow cover monitoring from the SCA compared to the results from MODIS Snow Products. The studies found that the SCA results were more reliable than MODIS Snow Products in the study area.

  17. Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

    Science.gov (United States)

    Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

    2005-04-01

    The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol

  18. In-cloud oxalate formation in the global troposphere: a 3-D modeling study

    Directory of Open Access Journals (Sweden)

    S. Myriokefalitakis

    2011-06-01

    Full Text Available Organic acids attract increasing attention as contributors to atmospheric acidity, secondary organic aerosol mass and aerosol hygroscopicity. Oxalic acid is globally the most abundant dicarboxylic acid, formed via chemical oxidation of gas-phase precursors in the aqueous phase of aerosols and droplets. Its lifecycle and atmospheric global distribution remain highly uncertain and are the focus of this study. The first global spatial and temporal distribution of oxalate, simulated using a state-of-the-art aqueous-phase chemical scheme embedded within the global 3-dimensional chemistry/transport model TM4-ECPL, is here presented. The model accounts for comprehensive gas-phase chemistry and its coupling with major aerosol constituents (including secondary organic aerosol. Model results are consistent with ambient observations of oxalate at rural and remote locations (slope = 1.16 ± 0.14, r2 = 0.36, N = 114 and suggest that aqueous-phase chemistry contributes significantly to the global atmospheric burden of secondary organic aerosol. In TM4-ECPL most oxalate is formed in-cloud and less than 5 % is produced in aerosol water. About 62 % of the oxalate is removed via wet deposition, 30 % by in-cloud reaction with hydroxyl radical, 4 % by in-cloud reaction with nitrate radical and 4 % by dry deposition. The in-cloud global oxalate net chemical production is calculated to be about 21–37 Tg yr−1 with almost 79 % originating from biogenic hydrocarbons, mainly isoprene. This condensed phase net source of oxalate in conjunction with a global mean turnover time against deposition of about 5 days, maintain oxalate's global tropospheric burden of 0.2–0.3 Tg, i.e. 0.05–0.1 Tg-C that is about 5–9 % of model-calculated water soluble organic carbon burden.

  19. Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

    Science.gov (United States)

    Cahalan, R. F.; Morcrette, J. J.

    1999-01-01

    Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better

  20. An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

    Science.gov (United States)

    Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

    2018-03-01

    Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

  1. Cloud motions on Venus - Global structure and organization

    Science.gov (United States)

    Limaye, S. S.; Suomi, V. E.

    1981-01-01

    Results on cloud motions on Venus obtained over a period of 3.5 days from Mariner 10 television images are presented. The implied atmosphere flow is almost zonal everywhere on the visible disk, and is in the same retrograde sense as the solid planet. Objective analysis of motions suggests the presence of jet cores (-130 m/s) and organized atmospheric waves. The longitudinal mean meridional profile of the zonal component of motion of the ultraviolet features shows presence of a midlatitude jet stream (-110 m/s). The mean zonal component is -97 m/s at the equator. The mean meridional motion at most latitudes is directed toward the pole in either hemisphere and is at least an order of magnitude smaller so that the flow is nearly zonal. A tentative conclusion from the limited coverage available from Mariner 10 is that at the level of ultraviolet features mean meridional circulation is the dominant mode of poleward angular momentum transfer as opposed to the eddy circulation.

  2. A Global Survey of Cloud Thermodynamic Phase using High Spatial Resolution VSWIR Spectroscopy, 2005-2015

    Science.gov (United States)

    Thompson, D. R.; Kahn, B. H.; Green, R. O.; Chien, S.; Middleton, E.; Tran, D. Q.

    2017-12-01

    Clouds' variable ice and liquid content significantly influences their optical properties, evolution, and radiative forcing potential (Tan and Storelvmo, J. Atmos. Sci, 73, 2016). However, most remote measurements of thermodynamic phase have spatial resolutions of 1 km or more and are insensitive to mixed phases. This under-constrains important processes, such as spatial partitioning within mixed phase clouds, that carry outsize radiative forcing impacts. These uncertainties could shift Global Climate Model (GCM) predictions of future warming by over 1 degree Celsius (Tan et al., Science 352:6282, 2016). Imaging spectroscopy of reflected solar energy from the 1.4 - 1.8 μm shortwave infrared (SWIR) spectral range can address this observational gap. These observations can distinguish ice and water absorption, providing a robust and sensitive measurement of cloud top thermodynamic phase including mixed phases. Imaging spectrometers can resolve variations at scales of tens to hundreds of meters (Thompson et al., JGR-Atmospheres 121, 2016). We report the first such global high spatial resolution (30 m) survey, based on data from 2005-2015 acquired by the Hyperion imaging spectrometer onboard NASA's EO-1 spacecraft (Pearlman et al., Proc. SPIE 4135, 2001). Estimated seasonal and latitudinal distributions of cloud thermodynamic phase generally agree with observations made by other satellites such as the Atmospheric Infrared Sounder (AIRS). Variogram analyses reveal variability at different spatial scales. Our results corroborate previously observed zonal distributions, while adding insight into the spatial scales of processes governing cloud top thermodynamic phase. Figure: Thermodynamic phase retrievals. Top: Example of a cloud top thermodynamic phase map from the EO-1/Hyperion. Bottom: Latitudinal distributions of pure and mixed phase clouds, 2005-2015, showing Liquid Thickness Fraction (LTF). LTF=0 corresponds to pure ice absorption, while LTF=1 is pure liquid. The

  3. Global atmospheric particle formation from CERN CLOUD measurements

    CERN Document Server

    Dunne, E M; Kurten, A; Almeida, J; Duplissy, J; Williamson, C; Ortega, I K; Pringle, K J; Adamov, A; Baltensperger, U; Barmet, P; Benduhn, F; Bianchi, F; Breitenlechner, M; Clarke, A; Curtius, J; Dommen, J; Donahue, N M; Ehrhart, S; Flagan, R C; Franchin, A; Guida, R; Hakala, J; Hansel, A; Heinritzi, M; Jokinen, T; Kangasluoma, J; Kirkby, J; Kulmala, M; Kupc, A; Lawler, M J; Lehtipalo, K; Makhmutov, V; Mann, G; Mathot, S; Merikanto, J; Miettinen, P; Nenes, A; Onnela, A; Rap, A; Reddington, C L S; Riccobono, F; Richards, N A D; Rissanen, M P; Rondo, L; Sarnela, N; Schobesberger, S; Sengupta, K; Simon, M; Sipila, M; Smith, J N; Stozkhov, Y; Tome, A; Trostl, J; Wagner, P E; Wimmer, D; Winkler, P M; Worsnop, D R; Carslaw, K S

    2016-01-01

    Fundamental questions remain about the origin of newly formed atmospheric aerosol particles because data from laboratory measurements have been insufficient to build global models. In contrast, gas-phase chemistry models have been based on laboratory kinetics measurements for decades. Here we build a global model of aerosol formation using extensive laboratory-measured nucleation rates involving sulfuric acid, ammonia, ions and organic compounds. The simulations and a comparison with atmospheric observations show that nearly all nucleation throughout the present-day atmosphere involves ammonia or biogenic organic compounds in addition to sulfuric acid. A significant fraction of nucleation involves ions, but the relatively weak dependence on ion concentrations indicates that for the processes studied variations in cosmic ray intensity do not significantly affect climate via nucleation in the present-day atmosphere.

  4. The global influence of dust mineralogical composition on heterogeneous ice nucleation in mixed-phase clouds

    International Nuclear Information System (INIS)

    Hoose, C; Lohmann, U; Erdin, R; Tegen, I

    2008-01-01

    Mineral dust is the dominant natural ice nucleating aerosol. Its ice nucleation efficiency depends on the mineralogical composition. We show the first sensitivity studies with a global climate model and a three-dimensional dust mineralogy. Results show that, depending on the dust mineralogical composition, coating with soluble material from anthropogenic sources can lead to quasi-deactivation of natural dust ice nuclei. This effect counteracts the increased cloud glaciation by anthropogenic black carbon particles. The resulting aerosol indirect effect through the glaciation of mixed-phase clouds by black carbon particles is small (+0.1 W m -2 in the shortwave top-of-the-atmosphere radiation in the northern hemisphere)

  5. Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

    Directory of Open Access Journals (Sweden)

    Patrick H. Freeborn

    2014-02-01

    Full Text Available Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI Fire Thermal Anomaly (FTA detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS across the Central African Republic (CAR. Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI’s omission rate can be attributed to a coupling between SEVIRI’s low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI’s commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i future improvements to the SEVIRI FTA detection algorithm; (ii the assimilation of the SEVIRI and MODIS active fire products; and (iii the potential inclusion of SEVIRI into a network of geostationary

  6. Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

    Science.gov (United States)

    Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

    2017-12-01

    Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

  7. Influence of cirrus clouds on weather and climate processes A global perspective

    Science.gov (United States)

    Liou, K.-N.

    1986-01-01

    Current understanding and knowledge of the composition and structure of cirrus clouds are reviewed and documented in this paper. In addition, the radiative properties of cirrus clouds as they relate to weather and climate processes are described in detail. To place the relevance and importance of cirrus composition, structure and radiative properties into a global perspective, pertinent results derived from simulation experiments utilizing models with varying degrees of complexity are presented; these have been carried out for the investigation of the influence of cirrus clouds on the thermodynamics and dynamics of the atmosphere. In light of these reviews, suggestions are outlined for cirrus-radiation research activities aimed toward the development and improvement of weather and climate models for a physical understanding of cause and effect relationships and for prediction purposes.

  8. Observations of Co-variation in Cloud Properties and their Relationships with Atmospheric State

    Science.gov (United States)

    Sinclair, K.; van Diedenhoven, B.; Fridlind, A. M.; Arnold, T. G.; Yorks, J. E.; Heymsfield, G. M.; McFarquhar, G. M.; Um, J.

    2017-12-01

    Radiative properties of upper tropospheric ice clouds are generally not well represented in global and cloud models. Cloud top height, cloud thermodynamic phase, cloud optical thickness, cloud water path, particle size and ice crystal shape all serve as observational targets for models to constrain cloud properties. Trends or biases in these cloud properties could have profound effects on the climate since they affect cloud radiative properties. Better understanding of co-variation between these cloud properties and linkages with atmospheric state variables can lead to better representation of clouds in models by reducing biases in their micro- and macro-physical properties as well as their radiative properties. This will also enhance our general understanding of cloud processes. In this analysis we look at remote sensing, in situ and reanalysis data from the MODIS Airborne Simulator (MAS), Cloud Physics Lidar (CPL), Cloud Radar System (CRS), GEOS-5 reanalysis data and GOES imagery obtained during the Tropical Composition, Cloud and Climate Coupling (TC4) airborne campaign. The MAS, CPL and CRS were mounted on the ER-2 high-altitude aircraft during this campaign. In situ observations of ice size and shape were made aboard the DC8 and WB57 aircrafts. We explore how thermodynamic phase, ice effective radius, particle shape and radar reflectivity vary with altitude and also investigate how these observed cloud properties vary with cloud type, cloud top temperature, relative humidity and wind profiles. Observed systematic relationships are supported by physical interpretations of cloud processes and any unexpected differences are examined.

  9. Influence of Ice Particle Surface Roughening on the Global Cloud Radiative Effect

    Science.gov (United States)

    Yi, Bingqi; Yang, Ping; Baum, Bryan A.; LEcuyer, Tristan; Oreopoulos, Lazaros; Mlawer, Eli J.; Heymsfield, Andrew J.; Liou, Kuo-Nan

    2013-01-01

    Ice clouds influence the climate system by changing the radiation budget and large-scale circulation. Therefore, climate models need to have an accurate representation of ice clouds and their radiative effects. In this paper, new broadband parameterizations for ice cloud bulk scattering properties are developed for severely roughened ice particles. The parameterizations are based on a general habit mixture that includes nine habits (droxtals, hollow/solid columns, plates, solid/hollow bullet rosettes, aggregate of solid columns, and small/large aggregates of plates). The scattering properties for these individual habits incorporate recent advances in light-scattering computations. The influence of ice particle surface roughness on the ice cloud radiative effect is determined through simulations with the Fu-Liou and the GCM version of the Rapid Radiative Transfer Model (RRTMG) codes and the National Center for Atmospheric Research Community Atmosphere Model (CAM, version 5.1). The differences in shortwave (SW) and longwave (LW) radiative effect at both the top of the atmosphere and the surface are determined for smooth and severely roughened ice particles. While the influence of particle roughening on the single-scattering properties is negligible in the LW, the results indicate that ice crystal roughness can change the SW forcing locally by more than 10 W m(exp -2) over a range of effective diameters. The global-averaged SW cloud radiative effect due to ice particle surface roughness is estimated to be roughly 1-2 W m(exp -2). The CAM results indicate that ice particle roughening can result in a large regional SW radiative effect and a small but nonnegligible increase in the global LW cloud radiative effect.

  10. AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2

    Data.gov (United States)

    National Aeronautics and Space Administration — This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS...

  11. Global Electric Circuit Implications of Total Current Measurements over Electrified Clouds

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

    2009-01-01

    We determined total conduction (Wilson) currents and flash rates for 850 overflights of electrified clouds spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative Wilson currents. We combined these individual storm overflight statistics with global diurnal lightning variation data from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to estimate the thunderstorm and electrified shower cloud contributions to the diurnal variation in the global electric circuit. The contributions to the global electric circuit from lightning producing clouds are estimated by taking the mean current per flash derived from the overflight data for land and ocean overflights and combining it with the global lightning rates (for land and ocean) and their diurnal variation derived from the LIS/OTD data. We estimate the contribution of non-lightning producing electrified clouds by assuming several different diurnal variations and total non-electrified storm counts to produce estimates of the total storm currents (lightning and non-lightning producing storms). The storm counts and diurnal variations are constrained so that the resultant total current diurnal variation equals the diurnal variation in the fair weather electric field (+/-15%). These assumptions, combined with the airborne and satellite data, suggest that the total mean current in the global electric circuit ranges from 2.0 to 2.7 kA, which is greater than estimates made by others using other methods.

  12. Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

    Science.gov (United States)

    Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

    2016-01-01

    The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

  13. Multitemporal cross-calibration of the Terra MODIS and Landsat 7 ETM+ reflective solar bands

    Science.gov (United States)

    Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chander, Gyanesh; Choi, Taeyoung

    2013-01-01

    In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

  14. A Ten-Year Global Record of Absorbing Aerosols Above Clouds from OMI's Near-UV Observations

    Science.gov (United States)

    Jethva, Hiren; Torres, Omar; Ahn, Changwoo

    2016-01-01

    Aerosol-cloud interaction continues to be one of the leading uncertain components of climate models, primarily due to the lack of an adequate knowledge of the complex microphysical and radiative processes associated with the aerosol-cloud system. The situations when aerosols and clouds are found in the same atmospheric column, for instance, when light-absorbing aerosols such as biomass burning generated carbonaceous particles or wind-blown dust overlay low-level cloud decks, are commonly found over several regional of the world. Contrary to the cloud-free scenario over dark surface, for which aerosols are known to produce a net cooling effect (negative radiative forcing) on climate, the overlapping situation of absorbing aerosols over cloud can potentially exert a significant level of atmospheric absorption and produces a positive radiative forcing at top-of-atmosphere. The magnitude of direct radiative effects of aerosols above cloud depends directly on the aerosol loading, microphysical-optical properties of the aerosol layer and the underlying cloud deck, and geometric cloud fraction. We help in addressing this problem by introducing a novel product of optical depth of absorbing aerosols above clouds retrieved from near-UV observations made by the Ozone Monitoring Instrument (OMI) on board NASA's Aura platform. The presence of absorbing aerosols above cloud reduces the upwelling radiation reflected by cloud and produces a strong 'color ratio' effect in the near-UV region, which can be unambiguously detected in the OMI measurements. Physically based on this effect, the OMACA algorithm retrieves the optical depths of aerosols and clouds simultaneously under a prescribed state of atmosphere. The algorithm architecture and results from a ten-year global record including global climatology of frequency of occurrence and above-cloud aerosol optical depth, and a discussion on related future field campaigns are presented.

  15. The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

    Directory of Open Access Journals (Sweden)

    L. A. Lee

    2013-09-01

    Full Text Available Aerosol–cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day concentrations of cloud condensation nuclei (CCN. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

  16. Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

    Science.gov (United States)

    Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

    2018-01-01

    Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

  17. Quality Assessment of Collection 6 MODIS Atmospheric Science Products

    Science.gov (United States)

    Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.

    2015-12-01

    Since the launch of the NASA Terra and Aqua satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (MODIS Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA MODIS science team investigators. MODAPS completed Collection 6 reprocessing of MODIS Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the MODIS Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of MODIS operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the

  18. Time dependent charging of layer clouds in the global electric circuit

    Science.gov (United States)

    Zhou, Limin; Tinsley, Brian A.

    2012-09-01

    There is much observational data consistent with the hypothesis that the ionosphere-earth current density (Jz) in the global electric circuit, which is modulated by both solar activity and thunderstorm activity, affects atmospheric dynamics and cloud cover. One candidate mechanism involves Jz causing the accumulation of space charge on droplets and aerosol particles, that affects the rate of scavenging of the latter, notably those of Cloud Condensation Nuclei (CCN) and Ice Forming Nuclei (IFN) (Tinsley, 2008, 2010). Space charge is the difference, per unit volume, between total positive and total negative electrical charge that is on droplets, aerosol particles (including the CCN and IFN) and air ions. The cumulative effects of the scavenging in stratiform clouds and aerosol layers in an air mass over the lifetime of the aerosol particles of 1-10 days affects the concentration and size distribution of the CCN, so that in subsequent episodes of cloud formation (including deep convective clouds) there can be effects on droplet size distribution, coagulation, precipitation processes, and even storm dynamics.Because the time scales for charging for some clouds can be long compared to cloud lifetimes, the amount of charge at a given time, and its effect on scavenging, depend more on the charging rate than on the equilibrium charge that would eventually be attained. To evaluate this, a new time-dependent charging model has been developed. The results show that for typical altostratus clouds with typical droplet radii 10 μm and aerosol particles of radius of 0.04 μm, the time constant for charging in response to a change in Jz is about 800 s, which is comparable to cloud formation and dissipation timescales for some cloud situations. The charging timescale is found to be strong functions of altitude and aerosol concentration, with the time constant for droplet charging at 2 km in air with a high concentration of aerosols being about an hour, and for clouds at 10 km in

  19. Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters

    Directory of Open Access Journals (Sweden)

    V. A. Karydis

    2012-10-01

    Full Text Available We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity with a single execution. The adjoint is then integrated within three dimensional (3-D aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI Chemical Transport Model (CTM, using wind fields computed with the Goddard Institute for Space Studies (GISS Global Circulation Model (GCM II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS of the NASA Global Modeling and Assimilation Office (GMAO. We find that over polluted (pristine areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity. Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.

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

    Directory of Open Access Journals (Sweden)

    A. A. Kokhanovsky

    2006-01-01

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

  1. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

    Science.gov (United States)

    Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

    2010-12-01

    Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

  2. Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products

    Science.gov (United States)

    Ginoux, Paul; Prospero, Joseph M.; Gill, Thomas E.; Hsu, N. Christina; Zhao, Ming

    2012-09-01

    Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1°) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

  3. Toward Improving the Representation of Convection and Cloud-Radiation Interaction for Global Climate Simulations

    Science.gov (United States)

    Wu, X.; Song, X.; Deng, L.; Park, S.; Liang, X.; Zhang, G. J.

    2006-05-01

    Despite the significant progress made in developing general circulation models (GCMs), major uncertainties related to the parameterization of convection, cloud and radiation processes still remain. The current GCM credibility of seasonal-interannual climate predictions or climate change projections is limited. In particular, the following long-standing biases, common to most GCMs, need to be reduced: 1) over-prediction of high-level cloud amounts although GCMs realistically simulating the global radiation budget; 2) general failure to reproduce the seasonal variation and migration of the ITCZ precipitation; 3) incomplete representation of the Madden-Julian Oscillation (MJO); and 4) false production of an excessive cold tone of sea surface temperature across the Pacific basin and a double ITCZ structure in precipitation when the atmosphere and ocean are fully coupled. The development of cloud-resolving models (CRMs) provides a unique opportunity to address issues aimed to reduce these biases. The statistical analysis of CRM simulations together with the theoretical consideration of subgrid-scale processes will enable us to develop physically-based parameterization of convection, clouds, radiation and their interactions.

  4. Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

    Directory of Open Access Journals (Sweden)

    H. Andersen

    2017-08-01

    Full Text Available The role of aerosols, clouds and their interactions with radiation remain among the largest unknowns in the climate system. Even though the processes involved are complex, aerosol–cloud interactions are often analyzed by means of bivariate relationships. In this study, 15 years (2001–2015 of monthly satellite-retrieved near-global aerosol products are combined with reanalysis data of various meteorological parameters to predict satellite-derived marine liquid-water cloud occurrence and properties by means of region-specific artificial neural networks. The statistical models used are shown to be capable of predicting clouds, especially in regions of high cloud variability. On this monthly scale, lower-tropospheric stability is shown to be the main determinant of cloud fraction and droplet size, especially in stratocumulus regions, while boundary layer height controls the liquid-water amount and thus the optical thickness of clouds. While aerosols show the expected impact on clouds, at this scale they are less relevant than some meteorological factors. Global patterns of the derived sensitivities point to regional characteristics of aerosol and cloud processes.

  5. Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds

    Energy Technology Data Exchange (ETDEWEB)

    Turner, David, D.; Ferrare, Richard, A.

    2011-07-06

    The 'Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds' project focused extensively on the analysis and utilization of water vapor and aerosol profiles derived from the ARM Raman lidar at the Southern Great Plains ARM site. A wide range of different tasks were performed during this project, all of which improved quality of the data products derived from the lidar or advanced the understanding of atmospheric processes over the site. These activities included: upgrading the Raman lidar to improve its sensitivity; participating in field experiments to validate the lidar aerosol and water vapor retrievals; using the lidar aerosol profiles to evaluate the accuracy of the vertical distribution of aerosols in global aerosol model simulations; examining the correlation between relative humidity and aerosol extinction, and how these change, due to horizontal distance away from cumulus clouds; inferring boundary layer turbulence structure in convective boundary layers from the high-time-resolution lidar water vapor measurements; retrieving cumulus entrainment rates in boundary layer cumulus clouds; and participating in a field experiment that provided data to help validate both the entrainment rate retrievals and the turbulent profiles derived from lidar observations.

  6. Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

    Science.gov (United States)

    Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny

    2010-01-01

    Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

  7. Reassessing the effect of cloud type on Earth's energy balance

    Science.gov (United States)

    Hang, A.; L'Ecuyer, T.

    2017-12-01

    Cloud feedbacks depend critically on the characteristics of the clouds that change, their location and their environment. As a result, accurately predicting the impact of clouds on future climate requires a better understanding of individual cloud types and their spatial and temporal variability. This work revisits the problem of documenting the effects of distinct cloud regimes on Earth's radiation budget distinguishing cloud types according to their signatures in spaceborne active observations. Using CloudSat's multi-sensor radiative fluxes product that leverages high-resolution vertical cloud information from CloudSat, CALIPSO, and MODIS observations to provide the most accurate estimates of vertically-resolved radiative fluxes available to date, we estimate the global annual mean net cloud radiative effect at the top of the atmosphere to be -17.1 W m-2 (-44.2 W m-2 in the shortwave and 27.1 W m-2 in the longwave), slightly weaker than previous estimates from passive sensor observations. Multi-layered cloud systems, that are often misclassified using passive techniques but are ubiquitous in both hemispheres, contribute about -6.2 W m-2 of the net cooling effect, particularly at ITCZ and higher latitudes. Another unique aspect of this work is the ability of CloudSat and CALIPSO to detect cloud boundary information providing an improved capability to accurately discern the impact of cloud-type variations on surface radiation balance, a critical factor in modulating the disposition of excess energy in the climate system. The global annual net cloud radiative effect at the surface is estimated to be -24.8 W m-2 (-51.1 W m-2 in the shortwave and 26.3 W m-2 in the longwave), dominated by shortwave heating in multi-layered and stratocumulus clouds. Corresponding estimates of the effects of clouds on atmospheric heating suggest that clouds redistribute heat from poles to equator enhancing the general circulation.

  8. New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

    Science.gov (United States)

    Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

    2016-12-01

    Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

  9. Evaluation of factors controlling global secondary organic aerosol production from cloud processes

    Directory of Open Access Journals (Sweden)

    C. He

    2013-02-01

    Full Text Available Secondary organic aerosols (SOA exert a significant influence on ambient air quality and regional climate. Recent field, laboratorial and modeling studies have confirmed that in-cloud processes contribute to a large fraction of SOA production with large space-time heterogeneity. This study evaluates the key factors that govern the production of cloud-process SOA (SOAcld on a global scale based on the GFDL coupled chemistry-climate model AM3 in which full cloud chemistry is employed. The association between SOAcld production rate and six factors (i.e., liquid water content (LWC, total carbon chemical loss rate (TCloss, temperature, VOC/NOx, OH, and O3 is examined. We find that LWC alone determines the spatial pattern of SOAcld production, particularly over the tropical, subtropical and temperate forest regions, and is strongly correlated with SOAcld production. TCloss ranks the second and mainly represents the seasonal variability of vegetation growth. Other individual factors are essentially uncorrelated spatiotemporally to SOAcld production. We find that the rate of SOAcld production is simultaneously determined by both LWC and TCloss, but responds linearly to LWC and nonlinearly (or concavely to TCloss. A parameterization based on LWC and TCloss can capture well the spatial and temporal variability of the process-based SOAcld formation (R2 = 0.5 and can be easily applied to global three dimensional models to represent the SOA production from cloud processes.

  10. How important is biological ice nucleation in clouds on a global scale?

    International Nuclear Information System (INIS)

    Hoose, C; Kristjansson, J E; Burrows, S M

    2010-01-01

    The high ice nucleating ability of some biological particles has led to speculations about living and dead organisms being involved in cloud ice and precipitation formation, exerting a possibly significant influence on weather and climate. In the present study, the role of primary biological aerosol particles (PBAPs) as heterogeneous ice nuclei is investigated with a global model. Emission parametrizations for bacteria, fungal spores and pollen based on recent literature are introduced, as well as an immersion freezing parametrization based on classical nucleation theory and laboratory measurements. The simulated contribution of PBAPs to the global average ice nucleation rate is only 10 -5 %, with an uppermost estimate of 0.6%. At the same time, observed PBAP concentrations in air and biological ice nucleus concentrations in snow are reasonably well captured by the model. This implies that 'bioprecipitation' processes (snow and rain initiated by PBAPs) are of minor importance on the global scale.

  11. CAMEX-4 ER-2 MODIS AIRBORNE SIMULATOR (MAS) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The MODIS Airborne Simulator (MAS) is an airborne scanning spectrometer that acquires high spatial resolution imagery of cloud and surface features from its vantage...

  12. Protocol for Validation of the Land Surface Reflectance Fundamental Climate Data Record using AERONET: Application to the Global MODIS and VIIRS Data Records

    Science.gov (United States)

    Roger, J. C.; Vermote, E.; Holben, B. N.

    2014-12-01

    The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. It is essential that a careful validation of its uncertainties is performed on a global and continuous basis. One approach is the direct comparison of this product with ground measurements but that approach presents several issues related to scale, the episodic nature of ground measurements and the global representativeness. An alternative is to compare the surface reflectance product to reference reflectance determined from Top of atmosphere reflectance corrected using accurate radiative transfer code and very detailed measurements of the atmosphere obtained over the AERONET sites (Vermote and al, 2014, RSE) which allows to test for a large range of aerosol characteristics; formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. This paper describes the protocol we have been working on based on our experience with the AERONET data and its application to the MODIS and VIIRS record.

  13. Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

    Science.gov (United States)

    Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

    2010-01-01

    The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with

  14. A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

    Science.gov (United States)

    Wan, Zhanming; Hong, Yang; Khan, Sadiq; Gourley, Jonathan; Flamig, Zachary; Kirschbaum, Dalia; Tang, Guoqiang

    2014-01-01

    Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

  15. Variation of cosmic-ray flux and global cloud-coverage

    CERN Document Server

    Svensmark, H

    1998-01-01

    There has long been a search for a physical link between solar activity and the earth's climate. The most direct way the Sun could affect the Earth's climate would be through temporal changes in its luminosity, but observations have shown that these small to explain the observed temperature changes. This does not, however exclude the possibility of an indirect physical mechanism. In the talk it will be shown that the excellent correlations observed between solar activity parameters and climate c link between cosmic ray flux and global cloud cover.

  16. Validation of MODIS aerosol optical depth over the Mediterranean Coast

    Science.gov (United States)

    Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

    2013-04-01

    Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial

  17. Reducing Striping and Near Field Response Influence in the MODIS 1.38um Cirrus Detection Band.

    Science.gov (United States)

    Ackerman, S. A.; Moeller, C. C.; Frey, R. A.; Gumley, L. E.; Menzel, W. P.

    2002-05-01

    Since first light in February 2000, the MODIS L1B data from Terra has exhibited detector striping in the cirrus detection band at 1.38 um (B26). This band's unique characteristic is that it is potentially able to discriminate very thin cirrus (optical depth of 0.1) because water vapor absorption effectively attenuates the upwelling signal from the earth's surface, leaving a flat dark background underneath the thin cirrus. The striping has diminished the power of this band for detecting thin cirrus in the MODIS Cloud Mask (MOD35) over the global environment by imparting a structure on the background. The striping amplitude (valley to peak) is 10 - 15% of the MODIS Ltyp radiance in B26 over land backgrounds, thus exceeding the 5% radiance prelaunch accuracy specification for the band. Also unexpected has been the presence of earth surface reflectance in B26. Forward model calculations indicate that the two-way transmittance of B26 in-band (1% to 1% response) should be water (TPW) exceeds about 12 mm. However, MODIS B26 imagery has routinely shown land surface reflectance, such as Florida, even in very moist (TPW > 30 mm) tropical air masses. MODIS prelaunch test data suggests that a near field response (NFR) at about 1.3 um in the B26 filter may be contributing to this behavior. A destriping and out-of-band correction algorithm has been under development at the University of Wisconsin to address the these issues. The simple linear algorithm is based on tuning detector dependent influence coefficients for B26 as a function of B5 (1.24 um) radiance so that the corrected B26 radiance is near zero for all B26 detectors in moist atmospheric conditions. B5 was chosen as a surrogate to characterize the NFR leak in the B26 filter because of its close spectral proximity to the NFR leak. Real MODIS L1B data is being used to estimate the influence coefficients. The paper will describe the B5 based destriping and NFR correction algorithm and influence coefficient development. It

  18. IO strategies and data services for petascale data sets from a global cloud resolving model

    International Nuclear Information System (INIS)

    Schuchardt, K L; Palmer, B J; Daily, J A; Elsethagen, T O; Koontz, A S

    2007-01-01

    Global cloud resolving models at resolutions of 4km or less create significant challenges for simulation output, data storage, data management, and post-simulation analysis and visualization. To support efficient model output as well as data analysis, new methods for IO and data organization must be evaluated. The model we are supporting, the Global Cloud Resolving Model being developed at Colorado State University, uses a geodesic grid. The non-monotonic nature of the grid's coordinate variables requires enhancements to existing data processing tools and community standards for describing and manipulating grids. The resolution, size and extent of the data suggest the need for parallel analysis tools and allow for the possibility of new techniques in data mining, filtering and comparison to observations. We describe the challenges posed by various aspects of data generation, management, and analysis, our work exploring IO strategies for the model, and a preliminary architecture, web portal, and tool enhancements which, when complete, will enable broad community access to the data sets in familiar ways to the community

  19. Advancing global marine biogeography research with open-source GIS software and cloud-computing

    Science.gov (United States)

    Fujioka, Ei; Vanden Berghe, Edward; Donnelly, Ben; Castillo, Julio; Cleary, Jesse; Holmes, Chris; McKnight, Sean; Halpin, patrick

    2012-01-01

    Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

  20. Effects of stratocumulus, cumulus, and cirrus clouds on the UV-B diffuse to global ratio: Experimental and modeling results

    International Nuclear Information System (INIS)

    López, María Laura; Palancar, Gustavo G.; Toselli, Beatriz M.

    2012-01-01

    Broadband measurements of global and diffuse UV-B irradiance (280-315 nm) together with modeled and measured diffuse to global ratios (DGR) have been used to characterize the influence of different types of clouds on irradiance at the surface. Measurements were carried out during 2000-2001 in Córdoba City, Argentina. The Tropospheric Ultraviolet Visible (TUV) model was used to analyze the behavior of the modeled DGRs for different cloud optical depths and at different altitudes and solar zenith angles (SZA). Different cloud altitudes were also tested, although only the results for a cloud placed at 1.5-2.5 km of altitude are shown. A total of 16 day with stratocumulus, 12 with cumulus, and 16 with cirrus have been studied and compared among them and also against 21 clear sky days. Different behaviors were clearly detected and also differentiated through the analysis of the averages and the standard deviations of the DGRs: 1.02±0.06 for stratocumulus, 0.74±0.18 for cumulus, 0.63±0.12 for cirrus, and 0.60±0.13 for the clear sky days, respectively. Stratocumulus clouds showed a low variability in the DGR values, which were concentrated close to one at all SZAs. DGR values for cumulus clouds presented a large variability at all SZAs, mostly associated with the different optical depths. Finally, the closeness between the DGR values for cirrus clouds and the DGR values for clear days showed that these clouds generally do not strongly affect the UV-B irradiance at the surface at any SZA. In the opposite side, stratocumulus clouds were identified as those with the largest effects, at all SZAs, on the UV-B irradiance at the surface.

  1. Diurnal Variation of Tropical Ice Cloud Microphysics inferred from Global Precipitation Measurement Microwave Imager (GPM-GMI)'s Polarimetric Measurement

    Science.gov (United States)

    Gong, J.; Zeng, X.; Wu, D. L.; Li, X.

    2017-12-01

    Diurnal variation of tropical ice cloud has been well observed and examined in terms of the area of coverage, occurring frequency, and total mass, but rarely on ice microphysical parameters (habit, size, orientation, etc.) because of lack of direct measurements of ice microphysics on a high temporal and spatial resolutions. This accounts for a great portion of the uncertainty in evaluating ice cloud's role on global radiation and hydrological budgets. The design of Global Precipitation Measurement (GPM) mission's procession orbit gives us an unprecedented opportunity to study the diurnal variation of ice microphysics on the global scale for the first time. Dominated by cloud ice scattering, high-frequency microwave polarimetric difference (PD, namely the brightness temperature difference between vertically- and horizontally-polarized paired channel measurements) from the GPM Microwave Imager (GMI) has been proven by our previous study to be very valuable to infer cloud ice microphysical properties. Using one year of PD measurements at 166 GHz, we found that cloud PD exhibits a strong diurnal cycle in the tropics (25S-25N). The peak PD amplitude varies as much as 35% over land, compared to only 6% over ocean. The diurnal cycle of the peak PD value is strongly anti-correlated with local ice cloud occurring frequency and the total ice mass with a leading period of 3 hours for the maximum correlation. The observed PD diurnal cycle can be explained by the change of ice crystal axial ratio. Using a radiative transfer model, we can simulate the observed 166 GHz PD-brightness temperature curve as well as its diurnal variation using different axial ratio values, which can be caused by the diurnal variation of ice microphysical properties including particle size, percentage of horizontally-aligned non-spherical particles, and ice habit. The leading of the change of PD ahead of ice cloud mass and occurring frequency implies the important role microphysics play in the

  2. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 1999 on board the Terra satellite platform (a...

  3. GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Moderate-resolution Imaging Spectroradiometer (MODIS) is a scientific instrument (radiometer) launched by NASA in 2002 on board the Aqua satellite platform (a...

  4. The Collection 6 'dark-target' MODIS Aerosol Products

    Science.gov (United States)

    Levy, Robert C.; Mattoo, Shana; Munchak, Leigh A.; Kleidman, Richard G.; Patadia, Falguni; Gupta, Pawan; Remer, Lorraine

    2013-01-01

    Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and

  5. Comparison and Validation of Long Time Serial Global GEOV1 and Regional Australian MODIS Fractional Vegetation Cover Products Over the Australian Continent

    Directory of Open Access Journals (Sweden)

    Yanling Ding

    2015-05-01

    Full Text Available Fractional vegetation cover (FVC is one of the most critical parameters in monitoring vegetation status. Comprehensive assessment of the FVC products is critical for their improvement and use in land surface models. This study investigates the performances of two major long time serial FVC products: GEOV1 and Australian MODIS. The spatial and temporal consistencies of these products were compared during the 2000–2012 period over the main biome types across the Australian continent. Their accuracies were validated by 443 FVC in-situ measurements during the 2011–2012 period. Our results show that there are strong correlations between the GEOV1 and Australian MODIS FVC products over the main Australian continent while they exhibit large differences and uncertainties in the coastal regions covered by dense forests. GEOV1 and Australian MODIS describe similar seasonal variations over the main biome types with differences in magnitude, while Australian MODIS exhibit unstable temporal variations over grasslands and shifted seasonal variations over evergreen broadleaf forests. The GEOV1 and Australian MODIS products overestimate FVC values over the biome types with high vegetation density and underestimate FVC in sparsely vegetated areas and grasslands. Overall, the GEOV1 and Australian MODIS FVC products agree with in-situ FVC values with a RMSE around 0.10 over the Australian continent.

  6. Global and Regional Impacts of HONO on the Chemical Composition of Clouds and Aerosols

    Science.gov (United States)

    Elshorbany, Y. F.; Crutzen, P. J.; Steil, B.; Pozzer, A.; Tost, H.; Lelieveld, J.

    2014-01-01

    Recently, realistic simulation of nitrous acid (HONO) based on the HONO / NOx ratio of 0.02 was found to have a significant impact on the global budgets of HOx (OH + HO2) and gas phase oxidation products in polluted regions, especially in winter when other photolytic sources are of minor importance. It has been reported that chemistry-transport models underestimate sulphate concentrations, mostly during winter. Here we show that simulating realistic HONO levels can significantly enhance aerosol sulphate (S(VI)) due to the increased formation of H2SO4. Even though in-cloud aqueous phase oxidation of dissolved SO2 (S(IV)) is the main source of S(VI), it appears that HONO related enhancement of H2O2 does not significantly affect sulphate because of the predominantly S(IV) limited conditions, except over eastern Asia. Nitrate is also increased via enhanced gaseous HNO3 formation and N2O5 hydrolysis on aerosol particles. Ammonium nitrate is enhanced in ammonia-rich regions but not under ammonia-limited conditions. Furthermore, particle number concentrations are also higher, accompanied by the transfer from hydrophobic to hydrophilic aerosol modes. This implies a significant impact on the particle lifetime and cloud nucleating properties. The HONO induced enhancements of all species studied are relatively strong in winter though negligible in summer. Simulating realistic HONO levels is found to improve the model measurement agreement of sulphate aerosols, most apparent over the US. Our results underscore the importance of HONO for the atmospheric oxidizing capacity and corroborate the central role of cloud chemical processing in S(IV) formation

  7. Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

    Science.gov (United States)

    Karlsson, Karl-Göran; Håkansson, Nina

    2018-02-01

    The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts

  8. A GLOBAL SOLUTION TO TOPOLOGICAL RECONSTRUCTION OF BUILDING ROOF MODELS FROM AIRBORNE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    J. Yan

    2016-06-01

    Full Text Available This paper presents a global solution to building roof topological reconstruction from LiDAR point clouds. Starting with segmented roof planes from building LiDAR points, a BSP (binary space partitioning algorithm is used to partition the bounding box of the building into volumetric cells, whose geometric features and their topology are simultaneously determined. To resolve the inside/outside labelling problem of cells, a global energy function considering surface visibility and spatial regularization between adjacent cells is constructed and minimized via graph cuts. As a result, the cells are labelled as either inside or outside, where the planar surfaces between the inside and outside form the reconstructed building model. Two LiDAR data sets of Yangjiang (China and Wuhan University (China are used in the study. Experimental results show that the completeness of reconstructed roof planes is 87.5%. Comparing with existing data-driven approaches, the proposed approach is global. Roof faces and edges as well as their topology can be determined at one time via minimization of an energy function. Besides, this approach is robust to partial absence of roof planes and tends to reconstruct roof models with visibility-consistent surfaces.

  9. A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

    Science.gov (United States)

    Wehner, M. F.; Oliker, L.; Shalf, J.

    2008-12-01

    Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

  10. MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites

    Directory of Open Access Journals (Sweden)

    G. Blöschl

    2012-07-01

    Full Text Available Numerous global and regional validation studies have examined MODIS snow mapping accuracy by using measurements at climate stations, which are mainly at open sites. MODIS accuracy in alpine and forested regions is, however, still not well understood. The main objective of this study is to evaluate MODIS (MOD10A1 and MYD10A1 snow cover products in a small experimental catchment by using extensive snow course measurements at open and forest sites. The MODIS accuracy is tested in the Jalovecky creek catchment (northern Slovakia in the period 2000–2011. The results show that the combined Terra and Aqua images enable snow mapping at an overall accuracy of 91.5%. The accuracies at forested, open and mixed land uses at the Červenec sites are 92.7%, 98.3% and 81.8%, respectively. The use of a 2-day temporal filter enables a significant reduction in the number of days with cloud coverage and an increase in overall snow mapping accuracy. In total, the 2-day temporal filter decreases the number of cloudy days from 61% to 26% and increases the snow mapping accuracy to 94%. The results indicate three possible factors leading to misclassification of snow as land: patchy snow cover, limited MODIS geolocation accuracy and mapping algorithm errors. Out of a total of 27 misclassification cases, patchy snow cover, geolocation issues and mapping errors occur in 12, 12 and 3 cases, respectively.

  11. Evaluation results of the optimal estimation based, multi-sensor cloud property data sets derived from AVHRR heritage measurements in the Cloud_cci project.

    Science.gov (United States)

    Stapelberg, S.; Jerg, M.; Stengel, M.; Hollmann, R.

    2014-12-01

    In 2010 the ESA Climate Change Initiative (CCI) Cloud project was started with the objectives of generating a long-term coherent data set of cloud properties. The cloud properties considered are cloud mask, cloud top estimates, cloud optical thickness, cloud effective radius and post processed parameters such as cloud liquid and ice water path. During the first phase of the project 3 years of data spanning 2007 to 2009 have been produced on a global gridded daily and monthly mean basis. Next to the processing an extended evaluation study was started in order to gain a first understanding of the quality of the retrieved data. The critical discussion of the results of the evaluation holds a key role for the further development and improvement of the dataset's quality. The presentation will give a short overview of the evaluation study undertaken in the Cloud_cci project. The focus will be on the evaluation of gridded, monthly mean cloud fraction and cloud top data from the Cloud_cci AVHRR-heritage dataset with CLARA-A1, MODIS-Coll5, PATMOS-X and ISCCP data. Exemplary results will be shown. Strengths and shortcomings of the retrieval scheme as well as possible impacts of averaging approaches on the evaluation will be discussed. An Overview of Cloud_cci Phase 2 will be given.

  12. Global Observations of Aerosols and Clouds from Combined Lidar and Passive Instruments to Improve Radiation Budget and Climate Studies

    Science.gov (United States)

    Winker, David M.

    1999-01-01

    Current uncertainties in the effects of clouds and aerosols on the Earth radiation budget limit our understanding of the climate system and the potential for global climate change. Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations - Climatologie Etendue des Nuages et des Aerosols (PICASSO-CENA) is a recently approved satellite mission within NASA's Earth System Science Pathfinder (ESSP) program which will address these uncertainties with a unique suite of active and passive instruments. The Lidar In-space Technology Experiment (LITE) demonstrated the potential benefits of space lidar for studies of clouds and aerosols. PICASSO-CENA builds on this experience with a payload consisting of a two-wavelength polarization-sensitive lidar, an oxygen A-band spectrometer (ABS), an imaging infrared radiometer (IIR), and a wide field camera (WFC). Data from these instruments will be used to measure the vertical distributions of aerosols and clouds in the atmosphere, as well as optical and physical properties of aerosols and clouds which influence the Earth radiation budget. PICASSO-CENA will be flown in formation with the PM satellite of the NASA Earth Observing System (EOS) to provide a comprehensive suite of coincident measurements of atmospheric state, aerosol and cloud optical properties, and radiative fluxes. The mission will address critical uncertainties iin the direct radiative forcing of aerosols and clouds as well as aerosol influences on cloud radiative properties and cloud-climate radiation feedbacks. PICASSO-CENA is planned for a three year mission, with a launch in early 2003. PICASSO-CENA is being developed within the framework of a collaboration between NASA and CNES.

  13. The Use of MODIS NDVI Data for Characterizing Cropland Across the Great Lakes Basin

    Science.gov (United States)

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides new opportunities for characterizing land-cover (LC) to support monitoring and assessment studies at watershed, regional and global scales. This research evaluated the potential for using the MODIS Normalized Diff...

  14. Clouds, Wind and the Biogeography of Central American Cloud Forests: Remote Sensing, Atmospheric Modeling, and Walking in the Jungle

    Science.gov (United States)

    Lawton, R.; Nair, U. S.

    2011-12-01

    Cloud forests stand at the core of the complex of montane ecosystems that provide the backbone to the multinational Mesoamerican Biological Corridor, which seeks to protect a biodiversity conservation "hotspot" of global significance in an area of rapidly changing land use. Although cloud forests are generally defined by frequent and prolonged immersion in cloud, workers differ in their feelings about "frequent" and "prolonged", and quantitative assessments are rare. Here we focus on the dry season, in which the cloud and mist from orographic cloud plays a critical role in forest water relations, and discuss remote sensing of orographic clouds, and regional and atmospheric modeling at several scales to quantitatively examine the distribution of the atmospheric conditions that characterize cloud forests. Remote sensing using data from GOES reveals diurnal and longer scale patterns in the distribution of dry season orographic clouds in Central America at both regional and local scales. Data from MODIS, used to calculate the base height of orographic cloud banks, reveals not only the geographic distributon of cloud forest sites, but also striking regional variation in the frequency of montane immersion in orographic cloud. At a more local scale, wind is known to have striking effects on forest structure and species distribution in tropical montane ecosystems, both as a general mechanical stress and as the major agent of ecological disturbance. High resolution regional atmospheric modeling using CSU RAMS in the Monteverde cloud forests of Costa Rica provides quantitative information on the spatial distribution of canopy level winds, insight into the spatial structure and local dynamics of cloud forest communities. This information will be useful in not only in local conservation planning and the design of the Mesoamerican Biological Corridor, but also in assessments of the sensitivity of cloud forests to global and regional climate changes.

  15. Insights from a Regime Decomposition Approach on CERES and CloudSat-inferred Cloud Radiative Effects

    Science.gov (United States)

    Oreopoulos, L.; Cho, N.; Lee, D.

    2015-12-01

    Our knowledge of the Cloud Radiative Effect (CRE) not only at the Top-of-the-Atmosphere (TOA), but also (with the help of some modeling) at the surface (SFC) and within the atmospheric column (ATM) has been steadily growing in recent years. Not only do we have global values for these CREs, but we can now also plot global maps of their geographical distribution. The next step in our effort to advance our knowledge of CRE is to systematically assess the contributions of prevailing cloud systems to the global values. The presentation addresses this issue directly. We identify the world's prevailing cloud systems, which we call "Cloud Regimes" (CRs) via clustering analysis of MODIS (Aqua-Terra) daily joint histograms of Cloud Top Pressure and Cloud Optical Thickness (TAU) at 1 degree scales. We then composite CERES diurnal values of CRE (TOA, SFC, ATM) separately for each CR by averaging these values for each CR occurrence, and thus find the contribution of each CR to the global value of CRE. But we can do more. We can actually decompose vertical profiles of inferred instantaneous CRE from CloudSat/CALIPSO (2B-FLXHR-LIDAR product) by averaging over Aqua CR occurrences (since A-Train formation flying allows collocation). Such an analysis greatly enhances our understanding of the radiative importance of prevailing cloud mixtures at different atmospheric levels. We can, for example, in addition to examining whether the CERES findings on which CRs contribute to radiative cooling and warming of the atmospheric column are consistent with CloudSat, also gain insight on why and where exactly this happens from the shape of the full instantaneous CRE vertical profiles.

  16. A 'special effort' to provide improved sounding and cloud-motion wind data for FGGE. [First GARP Global Experiment

    Science.gov (United States)

    Greaves, J. R.; Dimego, G.; Smith, W. L.; Suomi, V. E.

    1979-01-01

    Enhancement and editing of high-density cloud motion wind assessments and research satellite soundings have been necessary to improve the quality of data used in The Global Weather Experiment. Editing operations are conducted by a man-computer interactive data access system. Editing will focus on such inputs as non-US satellite data, NOAA operational sounding and wind data sets, wind data from the Indian Ocean satellite, dropwindsonde data, and tropical mesoscale wind data. Improved techniques for deriving cloud heights and higher resolution sounding in meteorologically active areas are principal parts of the data enhancement program.

  17. Analysis, improvement and application of the MODIS leaf area index products

    Science.gov (United States)

    Yang, Wenze

    Green leaf area governs the exchanges of energy, mass and momentum between the Earth's surface and the atmosphere. Therefore, leaf area index (LAI) and fraction of incident photosynthetically active radiation (0.4-0.7 mum) absorbed by the vegetation canopy (FPAR) are widely used in vegetation monitoring and modeling. The launch of Terra and Aqua satellites with the moderate resolution imaging spectroradiometer (MODIS) instrument onboard provided the first global products of LAI and FPAR, derived mainly from an algorithm based on radiative transfer. The objective of this research is to comprehensively evaluate the Terra and Aqua MODIS LAI/FPAR products. Large volumes of these products have been analyzed with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus back-up), snow (snow-free versus snow on the ground) and cloud (cloud-free versus cloudy) conditions. Field validation efforts identified several key factors that influence the accuracy of algorithm retrievals. The strategy of validation efforts guiding algorithm refinements has led to progressively more accurate LAI/FPAR products. The combination of products derived from the Terra and Aqua MODIS sensors increases the success rate of the main radiative transfer algorithm by 10-20 percent over woody vegetation. The Terra Collection 4 LAI data reveal seasonal swings in green leaf area of about 25 percent in a majority of the Amazon rainforests caused by variability in cloud cover and light. The timing and the influence of this seasonal cycle are critical to understanding tropical plant adaptation patterns and ecological processes. The results presented in this dissertation suggest how the product quality has gradually improved largely through the efforts of validation activities. The Amazon case study highlights the utility of these data sets for monitoring global vegetation dynamics. Thus, these results can be seen as a benchmark for evaluation of

  18. Validation of MODIS snow cover images over Austria

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

  19. Genetika MODY diabetu

    OpenAIRE

    Dušátková, Petra

    2012-01-01

    The most common form of monogenic diabetes is MODY (Maturity-Onset Diabetes of the Young). It ranks among genetic defects of the β cell. It is clinically heterogenous group of disorders characterised with non insulin-dependent diabetes mellitus with autosomal dominant inheritance and age at diagnosis up to 40 years. We specified the diagnosis of MODY in more than 240 Czech families using molecular-genetic approach. The most common subtype of MODY is GCK-MODY which was proved in 376 subjects f...

  20. Global anthropogenic aerosol effects on convective clouds in ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    U. Lohmann

    2008-04-01

    Full Text Available Aerosols affect the climate system by changing cloud characteristics in many ways. They act as cloud condensation and ice nuclei and may have an influence on the hydrological cycle. Here we investigate aerosol effects on convective clouds by extending the double-moment cloud microphysics scheme developed for stratiform clouds, which is coupled to the HAM double-moment aerosol scheme, to convective clouds in the ECHAM5 general circulation model. This enables us to investigate whether more, and smaller cloud droplets suppress the warm rain formation in the lower parts of convective clouds and thus release more latent heat upon freezing, which would then result in more vigorous convection and more precipitation. In ECHAM5, including aerosol effects in large-scale and convective clouds (simulation ECHAM5-conv reduces the sensitivity of the liquid water path increase with increasing aerosol optical depth in better agreement with observations and large-eddy simulation studies. In simulation ECHAM5-conv with increases in greenhouse gas and aerosol emissions since pre-industrial times, the geographical distribution of the changes in precipitation better matches the observed increase in precipitation than neglecting microphysics in convective clouds. In this simulation the convective precipitation increases the most suggesting that the convection has indeed become more vigorous.

  1. Cloud structure evolution of heavy rain events from the East-West Pacific Ocean: a combined global observation analysis

    Science.gov (United States)

    Sekaranom, A. B.; Nurjani, E.; Pujiastuti, I.

    2018-04-01

    Heavy rain events are often associated with flood hazards as one of the most devastating events across the globe. It is therefore essential to identify the evolution of heavy rainfall cloud structures, primarily from global satellite observation, as a tool to provide better disaster early warning systems. To identify the mechanism of heavy rainfall systems and its relationship with cloud development, especially over The Pacific Ocean, we aim to study the westward evolution of the convective systems over this area. Several datasets from Tropical Rainfall Measuring Mission (TRMM), CloudSat GEOPROF product, and ECMWF-reanalysis (ERA) interim were utilized to characterize the evolution. Geolocation and orbital time-lag analysis of the three different datasets for more than 8 years (2006-2014) could provide information related to the evolution of cloud structures associated with heavy rain events. In the first step, a heavy rainfall database was generated from TRMM. The CloudSat coordinate and time position were then matched with TRMM coordinate and time position. All of the processes were programatically conducted in fortran programming language. The result shows a transition between East and West Pacific ocean for TMI data.

  2. Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

    Science.gov (United States)

    Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

    2018-02-01

    Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

  3. Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

    Science.gov (United States)

    De Boer, G.; Shupe, M.D.; Caldwell, P.M.; Bauer, Susanne E.; Persson, O.; Boyle, J.S.; Kelley, M.; Klein, S.A.; Tjernstrom, M.

    2014-01-01

    Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

  4. Development of multi-sensor global cloud and radiance composites for earth radiation budget monitoring from DSCOVR

    Science.gov (United States)

    Khlopenkov, Konstantin; Duda, David; Thieman, Mandana; Minnis, Patrick; Su, Wenying; Bedka, Kristopher

    2017-10-01

    The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95% of the globe.

  5. [Winter wheat area estimation with MODIS-NDVI time series based on parcel].

    Science.gov (United States)

    Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

    2011-05-01

    Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

  6. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

    Directory of Open Access Journals (Sweden)

    Tao Yu

    2018-02-01

    Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

  7. Global model comparison of heterogeneous ice nucleation parameterizations in mixed phase clouds

    Science.gov (United States)

    Yun, Yuxing; Penner, Joyce E.

    2012-04-01

    A new aerosol-dependent mixed phase cloud parameterization for deposition/condensation/immersion (DCI) ice nucleation and one for contact freezing are compared to the original formulations in a coupled general circulation model and aerosol transport model. The present-day cloud liquid and ice water fields and cloud radiative forcing are analyzed and compared to observations. The new DCI freezing parameterization changes the spatial distribution of the cloud water field. Significant changes are found in the cloud ice water fraction and in the middle cloud fractions. The new DCI freezing parameterization predicts less ice water path (IWP) than the original formulation, especially in the Southern Hemisphere. The smaller IWP leads to a less efficient Bergeron-Findeisen process resulting in a larger liquid water path, shortwave cloud forcing, and longwave cloud forcing. It is found that contact freezing parameterizations have a greater impact on the cloud water field and radiative forcing than the two DCI freezing parameterizations that we compared. The net solar flux at top of atmosphere and net longwave flux at the top of the atmosphere change by up to 8.73 and 3.52 W m-2, respectively, due to the use of different DCI and contact freezing parameterizations in mixed phase clouds. The total climate forcing from anthropogenic black carbon/organic matter in mixed phase clouds is estimated to be 0.16-0.93 W m-2using the aerosol-dependent parameterizations. A sensitivity test with contact ice nuclei concentration in the original parameterization fit to that recommended by Young (1974) gives results that are closer to the new contact freezing parameterization.

  8. Moving to Google Cloud: Renovation of Global Borehole Temperature Database for Climate Research

    Science.gov (United States)

    Xiong, Y.; Huang, S.

    2013-12-01

    Borehole temperature comprises an independent archive of information on climate change which is complementary to the instrumental and other proxy climate records. With support from the international geothermal community, a global database of borehole temperatures has been constructed for the specific purpose of the study on climate change. Although this database has become an important data source in climate research, there are certain limitations partially because the framework of the existing borehole temperature database was hand-coded some twenty years ago. A database renovation work is now underway to take the advantages of the contemporary online database technologies. The major intended improvements include 1) dynamically linking a borehole site to Google Earth to allow for inspection of site specific geographical information; 2) dynamically linking an original key reference of a given borehole site to Google Scholar to allow for a complete list of related publications; and 3) enabling site selection and data download based on country, coordinate range, and contributor. There appears to be a good match between the enhancement requirements for this database and the functionalities of the newly released Google Fusion Tables application. Google Fusion Tables is a cloud-based service for data management, integration, and visualization. This experimental application can consolidate related online resources such as Google Earth, Google Scholar, and Google Drive for sharing and enriching an online database. It is user friendly, allowing users to apply filters and to further explore the internet for additional information regarding the selected data. The users also have ways to map, to chart, and to calculate on the selected data, and to download just the subset needed. The figure below is a snapshot of the database currently under Google Fusion Tables renovation. We invite contribution and feedback from the geothermal and climate research community to make the

  9. A cosmic ray-climate link and cloud observations

    Directory of Open Access Journals (Sweden)

    Dunne Eimear M.

    2012-11-01

    Full Text Available Despite over 35 years of constant satellite-based measurements of cloud, reliable evidence of a long-hypothesized link between changes in solar activity and Earth’s cloud cover remains elusive. This work examines evidence of a cosmic ray cloud link from a range of sources, including satellite-based cloud measurements and long-term ground-based climatological measurements. The satellite-based studies can be divided into two categories: (1 monthly to decadal timescale analysis and (2 daily timescale epoch-superpositional (composite analysis. The latter analyses frequently focus on sudden high-magnitude reductions in the cosmic ray flux known as Forbush decrease events. At present, two long-term independent global satellite cloud datasets are available (ISCCP and MODIS. Although the differences between them are considerable, neither shows evidence of a solar-cloud link at either long or short timescales. Furthermore, reports of observed correlations between solar activity and cloud over the 1983–1995 period are attributed to the chance agreement between solar changes and artificially induced cloud trends. It is possible that the satellite cloud datasets and analysis methods may simply be too insensitive to detect a small solar signal. Evidence from ground-based studies suggests that some weak but statistically significant cosmic ray-cloud relationships may exist at regional scales, involving mechanisms related to the global electric circuit. However, a poor understanding of these mechanisms and their effects on cloud makes the net impacts of such links uncertain. Regardless of this, it is clear that there is no robust evidence of a widespread link between the cosmic ray flux and clouds.

  10. Recent Trends of the Tropical Hydrological Cycle Inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

    Science.gov (United States)

    Zhou, Y. P.; Xu, Kuan-Man; Sud, Y. C.; Betts, A. K.

    2011-01-01

    Scores of modeling studies have shown that increasing greenhouse gases in the atmosphere impact the global hydrologic cycle; however, disagreements on regional scales are large, and thus the simulated trends of such impacts, even for regions as large as the tropics, remain uncertain. The present investigation attempts to examine such trends in the observations using satellite data products comprising Global Precipitation Climatology Project precipitation and International Satellite Cloud Climatology Project cloud and radiation. Specifically, evolving trends of the tropical hydrological cycle over the last 20-30 years were identified and analyzed. The results show (1) intensification of tropical precipitation in the rising regions of the Walker and Hadley circulations and weakening over the sinking regions of the associated overturning circulation; (2) poleward shift of the subtropical dry zones (up to 2deg/decade in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7deg/decade in June-July-August and September-October-November in the Southern Hemisphere) consistent with an overall broadening of the Hadley circulation; and (3) significant poleward migration (0.9-1.7deg/decade) of cloud boundaries of Hadley cell and plausible narrowing of the high cloudiness in the Intertropical Convergence Zone region in some seasons. These results support findings of some of the previous studies that showed strengthening of the tropical hydrological cycle and expansion of the Hadley cell that are potentially related to the recent global warming trends.

  11. The comparison of MODIS-Aqua (C5 and CALIOP (V2 & V3 aerosol optical depth

    Directory of Open Access Journals (Sweden)

    J. Redemann

    2012-03-01

    Full Text Available We assess the consistency between instantaneously collocated level-2 aerosol optical depth (AOD retrievals from MODIS-Aqua (C5 and CALIOP (Version 2 & 3, comparing the standard MODIS AOD (MYD04_L2 data to the AOD calculated from CALIOP aerosol extinction profiles for both the previous release (V2 and the latest release (V3 of CALIOP data. Based on data collected in January 2007, we investigate the most useful criteria for screening the MODIS and CALIOP retrievals to achieve the best agreement between the two data sets. Applying these criteria to eight months of data (Jan, Apr, Jul, Oct 2007 and 2009, we find an order of magnitude increase for the CALIOP V3 data density (by comparison to V2, that is generally accompanied by equal or better agreement with MODIS AOD. Differences in global, monthly mean, over-ocean AOD (532 nm between CALIOP and MODIS range between 0.03 and 0.04 for CALIOP V3, with CALIOP generally biased low, when all available data from both sensors are considered. Root-mean-squares (RMS differences in instantaneously collocated AOD retrievals by the two instruments are reduced from values ranging between 0.14 and 0.19 using the unscreened V3 data to values ranging from 0.09 to 0.1 for the screened data. A restriction to scenes with cloud fractions less than 1% (as defined in the MODIS aerosol retrievals generally results in improved correlation (R2>0.5, except for the month of July when correlations remain relatively lower. Regional assessments show hot spots in disagreement between the two sensors in Asian outflow during April and off the coast of South Africa in July.

  12. Providing Access and Visualization to Global Cloud Properties from GEO Satellites

    Science.gov (United States)

    Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.; Ayers, J. K.

    2015-12-01

    Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition. This project builds upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider. Using the Open Geospatial Consortium's Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also "merged" datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.

  13. Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: Part III. Using Combined PCA to Compare Spatiotemporal Variability of MODIS, MISR and OMI Aerosol Optical Depth

    Science.gov (United States)

    Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

    2014-01-01

    Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR.

  14. Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    U. Lohmann

    2007-07-01

    Full Text Available The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and −35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient.

    The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to −1.9 W m−2 in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to −0.7 W m−2. The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

  15. Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

    Science.gov (United States)

    Khlopenkov, K. V.; Duda, D. P.; Thieman, M. M.; Sun-Mack, S.; Su, W.; Minnis, P.; Bedka, K. M.

    2017-12-01

    The Deep Space Climate Observatory (DSCOVR) is designed to study the daytime Earth radiation budget by means of onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC imager observes in several shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and total broadband windows. Calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers. These properties have to be co-located with EPIC imager pixels to provide scene identification and to select anisotropic directional models, which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. The highest quality observation is selected by means of an aggregated rating which incorporates several factors such as the nearest time relative to EPIC observation, lowest viewing zenith angle, and others. This process provides a smoother transition and avoids abrupt changes in the merged composite data. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into the EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. Within every EPIC footprint, the PSF-weighted average radiances and cloud properties are computed for each cloud phase and then stored within five data subsets (clear-sky, water cloud, ice cloud, total cloud, and no

  16. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF)- Test data in HDF (CER_SSF_TRMM-PFM-VIRS_Subset-Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  17. CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_TRMM-PFM-VIRS_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop

  18. Using Long-Term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds Over Global Oceans

    Science.gov (United States)

    Zhao, Xuepeng; Liu, Yangang; Yu, Fangquan; Heidinger, Andrew K.

    2018-01-01

    Long-term (1981-2011) satellite climate data records of clouds and aerosols are used to investigate the aerosol-cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effects (AIEs) are evident in long-term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 change of long-term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. The sensitive regime of the conventional AIE identified in this observational study is likely associated with the transitional regime from the aerosol-limited regime to the updraft-limited regime identified for aerosol-cloud interaction in cloud model simulations.

  19. Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

    Science.gov (United States)

    Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

    2005-12-01

    Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

  20. Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

    Directory of Open Access Journals (Sweden)

    K. Zakšek

    2013-03-01

    Full Text Available Volcanic ash cloud-top height (ACTH can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3–4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

  1. Sensitivity of aerosol indirect forcing and autoconversion to cloud droplet parameterization: an assessment with the NASA Global Modeling Initiative.

    Science.gov (United States)

    Sotiropoulou, R. P.; Meshkhidze, N.; Nenes, A.

    2006-12-01

    The aerosol indirect forcing is one of the largest sources of uncertainty in assessments of anthropogenic climate change [IPCC, 2001]. Much of this uncertainty arises from the approach used for linking cloud droplet number concentration (CDNC) to precursor aerosol. Global Climate Models (GCM) use a wide range of cloud droplet activation mechanisms ranging from empirical [Boucher and Lohmann, 1995] to detailed physically- based formulations [e.g., Abdul-Razzak and Ghan, 2000; Fountoukis and Nenes, 2005]. The objective of this study is to assess the uncertainties in indirect forcing and autoconversion of cloud water to rain caused by the application of different cloud droplet parameterization mechanisms; this is an important step towards constraining the aerosol indirect effects (AIE). Here we estimate the uncertainty in indirect forcing and autoconversion rate using the NASA Global Model Initiative (GMI). The GMI allows easy interchange of meteorological fields, chemical mechanisms and the aerosol microphysical packages. Therefore, it is an ideal tool for assessing the effect of different parameters on aerosol indirect forcing. The aerosol module includes primary emissions, chemical production of sulfate in clear air and in-cloud aqueous phase, gravitational sedimentation, dry deposition, wet scavenging in and below clouds, and hygroscopic growth. Model inputs include SO2 (fossil fuel and natural), black carbon (BC), organic carbon (OC), mineral dust and sea salt. The meteorological data used in this work were taken from the NASA Data Assimilation Office (DAO) and two different GCMs: the NASA GEOS4 finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II' (GISS II') GCM. Simulations were carried out for "present day" and "preindustrial" emissions using different meteorological fields (i.e. DAO, FVGCM, GISS II'); cloud droplet number concentration is computed from the correlations of Boucher and Lohmann [1995], Abdul-Razzak and Ghan [2000

  2. Global model simulations of the impact of ocean-going ships on aerosols, clouds, and the radiation budget

    Directory of Open Access Journals (Sweden)

    A. Lauer

    2007-10-01

    Full Text Available International shipping contributes significantly to the fuel consumption of all transport related activities. Specific emissions of pollutants such as sulfur dioxide (SO2 per kg of fuel emitted are higher than for road transport or aviation. Besides gaseous pollutants, ships also emit various types of particulate matter. The aerosol impacts the Earth's radiation budget directly by scattering and absorbing the solar and thermal radiation and indirectly by changing cloud properties. Here we use ECHAM5/MESSy1-MADE, a global climate model with detailed aerosol and cloud microphysics to study the climate impacts of international shipping. The simulations show that emissions from ships significantly increase the cloud droplet number concentration of low marine water clouds by up to 5% to 30% depending on the ship emission inventory and the geographic region. Whereas the cloud liquid water content remains nearly unchanged in these simulations, effective radii of cloud droplets decrease, leading to cloud optical thickness increase of up to 5–10%. The sensitivity of the results is estimated by using three different emission inventories for present-day conditions. The sensitivity analysis reveals that shipping contributes to 2.3% to 3.6% of the total sulfate burden and 0.4% to 1.4% to the total black carbon burden in the year 2000 on the global mean. In addition to changes in aerosol chemical composition, shipping increases the aerosol number concentration, e.g. up to 25% in the size range of the accumulation mode (typically >0.1 μm over the Atlantic. The total aerosol optical thickness over the Indian Ocean, the Gulf of Mexico and the Northeastern Pacific increases by up to 8–10% depending on the emission inventory. Changes in aerosol optical thickness caused by shipping induced modification of aerosol particle number concentration and chemical composition lead to a change in the shortwave radiation budget at the top of the

  3. Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

    Science.gov (United States)

    Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

    Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

  4. Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds

    Energy Technology Data Exchange (ETDEWEB)

    Richard A. Ferrare; David D. Turner

    2011-09-01

    Project goals: (1) Use the routine surface and airborne measurements at the ARM SGP site, and the routine surface measurements at the NSA site, to continue our evaluations of model aerosol simulations; (2) Determine the degree to which the Raman lidar measurements of water vapor and aerosol scattering and extinction can be used to remotely characterize the aerosol humidification factor; (3) Use the high temporal resolution CARL data to examine how aerosol properties vary near clouds; and (4) Use the high temporal resolution CARL and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thin continental cumulus clouds.

  5. Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

    Science.gov (United States)

    Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

    2018-04-01

    Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the

  6. A 3D approach to reconstruct continuous optical images using lidar and MODIS

    Directory of Open Access Journals (Sweden)

    HuaGuo Huang

    2015-06-01

    Full Text Available Background Monitoring forest health and biomass for changes over time in the global environment requires the provision of continuous satellite images. However, optical images of land surfaces are generally contaminated when clouds are present or rain occurs. Methods To estimate the actual reflectance of land surfaces masked by clouds and potential rain, 3D simulations by the RAPID radiative transfer model were proposed and conducted on a forest farm dominated by birch and larch in Genhe City, DaXing’AnLing Mountain in Inner Mongolia, China. The canopy height model (CHM from lidar data were used to extract individual tree structures (location, height, crown width. Field measurements related tree height to diameter of breast height (DBH, lowest branch height and leaf area index (LAI. Series of Landsat images were used to classify tree species and land cover. MODIS LAI products were used to estimate the LAI of individual trees. Combining all these input variables to drive RAPID, high-resolution optical remote sensing images were simulated and validated with available satellite images. Results Evaluations on spatial texture, spectral values and directional reflectance were conducted to show comparable results. Conclusions The study provides a proof-of-concept approach to link lidar and MODIS data in the parameterization of RAPID models for high temporal and spatial resolutions of image reconstruction in forest dominated areas.

  7. New Approach for Snow Cover Detection through Spectral Pattern Recognition with MODIS Data

    Directory of Open Access Journals (Sweden)

    Kyeong-Sang Lee

    2017-01-01

    Full Text Available Snow cover plays an important role in climate and hydrology, at both global and regional scales. Most previous studies have used static threshold techniques to detect snow cover, which can lead to errors such as misclassification of snow and clouds, because the reflectance of snow cover exhibits variability and is affected by several factors. Therefore, we present a simple new algorithm for mapping snow cover from Moderate Resolution Imaging Spectroradiometer (MODIS data using dynamic wavelength warping (DWW, which is based on dynamic time warping (DTW. DTW is a pattern recognition technique that is widely used in various fields such as human action recognition, anomaly detection, and clustering. Before performing DWW, we constructed 49 snow reflectance spectral libraries as reference data for various solar zenith angle and digital elevation model conditions using approximately 1.6 million sampled data. To verify the algorithm, we compared our results with the MODIS swath snow cover product (MOD10_L2. Producer’s accuracy, user’s accuracy, and overall accuracy values were 92.92%, 78.41%, and 92.24%, respectively, indicating good overall classification accuracy. The proposed algorithm is more useful for discriminating between snow cover and clouds than threshold techniques in some areas, such as those with a high viewing zenith angle.

  8. Influence which masses of clouds have on the global solar radiation at Salamanca (Spain). Estudio de la interaccin nubosidad-radiacion solar en Salamanca

    Energy Technology Data Exchange (ETDEWEB)

    Pablo-Davila, F. de, Labajo, J.L.; Tomas-Sanchez, C

    1991-01-01

    It has been shown the influence which masses of clouds, (and more specifically for each group of cloud types: high, middle and low clauds), has on the global solar radiation recorded at Matacan (Salamanca), within the period 1977-1985. For this purpose, cloud observation were made every three hours; daily records of sunshine and solar radiation were continually taken too. It has also been, both graphically and numerically, the influence of each cloud type for monthly and seasonal periods. Futhermore, different statistical parameters have been presented in order to describe the method developed. Finally, the results have been analysed and evaluated. They have been explaines according to the composition, structure and radiative properties of clouds.(Author)

  9. Parameterization of cloud droplet formation for global and regional models: including adsorption activation from insoluble CCN

    Directory of Open Access Journals (Sweden)

    P. Kumar

    2009-04-01

    Full Text Available Dust and black carbon aerosol have long been known to exert potentially important and diverse impacts on cloud droplet formation. Most studies to date focus on the soluble fraction of these particles, and overlook interactions of the insoluble fraction with water vapor (even if known to be hydrophilic. To address this gap, we developed a new parameterization that considers cloud droplet formation within an ascending air parcel containing insoluble (but wettable particles externally mixed with aerosol containing an appreciable soluble fraction. Activation of particles with a soluble fraction is described through well-established Köhler theory, while the activation of hydrophilic insoluble particles is treated by "adsorption-activation" theory. In the latter, water vapor is adsorbed onto insoluble particles, the activity of which is described by a multilayer Frenkel-Halsey-Hill (FHH adsorption isotherm modified to account for particle curvature. We further develop FHH activation theory to i find combinations of the adsorption parameters AFHH, BFHH which yield atmospherically-relevant behavior, and, ii express activation properties (critical supersaturation that follow a simple power law with respect to dry particle diameter.

    The new parameterization is tested by comparing the parameterized cloud droplet number concentration against predictions with a detailed numerical cloud model, considering a wide range of particle populations, cloud updraft conditions, water vapor condensation coefficient and FHH adsorption isotherm characteristics. The agreement between parameterization and parcel model is excellent, with an average error of 10% and R2~0.98. A preliminary sensitivity study suggests that the sublinear response of droplet number to Köhler particle concentration is not as strong for FHH particles.

  10. Accuracy assessment of Terra-MODIS aerosol optical depth retrievals

    International Nuclear Information System (INIS)

    Safarpour, Sahabeh; Abdullah, Khiruddin; Lim, Hwee San; Dadras, Mohsen

    2014-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products have been widely used to address environment and climate change subjects with daily global coverage. Aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. MODIS-Terra and Global Aerosol Robotic Network (AERONET) products can be obtained from the Multi-sensor Aerosol Products Sampling System (MAPSS) for coastal regions during 2000-2010. Using data collected from 83 coastal stations worldwide from AERONET from 2000-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard the Terra satellite. AOD retrieved from MODIS at 0.55μm wavelength has been compared With the AERONET derived AOD, because it is reliable with the major wavelength used by many chemistry transport and climate models as well as previous MODIS validation studies. After removing retrievals with quality flags below1 for Ocean algorithm and below 3 for Land algorithm, The accuracy of AOD retrieved from MODIS Dark Target Ocean algorithms (correlation coefficient R 2 is 0.844 and a regression equation of τ M = 0.91·τ A + 0.02 (where subscripts M and A represent MODIS and AERONET respectively), is the greater than the MODIS Dark Target Land algorithms (correlation coefficient R 2 is 0.764 and τ M = 0.95·τ A + 0.03) and the Deep Blue algorithm (correlation coefficient R 2 is 0.652 and τ M = 0.81·τ A + 0.04). The reasons of the retrieval error in AOD are found to be the various underlying surface reflectance. Therefore, the aerosol models and underlying surface reflectance are the dominant factors which influence the accuracy of MODIS retrieval performance. Generally the MODIS Land algorithm implements better than the Ocean algorithm for coastal sites

  11. Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

    Energy Technology Data Exchange (ETDEWEB)

    Larson, Vincent [Univ. of Wisconsin, Milwaukee, WI (United States)

    2016-11-25

    The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. The chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.

  12. Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning

    Science.gov (United States)

    Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.

    2017-12-01

    Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree

  13. Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.

    Science.gov (United States)

    Ignatov, Alexander; Minnis, Patrick; Loeb, Norman; Wielicki, Bruce; Miller, Walter; Sun-Mack, Sunny; Tanré, Didier; Remer, Lorraine; Laszlo, Istvan; Geier, Erika

    2005-04-01

    Understanding the impact of aerosols on the earth's radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth's Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product.This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved

  14. A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

    Science.gov (United States)

    Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

    2017-12-01

    In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

  15. Extended-range prediction trials using the global cloud/cloud-system resolving model NICAM and its new ocean-coupled version NICOCO

    Science.gov (United States)

    Miyakawa, Tomoki

    2017-04-01

    The global cloud/cloud-system resolving model NICAM and its new fully-coupled version NICOCO is run on one of the worlds top-tier supercomputers, the K computer. NICOCO couples the full-3D ocean component COCO of the general circulation model MIROC using a general-purpose coupler Jcup. We carried out multiple MJO simulations using NICAM and the new ocean-coupled version NICOCO to examine their extended-range MJO prediction skills and the impact of ocean coupling. NICAM performs excellently in terms of MJO prediction, maintaining a valid skill up to 27 days after the model is initialized (Miyakawa et al 2014). As is the case in most global models, ocean coupling frees the model from being anchored by the observed SST and allows the model climate to drift away further from reality compared to the atmospheric version of the model. Thus, it is important to evaluate the model bias, and in an initial value problem such as the seasonal extended-range prediction, it is essential to be able to distinguish the actual signal from the early transition of the model from the observed state to its own climatology. Since NICAM is a highly resource-demanding model, evaluation and tuning of the model climatology (order of years) is challenging. Here we focus on the initial 100 days to estimate the early drift of the model, and subsequently evaluate MJO prediction skills of NICOCO. Results show that in the initial 100 days, NICOCO forms a La-Nina like SST bias compared to observation, with a warmer Maritime Continent warm pool and a cooler equatorial central Pacific. The enhanced convection over the Maritime Continent associated with this bias project on to the real-time multi-variate MJO indices (RMM, Wheeler and Hendon 2004), and contaminates the MJO skill score. However, the bias does not appear to demolish the MJO signal severely. The model maintains a valid MJO prediction skill up to nearly 4 weeks when evaluated after linearly removing the early drift component estimated from

  16. Deriving Snow Cover Metrics for Alaska from MODIS

    Directory of Open Access Journals (Sweden)

    Chuck Lindsay

    2015-09-01

    Full Text Available Moderate Resolution Imaging Spectroradiometer (MODIS daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1 and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

  17. Toward Quantitative Estimation of the Effect of Aerosol Particles in the Global Climate Model and Cloud Resolving Model

    Science.gov (United States)

    Eskes, H.; Boersma, F.; Dirksen, R.; van der A, R.; Veefkind, P.; Levelt, P.; Brinksma, E.; van Roozendael, M.; de Smedt, I.; Gleason, J.

    2005-05-01

    Based on measurements of GOME on ESA ERS-2, SCIAMACHY on ESA-ENVISAT, and Ozone Monitoring Instrument (OMI) on the NASA EOS-Aura satellite there is now a unique 11-year dataset of global tropospheric nitrogen dioxide measurements from space. The retrieval approach consists of two steps. The first step is an application of the DOAS (Differential Optical Absorption Spectroscopy) approach which delivers the total absorption optical thickness along the light path (the slant column). For GOME and SCIAMACHY this is based on the DOAS implementation developed by BIRA/IASB. For OMI the DOAS implementation was developed in a collaboration between KNMI and NASA. The second retrieval step, developed at KNMI, estimates the tropospheric vertical column of NO2 based on the slant column, cloud fraction and cloud top height retrieval, stratospheric column estimates derived from a data assimilation approach and vertical profile estimates from space-time collocated profiles from the TM chemistry-transport model. The second step was applied with only minor modifications to all three instruments to generate a uniform 11-year data set. In our talk we will address the following topics: - A short summary of the retrieval approach and results - Comparisons with other retrievals - Comparisons with global and regional-scale models - OMI-SCIAMACHY and SCIAMACHY-GOME comparisons - Validation with independent measurements - Trend studies of NO2 for the past 11 years

  18. Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

    Science.gov (United States)

    Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

    2017-12-01

    Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being

  19. Learning in the cloud: a new challenge for a global teaching system in optics and photonics

    Science.gov (United States)

    Sultana, Razia; Christ, Andreas; Feisst, Markus; Curticapean, Dan

    2014-07-01

    Nowadays, it is assumed of many applications, companies and parts of the society to be always available online. However, according to [Times, Oct, 31 2011], 73% of the world population do not use the internet and thus aren't "online" at all. The most common reasons for not being "online" are expensive personal computer equipment and high costs for data connections, especially in developing countries that comprise most of the world's population (e.g. parts of Africa, Asia, Central and South America). However it seems that these countries are leap-frogging the "PC and landline" age and moving directly to the "mobile" age. Decreasing prices for smart phones with internet connectivity and PC-like operating systems make it more affordable for these parts of the world population to join the "always-online" community. Storing learning content in a way accessible to everyone, including mobile and smart phones, seems therefore to be beneficial. This way, learning content can be accessed by personal computers as well as by mobile and smart phones and thus be accessible for a big range of devices and users. A new trend in the Internet technologies is to go to "the cloud". This paper discusses the changes, challenges and risks of storing learning content in the "cloud". The experiences were gathered during the evaluation of the necessary changes in order to make our solutions and systems "cloud-ready".

  20. MODY diabetes - diagnostika a terapie

    OpenAIRE

    Verner, Miroslav

    2010-01-01

    This work summarized basic informations about different types of MODY diabetes. The keypoint is diagnostic, based on family history, followed by analysis of MODY diabetes types with suggestion of optimal therapy. In conclusion I suggest a possible solution of the underestimated diagnostic in MODY diabetes with an information poster in diabetological consulting rooms.

  1. Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

    Science.gov (United States)

    Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

    2006-01-01

    A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

  2. Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

    Science.gov (United States)

    Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

    2004-01-01

    Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

  3. Enhancement of marine cloud albedo via controlled sea spray injections: a global model study of the influence of emission rates, microphysics and transport

    Directory of Open Access Journals (Sweden)

    H. Korhonen

    2010-05-01

    Full Text Available Modification of cloud albedo by controlled emission of sea spray particles into the atmosphere has been suggested as a possible geoengineering option to slow global warming. Previous global studies have imposed changes in cloud drop concentration in low level clouds to explore the radiative and climatic effects. Here, we use a global aerosol transport model to quantify how an imposed flux of sea spray particles affects the natural aerosol processes, the particle size distribution, and concentrations of cloud drops. We assume that the proposed fleet of vessels emits sea spray particles with a wind speed-dependent flux into four regions of persistent stratocumulus cloud off the western coasts of continents. The model results show that fractional changes in cloud drop number concentration (CDNC vary substantially between the four regions because of differences in wind speed (which affects the spray efficiency of the vessels, transport and particle deposition rates, and because of variations in aerosols from natural and anthropogenic sources. Using spray emission rates comparable to those implied by previous studies we find that the predicted CDNC changes are very small (maximum 20% and in one of the four regions even negative. The weak or negative effect is because the added particles suppress the in-cloud supersaturation and prevent existing aerosol particles from forming cloud drops. A scenario with five times higher emissions (considerably higher than previously assumed increases CDNC on average by 45–163%, but median concentrations are still below the 375 cm−3 assumed in previous studies. An inadvertent effect of the spray emissions is that sulphur dioxide concentrations are suppressed by 1–2% in the seeded regions and sulphuric acid vapour by 64–68% due to chemical reactions on the additional salt particles. The impact of this suppression on existing aerosol is negligible in the model, but should be investigated further in

  4. MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere.

    Science.gov (United States)

    Warren B. Cohen; Thomas K. Maiersperger; David P. Turner; William D. Ritts; Dirk Pflugmacher; Robert E. Kennedy; Alan Kirschbaum; Steven W. Running; Marcos Costa; Stith T. Gower

    2006-01-01

    Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS...

  5. Estimating seasonal variations in cloud droplet number concentration over the boreal forest from satellite observations

    NARCIS (Netherlands)

    Janssen, R.; Ganzeveld, L.N.; Kabat, P.; Kulmala, M.; Nieminen, T.; Roebeling, R.A.

    2011-01-01

    Seasonal variations in cloud droplet number concentration (NCD) in low-level stratiform clouds over the boreal forest are estimated from MODIS observations of cloud optical and microphysical properties, using a sub-adiabatic cloud model to interpret vertical profiles of cloud properties. An

  6. Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

    Science.gov (United States)

    Xi, B.; Dong, X.; Wu, P.; Qiu, S.

    2017-12-01

    A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

  7. Operationalizing a Research Sensor: MODIS to VIIRS

    Science.gov (United States)

    Grant, K. D.; Miller, S. W.; Puschell, J.

    2012-12-01

    The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellite will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). MODIS data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. MODIS has flown on the EOS Terra satellite since 1999 and on the EOS Aqua satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of MODIS-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to MODIS for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager

  8. The impact of aerosol vertical distribution on aerosol optical depth retrieval using CALIPSO and MODIS data: Case study over dust and smoke regions

    Science.gov (United States)

    Wu, Yerong; de Graaf, Martin; Menenti, Massimo

    2017-08-01

    Global quantitative aerosol information has been derived from MODerate Resolution Imaging SpectroRadiometer (MODIS) observations for decades since early 2000 and widely used for air quality and climate change research. However, the operational MODIS Aerosol Optical Depth (AOD) products Collection 6 (C6) can still be biased, because of uncertainty in assumed aerosol optical properties and aerosol vertical distribution. This study investigates the impact of aerosol vertical distribution on the AOD retrieval. We developed a new algorithm by considering dynamic vertical profiles, which is an adaptation of MODIS C6 Dark Target (C6_DT) algorithm over land. The new algorithm makes use of the aerosol vertical profile extracted from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements to generate an accurate top of the atmosphere (TOA) reflectance for the AOD retrieval, where the profile is assumed to be a single layer and represented as a Gaussian function with the mean height as single variable. To test the impact, a comparison was made between MODIS DT and Aerosol Robotic Network (AERONET) AOD, over dust and smoke regions. The results show that the aerosol vertical distribution has a strong impact on the AOD retrieval. The assumed aerosol layers close to the ground can negatively bias the retrievals in C6_DT. Regarding the evaluated smoke and dust layers, the new algorithm can improve the retrieval by reducing the negative biases by 3-5%.

  9. El Chichon and 'mystery cloud' aerosols between 30 and 55 km Global observations from the SME visible spectrometer

    Science.gov (United States)

    Clancy, R. T.

    1986-01-01

    Visible limb radiances measured by the Solar Mesosphere Explorer (SME) are used to obtain volume scattering ratios for aerosol loading in the 30-55 km altitude range of the stratosphere. Global maps of these ratios are presented for the period January 1982 to August 1984. Significant aerosol scattering from the 'mystery cloud' and El Chichon aerosol layers are found above 30 km. A timescale of approximately 2 months between the appearance of the aerosol at 30.5 km and at 37.5 km is consistent with vertical transport of aerosol or vapor by eddy diffusion above 30 km. An anticorrelation exists between aerosol scattering and stratospheric temperatures. Periods of lower stratospheric temperatures may account for the formation of aerosol between 40 and 55 km altitude.

  10. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  11. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  12. The 3-D Tropical Convective Cloud Spectrum in AMIE Radar Observations and Global Climate Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Schumacher, Courtney [Texas A & M Univ., College Station, TX (United States). Dept. of Atmospheric Sciences

    2015-08-31

    During the three years of this grant performance, the PI and her research group have made a number of significant contributions towards determining properties of tropical deep convective clouds and how models depict and respond to the heating associated with tropical convective systems. The PI has also been an active ARM/ASR science team member, including playing a significant role in AMIE and GoAmazon2014/5. She served on the DOE ASR radar science steering committee and was a joint chair of the Mesoscale Convective Organization group under the Cloud Life Cycle working group. This grant has funded a number of graduate students, many of them women, and the PI and her group have presented their DOE-supported work at various universities and national meetings. The PI and her group participated in the AMIE (2011-12) and GoAmazon2014/5 (2014-15) DOE field deployments that occurred in the tropical Indian Ocean and Brazilian Amazon, respectively. AMIE observational results (DePasquale et al. 2014, Feng et al. 2014, Ahmed and Schumacher 2015) focus on the variation and possible importance of Kelvin waves in various phases of the Madden-Julian Oscillation (MJO), on the synergy of the different wavelength radars deployed on Addu Atoll, and on the importance of humidity thresholds in the tropics on stratiform rain production. Much of the PIs GoAmazon2014/5 results to date relate to overviews of the observations made during the field campaign (Martin et al. 2015, 2016; Fuentes et al. 2016), but also include the introduction of the descending arm and its link to ozone transport from the mid-troposphere to the surface (Gerken et al. 2016). Vertical motion and mass flux profiles from GoAmazon (Giangrande et al. 2016) also show interesting patterns between seasons and provide targets for model simulations. Results from TWP-ICE (Schumacher et al. 2015), which took place in Darwin, Australia in 2006 show that vertical velocity retrievals from the profilers provide structure to

  13. The global dispersion of microorganisms and pollutants in clouds of desert dust

    Science.gov (United States)

    Griffin, D. W.; Kellogg, C. A.; Garrison, V. H.; Kubilay, N.; Kocak, M.; Shinn, E.

    2003-12-01

    A current estimate of the quantity of dust that is transported some distance in Earth's atmosphere each year is approximately two billion metric tons. Whereas various research projects have been undertaken to understand this planetary process, little has been done to address public and ecosystem health issues. Our research group is currently investigating long-range transport of microorganisms associated with desert dust clouds at various points on the globe via the integration of remote sensing, modeling and microbiological assays. Using a suite of molecular biology techniques, we are identifying cultivable bacteria and fungi and enumerating total bacteria and viruses. Research results indicate that approximately 30% of the microorganisms found in Earth's atmosphere during `African dust events' are species of bacteria or fungi that have previously been identified as disease causing agents in terrestrial plants, trees, and animals. This presentation will cover historical research in this field and the implications of microbial and pollutant \\(metals, pesticides, etc.\\) transport to downwind ecosystems.

  14. The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

    Science.gov (United States)

    Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

    2016-12-01

    Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection

  15. MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

    Science.gov (United States)

    Ichoku, Charles; Kaufman, Yoram; Remer, Lorraine; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Kleidman, Richard; Lau, William K. M. (Technical Monitor)

    2001-01-01

    Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial

  16. Aerosol-Cloud Interactions in the South-East Atlantic: Knowledge Gaps, Planned Observations to Address Them, and Implications for Global Climate Change Modeling

    Science.gov (United States)

    Redemann, Jens; Wood, R.; Zuidema, P.; Haywood, J.; Luna, B.; Abel, S.

    2015-01-01

    Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical Stratocumulus (Sc) cloud decks in the world. The stratocumulus "climate radiators" are critical to the regional and global climate system. They interact with dense layers of BB aerosols that initially overlay the cloud deck, but later subside and are mixed into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects. As emphasized in the latest IPCC report, the global representation of these aerosol-cloud interaction processes in climate models is one of the largest uncertainty in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for global climate change scenarios. We discuss the current knowledge of aerosol and cloud property distributions based on satellite observations and sparse suborbital sampling, and describe planned field campaigns in the region. Specifically, we describe the scientific objectives and implementation of the following four synergistic, international research activities aimed at providing a process-level understanding of aerosol-cloud interactions over the SE Atlantic: 1) ORACLES (Observations of Aerosols above Clouds and their interactions), a five-year investigation between 2015 and 2019 with three Intensive Observation Periods (IOP), recently funded by the NASA Earth-Venture Suborbital Program, 2) CLARIFY-2016 (Cloud-Aerosol-Radiation Interactions and Forcing: Year 2016), a comprehensive observational and modeling programme funded by the UK's Natural Environment Research Council (NERC), and supported by the UK Met Office. 3) LASIC (Layered Atlantic Smoke Interactions with Clouds), a funded

  17. Estimating cloud field coverage using morphological analysis

    International Nuclear Information System (INIS)

    Bar-Or, Rotem Z; Koren, Ilan; Altaratz, Orit

    2010-01-01

    The apparent cloud-free atmosphere in the vicinity of clouds ('the twilight zone') is often affected by undetectable weak signature clouds and humidified aerosols. It is suggested here to classify the atmosphere into two classes: cloud fields, and cloud-free (away from a cloud field), while detectable clouds are included in the cloud field class as a subset. Since the definition of cloud fields is ambiguous, a robust cloud field masking algorithm is presented here, based on the cloud spatial distribution. The cloud field boundaries are calculated then on the basis of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask products and the total cloud field area is estimated for the Atlantic Ocean (50 deg. S-50 deg. N). The findings show that while the monthly averaged cloud fraction over the Atlantic Ocean during July is 53%, the cloud field fraction may reach 97%, suggesting that cloud field properties should be considered in climate studies. A comparison between aerosol optical depth values inside and outside cloud fields reveals differences in the retrieved radiative properties of aerosols depending on their location. The observed mean aerosol optical depth inside the cloud fields is more than 10% higher than outside it, indicating that such convenient cloud field masking may contribute to better estimations of aerosol direct and indirect forcing.

  18. Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data

    OpenAIRE

    Zhang, Hu; Jiao, Ziti; Dong, Yadong; Li, Xiaowen

    2015-01-01

    Bidirectional reflectance distribution function (BRDF) archetypes extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo product over the global Earth Observing System Land Validation Core Sites can be used to simplify BRDF models. The present study attempts to evaluate the representativeness of BRDF archetypes for surface reflectance anisotropy. Five-year forward-modeled MODIS multi-angular reflectance (MCD-ref) and aditional actual MODIS multi-angular observat...

  19. Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

    Science.gov (United States)

    Huemmrich, K. F.; Middleton, E.; Landis, D.; Black, T. A.; Barr, A. G.; McCaughey, J. H.; Hall, F.

    2009-12-01

    Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Optimal photosynthetic function is negatively affected by stress factors that cause down-regulation (i.e., reduced rate of photosynthesis). Present modeling approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from remote sensing, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses exhibited by photosynthetic pigments. This approach uses the Moderate-Resolution Spectroradiometer (MODIS) on Aqua and Terra to provide frequent, narrow-band measurements. The reflective ocean MODIS bands were used to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments in the xanthophyll cycle. MODIS PRI values were compared with LUE calculated from CO2 flux measured at four Canadian forest sites: A mature Douglas fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed forest site in Ontario, all part of the Canadian Carbon Program network. The relationships between LUE and MODIS PRI were different among forest types, with clear differences in the slopes of the relationships for conifer and deciduous forests. The MODIS based LUE measurements provide a more accurate estimation of observed LUE than the values calculated in the MODIS GPP model. This suggests the possibility of a GPP model that uses MODIS LUE instead of modeled LUE. This type of model may provide a useful contrast to existing

  20. Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

    Science.gov (United States)

    Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

    2013-12-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

  1. In-cloud oxalate formation in the global troposphere: A 3-D modeling study

    NARCIS (Netherlands)

    Myriokefalitakis, S.; Tsigaridis, K.; Mihalopoulos, N.; Sciare, J.; Nenes, A.; Kawamura, K.; Segers, A.; Kanakidou, M.

    2011-01-01

    Organic acids attract increasing attention as contributors to atmospheric acidity, secondary organic aerosol mass and aerosol hygroscopicity. Oxalic acid is globally the most abundant dicarboxylic acid, formed via chemical oxidation of gas-phase precursors in the aqueous phase of aerosols and

  2. Inferences of all-sky solar irradiance using Terra and Aqua MODIS satellite data

    DEFF Research Database (Denmark)

    Houborg, Rasmus Møller; Søgaard, Henrik; Emmerich, W.

    2007-01-01

    -sky solar irradiance components, which links a physically based clear-sky model with a neural network version of a rigorous radiative transfer model. The scheme exploits the improved cloud characterization and retrieval capabilities of the MODerate resolution Imaging Spectroradiometer (MODIS) onboard...... contrasting climates and cloud environments. Information on the atmospheric state was provided by MODIS data products and verifications against AErosol RObotic NETwork (AERONET) data demonstrated usefulness of MODIS aerosol optical depth and total precipitable water vapour retrievals for the delineation...... and become unusable above approximately 60° latitude. However, in principle, the scheme can be applied anywhere on the globe, and a synergistic use of MODIS and geostationary satellite datasets may be envisaged for some applications....

  3. CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

    Science.gov (United States)

    Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

    2004-02-01

    The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

  4. Undiagnosed MODY: Time for Action

    Science.gov (United States)

    Kleinberger, Jeffrey W.; Pollin, Toni I.

    2016-01-01

    Maturity-Onset Diabetes of the Young (MODY) is a monogenic form of diabetes that accounts for at least 1% of all cases of diabetes mellitus. MODY classically presents as non-insulin requiring diabetes in lean individuals younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95% of MODY cases in the U.S. are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals. PMID:26458381

  5. Unveiling aerosol-cloud interactions - Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

    Science.gov (United States)

    Neubauer, David; Christensen, Matthew W.; Poulsen, Caroline A.; Lohmann, Ulrike

    2017-11-01

    Aerosol-cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud-Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS-CERES (Moderate Resolution Imaging Spectroradiometer - Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol-liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR-CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR-CAPA or MODIS-CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR-CAPA vs. MODIS-CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS-CERES but positive for AATSR-CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well

  6. Hardware/Software Co-design of Global Cloud System Resolving

    Directory of Open Access Journals (Sweden)

    Michael Wehner

    2011-10-01

    Full Text Available We present an analysis of the performance aspects of an atmospheric general circulation model at the ultra-high resolution required to resolve individual cloud systems and describe alternative technological paths to realize the integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by the Courant stability criterion, the solution of the equations of motion dominate the calculation at these ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require a sustained computational rate of at least 28 Petaflop/s to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of next-generation ultra-scale systems. We demonstrate that hardware/software co-design of low-power embedded processor technology could be exploited to design a custom machine tailored to ultra-high resolution climate model specifications at relatively affordable cost and power considerations. A strawman machine design is presented consisting of in excess of 20 million processing elements that effectively exploits forthcoming many-core chips. The system pushes the limits of domain decomposition to increase explicit parallelism, and suggests that functional partitioning of sub-components of the climate code (much like the coarse-grained partitioning of computation between the atmospheric, ocean, land, and ice components of current coupled models may be necessary for future performance scaling.

  7. Role of updraft velocity in temporal variability of global cloud hydrometeor number

    Science.gov (United States)

    Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; Nenes, Athanasios

    2016-05-01

    Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

  8. Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

    Science.gov (United States)

    Li, Linlin; Vrieling, Anton; Skidmore, Andrew; Wang, Tiejun; Turak, Eren

    2018-04-01

    Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30 m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10 years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our method was not only effective for mapping permanent water fraction, but

  9. Dark Targets, Aerosols, Clouds and Toys

    Science.gov (United States)

    Remer, L. A.

    2015-12-01

    Today if you use the Thomson-Reuters Science Citations Index to search for "aerosol*", across all scientific disciplines and years, with no constraints, and you sort by number of citations, you will find a 2005 paper published in the Journal of the Atmospheric Sciences in the top 20. This is the "The MODIS Aerosol Algorithm, Products and Validation". Although I am the first author, there are in total 12 co-authors who each made a significant intellectual contribution to the paper or to the algorithm, products and validation described. This paper, that algorithm, those people lie at the heart of a lineage of scientists whose collaborations and linked individual pursuits have made a significant contribution to our understanding of radiative transfer and climate, of aerosol properties and the global aerosol system, of cloud physics and aerosol-cloud interaction, and how to measure these parameters and maximize the science that can be obtained from those measurements. The 'lineage' had its origins across the globe, from Soviet Russia to France, from the U.S. to Israel, from the Himalayas, the Sahel, the metropolises of Sao Paulo, Taipei, and the cities of east and south Asia. It came together in the 1990s and 2000s at the NASA Goddard Space Flight Center, using cultural diversity as a strength to form a common culture of scientific creativity that continues to this day. The original algorithm has spawned daughter algorithms that are being applied to new satellite and airborne sensors. The original MODIS products have been fundamental to analyses as diverse as air quality monitoring and aerosol-cloud forcing. AERONET, designed originally for the need of validation, is now its own thriving institution, and the lineage continues to push forward to provide new technology for the coming generations.

  10. Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

    Science.gov (United States)

    Takeshi Ise; Creighton M. Litton; Christian P. Giardina; Akihiko Ito

    2010-01-01

    Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long�]lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning...

  11. Clear-sky narrowband albedos derived from VIRS and MODIS

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Arduini, Robert F.

    2004-02-01

    The Clouds and Earth"s Radiant Energy System (CERES) project is using multispectral imagers, the Visible Infrared Scanner (VIRS) on the tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, operating since spring 2000, and Aqua, operating since summer 2002, to provide cloud and clear-sky properties at various wavelengths. This paper presents the preliminary results of an analysis of the CERES clear-sky reflectances to derive a set top-of-atmosphere clear sky albedo for 0.65, 0.86, 1.6, 2.13 μm, for all major surface types using the combined MODIS and VIRS datasets. The variability of snow albedo with surface type is examined using MODIS data. Snow albedo was found to depend on the vertical structure of the vegetation. At visible wavelengths, it is least for forested areas and greatest for smooth desert and tundra surfaces. At 1.6 and 2.1-μm, the snow albedos are relatively insensitive to the underlying surface because snow decreases the reflectance. Additional analyses using all of the MODIS results will provide albedo models that should be valuable for many remote sensing, simulation and radiation budget studies.

  12. A global lightning parameterization based on statistical relationships among environmental factors, aerosols, and convective clouds in the TRMM climatology

    Science.gov (United States)

    Stolz, Douglas C.; Rutledge, Steven A.; Pierce, Jeffrey R.; van den Heever, Susan C.

    2017-07-01

    The objective of this study is to determine the relative contributions of normalized convective available potential energy (NCAPE), cloud condensation nuclei (CCN) concentrations, warm cloud depth (WCD), vertical wind shear (SHEAR), and environmental relative humidity (RH) to the variability of lightning and radar reflectivity within convective features (CFs) observed by the Tropical Rainfall Measuring Mission (TRMM) satellite. Our approach incorporates multidimensional binned representations of observations of CFs and modeled thermodynamics, kinematics, and CCN as inputs to develop approximations for total lightning density (TLD) and the average height of 30 dBZ radar reflectivity (AVGHT30). The results suggest that TLD and AVGHT30 increase with increasing NCAPE, increasing CCN, decreasing WCD, increasing SHEAR, and decreasing RH. Multiple-linear approximations for lightning and radar quantities using the aforementioned predictors account for significant portions of the variance in the binned data set (R2 ≈ 0.69-0.81). The standardized weights attributed to CCN, NCAPE, and WCD are largest, the standardized weight of RH varies relative to other predictors, while the standardized weight for SHEAR is comparatively small. We investigate these statistical relationships for collections of CFs within various geographic areas and compare the aerosol (CCN) and thermodynamic (NCAPE and WCD) contributions to variations in the CF population in a partial sensitivity analysis based on multiple-linear regression approximations computed herein. A global lightning parameterization is developed; the average difference between predicted and observed TLD decreases from +21.6 to +11.6% when using a hybrid approach to combine separate approximations over continents and oceans, thus highlighting the need for regionally targeted investigations in the future.

  13. A cloud based model to facilitate software development uutsourcing to globally distributed locations

    OpenAIRE

    Hashmi, Sajid Ibrahim; Richardson, Ita

    2013-01-01

    peer-reviewed Outsourcing is an essential part of global software development and entails software development distributed across geographical borders. More specifically, it deals with software development teams dispersed across multiple geographical locations to carry out software development activities. By means of this business model, organizations expect to benefit from enhanced corporate value through advantages such as round the clock software development, availability of skills and ...

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

    Directory of Open Access Journals (Sweden)

    C. K. Carbajal Henken

    2014-11-01

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

  15. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

    Science.gov (United States)

    Norris, Peter M.; da Silva, Arlindo M.

    2018-01-01

    Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by

  16. Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

    Science.gov (United States)

    Norris, Peter M.; da Silva, Arlindo M.

    2016-01-01

    Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by

  17. Synergetic use of Aerosol Robotic Network (AERONET) and Moderate Image Spectrometer (MODIS)

    Science.gov (United States)

    Kaufman, Y.

    2004-01-01

    I shall describe several distinct modes in which AERONET data are used in conjunction with MODIS data to evaluate the global aerosol system and its impact on climate. These includes: 1) Evaluation of the aerosol diurnal cycle not available from MODIS, and the relationship between the aerosol properties derived from MODIS and the daily average of these properties; 2) Climatology of the aerosol size distribution and single scattering albedo. The climatology is used to formulate the assumptions used in the MODIS look up tables used in the inversion of MODIS data; 3) Measurement of the aerosol effect on irradiation of the surface, this is used in conjunction with the MODIS evaluation of the aerosol effect at the TOA; and 4) Assessment of the aerosol baseline on top off which the satellite data are used to find the amount of dust or anthropogenic aerosol.

  18. Testing the Two-Layer Model for Correcting Near Cloud Reflectance Enhancement Using LES SHDOM Simulated Radiances

    Science.gov (United States)

    Wen, Guoyong; Marshak, Alexander; Varnai, Tamas; Levy, Robert

    2016-01-01

    A transition zone exists between cloudy skies and clear sky; such that, clouds scatter solar radiation into clear-sky regions. From a satellite perspective, it appears that clouds enhance the radiation nearby. We seek a simple method to estimate this enhancement, since it is so computationally expensive to account for all three-dimensional (3-D) scattering processes. In previous studies, we developed a simple two-layer model (2LM) that estimated the radiation scattered via cloud-molecular interactions. Here we have developed a new model to account for cloud-surface interaction (CSI). We test the models by comparing to calculations provided by full 3-D radiative transfer simulations of realistic cloud scenes. For these scenes, the Moderate Resolution Imaging Spectroradiometer (MODIS)-like radiance fields were computed from the Spherical Harmonic Discrete Ordinate Method (SHDOM), based on a large number of cumulus fields simulated by the University of California, Los Angeles (UCLA) large eddy simulation (LES) model. We find that the original 2LM model that estimates cloud-air molecule interactions accounts for 64 of the total reflectance enhancement and the new model (2LM+CSI) that also includes cloud-surface interactions accounts for nearly 80. We discuss the possibility of accounting for cloud-aerosol radiative interactions in 3-D cloud-induced reflectance enhancement, which may explain the remaining 20 of enhancements. Because these are simple models, these corrections can be applied to global satellite observations (e.g., MODIS) and help to reduce biases in aerosol and other clear-sky retrievals.

  19. On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

    Science.gov (United States)

    Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

    2016-04-01

    Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

  20. Cloud Geospatial Analysis Tools for Global-Scale Comparisons of Population Models for Decision Making

    Science.gov (United States)

    Hancher, M.; Lieber, A.; Scott, L.

    2017-12-01

    The volume of satellite and other Earth data is growing rapidly. Combined with information about where people are, these data can inform decisions in a range of areas including food and water security, disease and disaster risk management, biodiversity, and climate adaptation. Google's platform for planetary-scale geospatial data analysis, Earth Engine, grants access to petabytes of continually updating Earth data, programming interfaces for analyzing the data without the need to download and manage it, and mechanisms for sharing the analyses and publishing results for data-driven decision making. In addition to data about the planet, data about the human planet - population, settlement and urban models - are now available for global scale analysis. The Earth Engine APIs enable these data to be joined, combined or visualized with economic or environmental indicators such as nighttime lights trends, global surface water, or climate projections, in the browser without the need to download anything. We will present our newly developed application intended to serve as a resource for government agencies, disaster response and public health programs, or other consumers of these data to quickly visualize the different population models, and compare them to ground truth tabular data to determine which model suits their immediate needs. Users can further tap into the power of Earth Engine and other Google technologies to perform a range of analysis from simple statistics in custom regions to more complex machine learning models. We will highlight case studies in which organizations around the world have used Earth Engine to combine population data with multiple other sources of data, such as water resources and roads data, over deep stacks of temporal imagery to model disease risk and accessibility to inform decisions.

  1. Heads in the clouds, feet in the sand: Multilateral policy coordination in global environmental issues

    International Nuclear Information System (INIS)

    Harrison, N.E.

    1994-01-01

    This is a study of how issues that can only be solved through cooperation (such as commons issues) reach the international agenda and how states then form policy on those issues. Extensive primary data are used in analyzing (1) accession of stratospheric ozone depletion and global climate change to the international agenda and (2) the policy formation of ten states on these issues. This study shows that commons issues reach the international agenda through the actions of intergovernmental organizations in defining the problem, and the political activities of a leader state (such as the US on ozone) or a state acting as a policy entrepreneur. In the extensive literature on international cooperation most studies emphasize the importance of system level variables. Adapting the two-level games approach to multilateral issues, this study argues that, as commons issues do not directly threaten the security of most states, state policy on such issues primarily reflects domestic political necessities. In effect, foreign and domestic policy on such issues become unified. Through analysis of secondary and primary data, including more than 30 interviews with representatives of both developed states (the US, Canada, the UK, and Japan) and developing states (Brazil, India, Algeria, Mexico, and Thailand), and the Soviet Union, this study shows how domestic factors influenced foreign policy decisions and actions. The study shows that states seem to be less interested in absolute or relative gains in international negotiations that in maximizing domestic political rewards from its choice of foreign policy. Finally, through study of the accession of the global climate change issue it is appears that knowledge may be politically derived. States required a open-quotes consensusclose quotes among the technical experts before initiating the international negotiations. Politics seems to have played a large part in forming the technical consensus and in communicating it to states

  2. Global albedo change and radiative cooling from anthropogenic land cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative kernels, and reanalysis

    Science.gov (United States)

    Ghimire, Bardan; Williams, Christopher A.; Masek, Jeffrey; Gao, Feng; Wang, Zhuosen; Schaaf, Crystal; He, Tao

    2014-12-01

    Widespread anthropogenic land cover change over the last five centuries has influenced the global climate system through both biogeochemical and biophysical processes. Models indicate that warming from carbon emissions associated with land cover conversion has been partially offset by cooling from elevated albedo, but considerable uncertainty remains partly because of uncertainty in model treatments of albedo. This study incorporates a new spatially and temporally explicit, land cover specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product) to provide more precise, observationally derived estimates of albedo impacts from anthropogenic land cover change with a complete range of data set specific uncertainty. The mean annual global albedo increase due to land cover change during 1700-2005 was estimated as 0.00106 ± 0.00008 (mean ± standard deviation), mainly driven by snow exposure due to land cover transitions from natural vegetation to agriculture. This translates to a top-of-atmosphere radiative cooling of -0.15 ± 0.1 W m-2 (mean ± standard deviation). Our estimate was in the middle of the Intergovernmental Panel on Climate Change Fifth Assessment Report range of -0.05 to -0.25 W m-2 and incorporates variability in albedo within land cover classes.