LANDSAT: US standard catalog, 1 February 1977 - 28 February 1977. [LANDSAT imagery for the month of February 1977

NASA Technical Reports Server (NTRS)

1977-01-01

The U.S. Standard Catalog lists U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as data acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

LANDSAT non-U.S. standard catalog, 1 January 1977 through 31 January 1977. [LANDSAT imagery January 1977

NASA Technical Reports Server (NTRS)

1977-01-01

The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which was processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover, and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

Brute Force Matching Between Camera Shots and Synthetic Images from Point Clouds

NASA Astrophysics Data System (ADS)

Boerner, R.; Kröhnert, M.

2016-06-01

3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.

Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

NASA Astrophysics Data System (ADS)

Kealy, John C.; Marenco, Franco; Marsham, John H.; Garcia-Carreras, Luis; Francis, Pete N.; Cooke, Michael C.; Hocking, James

2017-05-01

Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

LANDSAT 2 world standard catalog, 1-31 December 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 2 which was processed and input to the data files during the referenced period. Information on cloud cover and image quality is given for each scene. The microfilm roll and frame on which the scene may be found is presented.

LANDSAT 3 world standard catalog, 1-31 December 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 3 which was processed and input to the data files during the referenced period. Information on cloud cover and image quality is given for each scene. The microfilm roll and frame on which the scene may be found is given.

Dissipation of Titans north polar cloud at northern spring equinox

USGS Publications Warehouse

Le, Mouelic S.; Rannou, P.; Rodriguez, S.; Sotin, Christophe; Griffith, C.A.; Le, Corre L.; Barnes, J.W.; Brown, R.H.; Baines, K.H.; Buratti, B.J.; Clark, R.N.; Nicholson, P.D.; Tobie, G.

2012-01-01

Saturns Moon Titan has a thick atmosphere with a meteorological cycle. We report on the evolution of the giant cloud system covering its north pole using observations acquired by the Visual and Infrared Mapping Spectrometer onboard the Cassini spacecraft. A radiative transfer model in spherical geometry shows that the clouds are found at an altitude between 30 and 65 km. We also show that the polar cloud system vanished progressively as Titan approached equinox in August 2009, revealing at optical wavelengths the underlying sea known as Kraken Mare. This decrease of activity suggests that the north-polar downwelling has begun to shut off. Such a scenario is compared with the Titan global circulation model of Rannou et al. (2006), which predicts a decrease of cloud coverage in northern latitudes at the same period of time. ?? 2011 Elsevier Ltd. All rights reserved.

Seasonal Change in Titan's Cloud Activity Observed with IRTF/SpeX

NASA Astrophysics Data System (ADS)

Schaller, Emily L.; Brown, M. E.; Roe, H. G.

2006-09-01

We have acquired whole disk spectra of Titan on nineteen nights with IRTF/SpeX over a three-month period in the spring of 2006. The data encompass the spectral range of 0.8 to 2.4 microns at a resolution of 375. These disk-integrated spectra allow us to determine Titan's total fractional cloud coverage and altitudes of clouds present. We find that Titan had less than 0.15% fractional cloud coverage on all but one of the nineteen nights. The near lack of cloud activity in these spectra is in sharp contrast to nearly every spectrum taken from 1995-1999 with UKIRT by Griffith et al. (1998 & 2000) who found rapidly varying clouds covering 0.5% of Titan's disk. The differences in these two similar datasets indicate a striking seasonal change in the behavior of Titan's clouds. Observations of the latitudes, magnitudes, altitudes, and frequencies of Titan's clouds as Titan moves toward southern autumnal equinox in 2009 will help elucidate when and how Titan's methane hydrological cycle changes with season.

LANDSAT 2 world standard catalog, 1-31 January 1979

NASA Technical Reports Server (NTRS)

1979-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 2 which are processed and input to the data files during the referenced period. Information such as cloud cover and image quality is given for each scene. The microfilm roll and frame on which the scene may be found is also given.

LANDSAT 2 world standard catalog, 1-30 November 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 2 which was processed and input to the data files during the referenced period. Information such as cloud cover and image quality is given for each scene. The microfilm roll and frame on which the scene may be found is also given.

LANDSAT 2 world standard catalog, 1-31 October 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 2 which was processed and input to the data files during the referenced period. Information such as cloud cover and image quality is given for each scene. The microfilms roll and frame on which the scene may be found is also given.

Forest/non-forest stratification in Georgia with Landsat Thematic Mapper data

Treesearch

William H. Cooke

2000-01-01

Geographically accurate Forest Inventory and Analysis (FIA) data may be useful for training, classification, and accuracy assessment of Landsat Thematic Mapper (TM) data. Minimum expectation for maps derived from Landsat data is accurate discrimination of several land cover classes. Landsat TM costs have decreased dramatically, but acquiring cloud-free scenes at...

LANDSAT 2 world standard catalog, 1 Jan. - 30 Apr. 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 2 which has been processed and input to the data files during the referenced months. Data, such as cloud cover and image quality, are given for each scene. The microfilm roll and frame on which the scene may be found is also given.

The Influence of Cloud Field Uniformity on Observed Cloud Amount

NASA Astrophysics Data System (ADS)

Riley, E.; Kleiss, J.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.

2017-12-01

Two ground-based measurements of cloud amount include cloud fraction (CF) obtained from time series of zenith-pointing radar-lidar observations and fractional sky cover (FSC) acquired from a Total Sky Imager (TSI). In comparison with the radars and lidars, the TSI has a considerably larger field of view (FOV 100° vs. 0.2°) and therefore is expected to have a different sensitivity to inhomogeneity in a cloud field. Radiative transfer calculations based on cloud properties retrieved from narrow-FOV overhead cloud observations may differ from shortwave and longwave flux observations due to spatial variability in local cloud cover. This bias will impede radiative closure for sampling reasons rather than the accuracy of cloud microphysics retrievals or radiative transfer calculations. Furthermore, the comparison between observed and modeled cloud amount from large eddy simulations (LES) models may be affected by cloud field inhomogeneity. The main goal of our study is to estimate the anticipated impact of cloud field inhomogeneity on the level of agreement between CF and FSC. We focus on shallow cumulus clouds observed at the U.S. Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Our analysis identifies cloud field inhomogeneity using a novel metric that quantifies the spatial and temporal uniformity of FSC over 100-degree FOV TSI images. We demonstrate that (1) large differences between CF and FSC are partly attributable to increases in inhomogeneity and (2) using the uniformity metric can provide a meaningful assessment of uncertainties in observed cloud amount to aide in comparing ground-based measurements to radiative transfer or LES model outputs at SGP.

LANDSAT 3 world standard catalog, 6 March - 31 July 1978

NASA Technical Reports Server (NTRS)

1978-01-01

The World Standard Catalog lists imagery acquired by LANDSAT 3 which was processed and input to the data files during the referenced period. Information such as date of entry, cloud cover, and image quality is given for each scene. The microfilm roll and frame on which the scene may be found is also indicated.

BOREAS TF-8 NSA-OJP and SSA-OBS Ceilometer Data

NASA Technical Reports Server (NTRS)

Moore, Kathleen E.; Hall, Forrest G. (Editor); Huemmrich, Karl (Editor); Fitzjarrald, David R.

2000-01-01

The BOREAS TF-8 team used ceilometers to collect data on the fraction of the sky covered with clouds and the cloud height. Included with these data is the surface-based lifting condensation level, derived from temperature and humidity values acquired at the flux tower at the NSA-OJP site. Ceilo-meter data were collected at the NSA-OJP site in 1994 and at the NSA-OJP and SSA-OBS sites in 1996. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884).

Indirect and Semi-Direct Aerosol Campaign: The Impact of Arctic Aerosols on Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

McFarquhar, Greg; Ghan, Steven J.; Verlinde, J.

2011-02-01

A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the arctic boundary layer in the vicinity of Barrow, Alaska was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) sponsored by the Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric Science Programs. The primary aim of ISDAC was to examine indirect effects of aerosols on clouds that contain both liquid and ice water. The experiment utilized the ARM permanent observational facilities at the North Slope of Alaska (NSA) in Barrow. These include a cloud radar, a polarized micropulse lidar, and an atmosphericmore » emitted radiance interferometer as well as instruments specially deployed for ISDAC measuring aerosol, ice fog, precipitation and spectral shortwave radiation. The National Research Council of Canada Convair-580 flew 27 sorties during ISDAC, collecting data using an unprecedented 42 cloud and aerosol instruments for more than 100 hours on 12 different days. Data were obtained above, below and within single-layer stratus on 8 April and 26 April 2008. These data enable a process-oriented understanding of how aerosols affect the microphysical and radiative properties of arctic clouds influenced by different surface conditions. Observations acquired on a heavily polluted day, 19 April 2008, are enhancing this understanding. Data acquired in cirrus on transit flights between Fairbanks and Barrow are improving our understanding of the performance of cloud probes in ice. Ultimately the ISDAC data will be used to improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and to determine the extent to which long-term surface-based measurements can provide retrievals of aerosols, clouds, precipitation and radiative heating in the Arctic.« less

Methods for Cloud Cover Estimation

NASA Technical Reports Server (NTRS)

Glackin, D. L.; Huning, J. R.; Smith, J. H.; Logan, T. L.

1984-01-01

Several methods for cloud cover estimation are described relevant to assessing the performance of a ground-based network of solar observatories. The methods rely on ground and satellite data sources and provide meteorological or climatological information. One means of acquiring long-term observations of solar oscillations is the establishment of a ground-based network of solar observatories. Criteria for station site selection are: gross cloudiness, accurate transparency information, and seeing. Alternative methods for computing this duty cycle are discussed. The cycle, or alternatively a time history of solar visibility from the network, can then be input to a model to determine the effect of duty cycle on derived solar seismology parameters. Cloudiness from space is studied to examine various means by which the duty cycle might be computed. Cloudiness, and to some extent transparency, can potentially be estimated from satellite data.

Titan's Methane Hydrological Cycle: Detection of Seasonal Change

NASA Astrophysics Data System (ADS)

Schaller, E. L.; Brown, M. E.; Roe, H. G.

2007-08-01

We have acquired whole disk spectra of Titan on over 100 nights with IRTF/SpeX during the 2006-2007 Titan season. The data encompass the spectral range of 0.8 to 2.4 microns at a resolution of 375. These disk- integrated spectra allow us to determine Titan's total fractional cloud coverage and altitudes of clouds present. The near lack of tropospheric cloud activity in these spectra is in sharp contrast to nearly every spectrum taken from 1995-1999 with UKIRT by Griffith et al. (1998 & 2000) who found rapidly varying clouds covering 0.5-9% of Titan's disk. The differences in these two similar datasets indicate a striking seasonal change in the behavior of Titan's clouds. Adaptive optics observations from Keck and Gemini also show markedly decreased cloud activity in the late southern summer era compared with the period surrounding southern summer solstice (October 2002). Observations of the latitudes, magnitudes, altitudes, and frequencies of Titan's clouds as Titan moves toward southern autumnal equinox in 2009 will help elucidate when and how Titan's methane hydrological cycle changes with season.

UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery

USGS Publications Warehouse

Sturdivant, Emily; Lentz, Erika; Thieler, E. Robert; Farris, Amy; Weber, Kathryn; Remsen, David P.; Miner, Simon; Henderson, Rachel

2017-01-01

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

Estimating Cloud Cover

ERIC Educational Resources Information Center

Moseley, Christine

2007-01-01

The purpose of this activity was to help students understand the percentage of cloud cover and make more accurate cloud cover observations. Students estimated the percentage of cloud cover represented by simulated clouds and assigned a cloud cover classification to those simulations. (Contains 2 notes and 3 tables.)

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE PAGES

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

2018-04-13

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

An A-Train Climatology of Extratropical Cyclone Clouds

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike

2016-01-01

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

The 2011 Eco3D Flight Campaign: Vegetation Structure and Biomass Estimation from Simultaneous SAR, Lidar and Radiometer Measurements

NASA Technical Reports Server (NTRS)

Fatoyinbo, Temilola; Rincon, Rafael; Harding, David; Gatebe, Charles; Ranson, Kenneth Jon; Sun, Guoqing; Dabney, Phillip; Roman, Miguel

2012-01-01

The Eco3D campaign was conducted in the Summer of 2011. As part of the campaign three unique and innovative NASA Goddard Space Flight Center airborne sensors were flown simultaneously: The Digital Beamforming Synthetic Aperture Radar (DBSAR), the Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) and the Cloud Absorption Radiometer (CAR). The campaign covered sites from Quebec to Southern Florida and thereby acquired data over forests ranging from Boreal to tropical wetlands. This paper describes the instruments and sites covered and presents the first images resulting from the campaign.

Gravity Waves Ripple over Marine Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

2004-01-01

In this natural-color image from the Multi-angle Imaging SpectroRadiometer (MISR), a fingerprint-like gravity wave feature occurs over a deck of marine stratocumulus clouds. Similar to the ripples that occur when a pebble is thrown into a still pond, such 'gravity waves' sometimes appear when the relatively stable and stratified air masses associated with stratocumulus cloud layers are disturbed by a vertical trigger from the underlying terrain, or by a thunderstorm updraft or some other vertical wind shear. The stratocumulus cellular clouds that underlie the wave feature are associated with sinking air that is strongly cooled at the level of the cloud-tops -- such clouds are common over mid-latitude oceans when the air is unperturbed by cyclonic or frontal activity. This image is centered over the Indian Ocean (at about 38.9o South, 80.6o East), and was acquired on October 29, 2003.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 20545. The image covers an area of 245 kilometers x 378 kilometers, and uses data from blocks 121 to 122 within World Reference System-2 path 134.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

LANDSAT: Non-US standard catalog 1-31 December 1976. [LANDSAT imagery for December 1976

NASA Technical Reports Server (NTRS)

1976-01-01

The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date required, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found are also given.

Tropical Cyclone Monty Strikes Western Australia

NASA Technical Reports Server (NTRS)

2004-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) acquired these natural color images and cloud top height measurements for Monty before and after the storm made landfall over the remote Pilbara region of Western Australia, on February 29 and March 2, 2004 (shown as the left and right-hand image sets, respectively). On February 29, Monty was upgraded to category 4 cyclone status. After traveling inland about 300 kilometers to the south, the cyclonic circulation had decayed considerably, although category 3 force winds were reported on the ground. Some parts of the drought-affected Pilbara region received more than 300 millimeters of rainfall, and serious and extensive flooding has occurred.

The natural color images cover much of the same area, although the right-hand panels are offset slightly to the east. Automated stereoscopic processing of data from multiple MISR cameras was utilized to produce the cloud-top height fields. The distinctive spatial patterns of the clouds provide the necessary contrast to enable automated feature matching between images acquired at different view angles. The height retrievals are at this stage uncorrected for the effects of the high winds associated with cyclone rotation. Areas where heights could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbits 22335 and 22364. The panels cover an area of about 380 kilometers x 985 kilometers, and utilize data from blocks 105 to 111 within World Reference System-2 paths 115 and 113.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Coupled retrieval of water cloud and above-cloud aerosol properties using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F. C.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Davis, A. B.; Jovanovic, V. M.; Brian, C.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (*denotes polarimetric bands). In sweep mode, georectified images cover an area of 80-100 km (along track) by 10-25 km (across track) between ±66° off nadir, with a map-projected spatial resolution of 25 meters. An efficient and flexible retrieval algorithm has been developed using AirMSPI polarimetric bands for simultaneous retrieval of cloud and above-cloud aerosol microphysical properties. We design a three-step retrieval approach, namely 1) estimating effective droplet size distribution using polarimetric cloudbow observations and using it as initial guess for Step 2; 2) combining water cloud and aerosol above cloud retrieval by fitting polarimetric signals at all scattering angles (e.g. from 80° to 180°); and 3) constructing a lookup table of radiance for a set of cloud optical depth grids using aerosol and cloud information retrieved from Step 2 and then estimating pixel-scale cloud optical depth based on 1D radiative transfer (RT) theory by fitting the AirMSPI radiance. Retrieval uncertainty is formulated by accounting for instrumental errors and constraints imposed on spectral variations of aerosol and cloud droplet optical properties. As the forward RT model, a hybrid approach is developed to combine the computational strengths of Markov-chain and adding-doubling methods to model polarized RT in a coupled aerosol, Rayleigh and cloud system. Our retrieval approach is tested using 134 AirMSPI datasets acquired during NASA ORACLES field campaign in 09/2016, with low to high aerosol loadings. For validation, the retrieved aerosol optical depths and cloud-top heights are compared to coincident High Spectral Resolution Lidar-2 (HSRL-2) data, and the droplet size parameters including effective radius and effective variance and cloud optical thickness are compared to coincident Research Scanning Polarimeter (RSP) data.

Heat Capacity Mapping Mission (HCMM): Interpretation of imagery over Canada

NASA Technical Reports Server (NTRS)

Cihlar, J. (Principal Investigator); Dixon, R. G.

1981-01-01

Visual analysis of HCMM images acquired over two sites in Canada and supporting aircraft and ground data obtained at a smaller subsite in Alberta show that nightime surface temperature distribution is primarily related to the near-surface air temperature; the effects of topography, wind, and land cover were low or indirect through air temperature. Surface cover and large altitudinal differences were important parameters influencing daytime apparent temperature values. A quantitative analysis of the relationship between the antecedent precipitation index and the satellite thermal IR measurements did not yield statistically significant correlation coefficients, but the correlations had a definite temporal trend which could be related to the increasing uniformity of vegetation cover. The large pixel size (resulting in a mixture of cover types and soil/canopy temperatures measured by the satellite) and high cloud cover frequency found in images covering both Canadian sites and northern U.S. were considered the main deficiencies of the thermal satellite data.

Multidecadal Changes in Near-Global Cloud Cover and Estimated Cloud Cover Radiative Forcing

NASA Technical Reports Server (NTRS)

Norris, Joel

2005-01-01

The first paper was Multidecadal changes in near-global cloud cover and estimated cloud cover radiative forcing, by J. R. Norris (2005, J. Geophys. Res. - Atmos., 110, D08206, doi: lO.l029/2004JD005600). This study examined variability in zonal mean surface-observed upper-level (combined midlevel and high-level) and low-level cloud cover over land during 1971-1 996 and over ocean during 1952-1997. These data were averaged from individual synoptic reports in the Extended Edited Cloud Report Archive (EECRA). Although substantial interdecadal variability is present in the time series, long-term decreases in upper-level cloud cover occur over land and ocean at low and middle latitudes in both hemispheres. Near-global upper-level cloud cover declined by 1.5%-sky-cover over land between 1971 and 1996 and by 1.3%-sky-cover over ocean between 1952 and 1997. Consistency between EECRA upper-level cloud cover anomalies and those from the International Satellite Cloud Climatology Project (ISCCP) during 1984-1 997 suggests the surface-observed trends are real. The reduction in surface-observed upper-level cloud cover between the 1980s and 1990s is also consistent with the decadal increase in all-sky outgoing longwave radiation reported by the Earth Radiation Budget Satellite (EMS). Discrepancies occur between time series of EECRA and ISCCP low-level cloud cover due to identified and probable artifacts in satellite and surface cloud data. Radiative effects of surface-observed cloud cover anomalies, called "cloud cover radiative forcing (CCRF) anomalies," are estimated based on a linear relationship to climatological cloud radiative forcing per unit cloud cover. Zonal mean estimated longwave CCRF has decreased over most of the globe. Estimated shortwave CCRF has become slightly stronger over northern midlatitude oceans and slightly weaker over northern midlatitude land areas. A long-term decline in the magnitude of estimated shortwave CCRF occurs over low-latitude land and ocean, but comparison with EMS all-sky reflected shortwave radiation during 1985-1997 suggests this decrease may be underestimated.

Distinguishing Clouds from Ice over the East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

As a consequence of its capability to retrieve cloud-top elevations, stereoscopic observations from the Multi-angle Imaging SpectroRadiometer (MISR) can discriminate clouds from snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in these views from data acquired on May 28, 2002.

The left-hand image is a natural color view from MISR's nadir camera. On the right is a height field retrieved using automated computer processing of data from multiple MISR cameras. Although both clouds and ice appear white in the natural color view, the stereoscopic retrievals are able to identify elevated clouds based on the geometric parallax which results when they are observed from different angles. Owing to their elevation above sea level, clouds are mapped as green and yellow areas, whereas land, sea ice, and very low clouds appear blue and purple. Purple, in particular, denotes elevations very close to sea level. The island of Novaya Sibir is located in the lower left of the images. It can be identified in the natural color view as the dark area surrounded by an expanse of fast ice. In the stereo map the island appears as a blue region indicating its elevation of less than 100 meters above sea level. Areas where the automated stereo processing failed due to lack of sufficient spatial contrast are shown in dark gray. The northern edge of the Siberian mainland can be found at the very bottom of the panels, and is located a little over 250 kilometers south of Novaya Sibir. Pack ice containing numerous fragmented ice floes surrounds the fast ice, and narrow areas of open ocean are visible.

The East Siberian Sea is part of the Arctic Ocean and is ice-covered most of the year. The New Siberian Islands are almost always covered by snow and ice, and tundra vegetation is very scant. Despite continuous sunlight from the end of April until the middle of August, the ice between the island and the mainland typically remains until August or September.

The Multi-angle Imaging SpectroRadiometer views almost the entire Earth every 9 days. These images were acquired during Terra orbit 12986 and cover an area of about 380 kilometers x 1117 kilometers. They utilize data from blocks 24 to 32 within World Reference System-2 path 117.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

The Citizen CATE Experiment: Techniques to Determine Totality Coverage and Clouded Data Removal.

NASA Astrophysics Data System (ADS)

McKay, Myles A.; Ursache, Andrei; Penn, Matthew; Citizen CATE Experiment 2017 Team

2018-01-01

August 21, 2017, the Citizen Continental-America Telescopic Eclipse(CATE) Experiment observed the 2017 total solar eclipse using a network of 68 identical telescopes and camera systems along the path of totality. The result from the observation was over 90% of all sites collected totality data on the day of the eclipse. Since the volunteers had to remove the solar filter manually, there is an uncertainty between the time of totality and data acquired during totality. Some sites also experienced cloudy weather which obscured the eclipse in some of the exposures but had small breaks in the clouds during the observation, collecting clear totality data. Before we can process and analyze the eclipse data, we must carefully determine which frames cover the time of totality for each site and remove exposures with clouds blocking the FOV. In this poster, we will discuss the techniques we used to determine the extent of totality from each location using the logged GPS data and the removal of totality exposure with clouds.

Cloud cover models derived from satellite radiation measurements

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1979-01-01

Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

Rise in the frequency of cloud cover in LANDSAT data for the period 1973 to 1981. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Mendonca, F. J.; Neto, G. C.

1983-01-01

Percentages of cloud cover in LANDSAT imagery were used to calculate the cloud cover monthly average statistic for each LANDSAT scene in Brazil, during the period of 1973 to 1981. The average monthly cloud cover and the monthly minimum cloud cover were also calculated for the regions of north, northeast, central west, southeast and south, separately.

Typhoon Sinlaku

NASA Technical Reports Server (NTRS)

2002-01-01

One of the more destructive cyclones to emerge from the northern hemisphere 2002 summer storm season was Typhoon Sinlaku. Several attributes of this storm event are portrayed in these data products from the Multi-angle Imaging SpectroRadiometer. The images were acquired on September 5, when the western portion of the storm was situated over the Okinawan island chain. Over the next few days it moved west-northwest, sweeping over Taiwan before making landfall along China's Zhejian province on the 7th. The typhoon forced hundreds of thousands of people from their homes, caused major power outages, and at least 26 people were reported dead or missing before the storm weakened as it moved inland.

While the nature and formation of individual storm events is relatively well understood, the influence of clouds on climate is difficult to assess due to the variable nature of cloud cover at various altitudes. MISR's data products are designed to help understand these influences. Typhoon Sinlaku is shown at left as a natural-color view observed by MISR's vertical-viewing (nadir)camera. The center panel shows the cloud-top height field derived using automated stereoscopic processing of data from multiple MISR cameras. Relative height variations, such as the clearing within the storm's eye, are well represented. Areas where heights could not be retrieved are shown in dark gray.

Clouds have a significant influence on the global radiation balance of the Earth's atmosphere, and the improvement of climate models requires more accurate information on how different types of clouds influence Earth's energy budget. One measure of this influence is albedo, which is the amount of sunlight reflected back to space divided by amount of incident sunlight. Bright objects have high albedo. Retrieved local albedo values for Typhoon Sinlaku are shown at right. Generation of this product is dependent on observed cloud radiances as a function of viewing angle and the cloud height field. Over the short distances (2.2 kilometers) that MISR's local albedo product is generated, values can be greater than 1.0 due to the contributions from the sides of the clouds. Areas where albedo could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and views almost the entire globe every 9 days. This image is a portion of the data acquired during Terra orbit 14442, and covers an area of about 380 kilometers x 1408 kilometers. It utilizes data from blocks 65 to 74 within World Reference System-2 path 113.

Observations of temporal change of nighttime cloud cover from Himawari 8 and ground-based sky camera over Chiba, Japan

NASA Astrophysics Data System (ADS)

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

2017-12-01

Detection of nighttime cloud from Himawari 8 is implemented using the difference of digital numbers from bands 13 (10.4µm) and 7 (3.9µm). The digital number difference of -1.39x104 can be used as a threshold to separate clouds from clear sky conditions. To look at observations from the ground over Chiba, a digital camera (Canon Powershot A2300) is used to take images of the sky every 5 minutes at an exposure time of 5s at the Center for Environmental Remote Sensing, Chiba University. From these images, cloud cover values are obtained using threshold algorithm (Gacal, et al, 2016). Ten minute nighttime cloud cover values from these two datasets are compared and analyzed from 29 May to 05 June 2017 (20:00-03:00 JST). When compared with lidar data, the camera can detect thick high level clouds up to 10km. The results show that during clear sky conditions (02-03 June), both camera and satellite cloud cover values show 0% cloud cover. During cloudy conditions (05-06 June), the camera shows almost 100% cloud cover while satellite cloud cover values range from 60 to 100%. These low values can be attributed to the presence of low-level thin clouds ( 2km above the ground) as observed from National Institute for Environmental Studies lidar located inside Chiba University. This difference of cloud cover values shows that the camera can produce accurate cloud cover values of low level clouds that are sometimes not detected by satellites. The opposite occurs when high level clouds are present (01-02 June). Derived satellite cloud cover shows almost 100% during the whole night while ground-based camera shows cloud cover values that range from 10 to 100% during the same time interval. The fluctuating values can be attributed to the presence of thin clouds located at around 6km from the ground and the presence of low level clouds ( 1km). Since the camera relies on the reflected city lights, it is possible that the high level thin clouds are not observed by the camera but is observed by the satellite. Also, this condition constitutes layers of clouds that are not observed by each camera. The results of this study show that one instrument can be used to correct each other to provide better cloud cover values. These corrections is dependent on the height and thickness of the clouds. No correction is necessary when the sky is clear.

New Image of Kilauea's Lava Flows taken by NASA Spacecraft

NASA Image and Video Library

2018-05-24

Hawaii's Kilauea's eruption, which began three weeks ago, has produced new lava flows that reached the ocean. The combination of molten lava and sea water produced clouds of noxious gases, such as hydrogen sulfide. In this image from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer instrument on NASA's Terra satellite, vegetation is displayed in red, clouds are white and the hot lava flows, detected by ASTER's thermal infrared channels, are overlaid in yellow. The image was acquired May 22, 2018, covers an area of 20.3 by 20.9 miles (32.6 by 33.6 kilometers), and is located at 19.6 degrees north, 154.9 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA22459

Study and Application on Cloud Covered Rate for Agroclimatical Distribution Using In Guangxi Based on Modis Data

NASA Astrophysics Data System (ADS)

Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua

Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.

Evolving land cover classification algorithms for multispectral and multitemporal imagery

NASA Astrophysics Data System (ADS)

Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.

2002-01-01

The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.

The beta distribution: A statistical model for world cloud cover

NASA Technical Reports Server (NTRS)

Falls, L. W.

1973-01-01

Much work has been performed in developing empirical global cloud cover models. This investigation was made to determine an underlying theoretical statistical distribution to represent worldwide cloud cover. The beta distribution with probability density function is given to represent the variability of this random variable. It is shown that the beta distribution possesses the versatile statistical characteristics necessary to assume the wide variety of shapes exhibited by cloud cover. A total of 160 representative empirical cloud cover distributions were investigated and the conclusion was reached that this study provides sufficient statical evidence to accept the beta probability distribution as the underlying model for world cloud cover.

Monthly and Seasonal Cloud Cover Patterns at the Manila Observatory (14.64°N, 121.08°E)

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Lagrosas, N.; Caballa, K.

2014-12-01

A ground based sky imaging system was developed at the Manila Observatory in 2012 to measure cloud occurrence and to analyse seasonal variation of cloud cover over Metro Manila. Ground-based cloud occurrence measurements provide more reliable results compared to satellite observations. Also, cloud occurrence data aid in the analysis of radiation budget in the atmosphere. In this study, a GoPro Hero 2 with almost 180o field of view is employed to take pictures of the atmosphere. These pictures are taken continuously, having a temporal resolution of 1min. Atmospheric images from April 2012 to June 2013 (excluding the months of September, October, and November 2012) were processed to determine cloud cover. Cloud cover in an image is measured as the ratio of the number of pixels with clouds present in them to the total number of pixels. The cloud cover values were then averaged over each month to know its monthly and seasonal variation. In Metro Manila, the dry season occurs in the months of November to May of the next year, while the wet season occurs in the months of June to October of the same year. Fig 1 shows the measured monthly variation of cloud cover. No data was collected during the months of September (wherein the camera was used for the 7SEAS field campaign), October, and November 2012 (due to maintenance and repairs). Results show that there is high cloud cover during the wet season months (80% on average) while there is low cloud cover during the dry season months (62% on average). The lowest average cloud cover for a wet season month occurred in June 2012 (73%) while the highest average cloud cover for a wet season month occurred in June 2013 (86%). The variations in cloud cover average in this season is relatively smaller compared to that of the dry season wherein the lowest average cloud cover in a month was during April 2012 (38%) while the highest average cloud cover in a month was during January 2013 (77%); minimum and maximum averages being 39% apart. During the wet season, the cloud occurrence is mainly due to tropical storms, Southwest Monsoon, and local convection processes. In the dry season, less cloud is formed because of cold dry air from Northeast Monsoon (December to February) and generally dry and hot weather (March to May). Regular data collection has been implemented for further long term data analysis.

SatCam: A mobile application for coordinated ground/satellite observation of clouds and validation of satellite-derived cloud mask products.

NASA Astrophysics Data System (ADS)

Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.

2011-12-01

SatCam is an application for iOS devices that allows users to collect observations of local cloud and surface conditions in coordination with an overpass of the Terra, Aqua, or NPP satellites. SatCam allows users to acquire images of sky conditions and ground conditions at their location anywhere in the world using the built-in iPhone or iPod Touch camera at the same time that the satellite is passing overhead and viewing their location. Immediately after the sky and ground observations are acquired, the application asks the user to rate the level of cloudiness in the sky (Completely Clear, Mostly Clear, Partly Cloudy, Overcast). For the ground observation, the user selects their assessment of the surface conditions (Urban, Green Vegetation, Brown Vegetation, Desert, Snow, Water). The sky condition and surface condition selections are stored along with the date, time, and geographic location for the images, and the images are uploaded to a central server. When the MODIS (Terra and Aqua) or VIIRS (NPP) imagery acquired over the user location becomes available, a MODIS or VIIRS true color image centered at the user's location is delivered back to the SatCam application on the user's iOS device. SSEC also proposes to develop a community driven SatCam website where users can share their observations and assessments of satellite cloud products in a collaborative environment. SSEC is developing a server side data analysis system to ingest the SatCam user observations, apply quality control, analyze the sky images for cloud cover, and collocate the observations with MODIS and VIIRS satellite products (e.g., cloud mask). For each observation that is collocated with a satellite observation, the server will determine whether the user scored a "hit", meaning their sky observation and sky assessment matched the automated cloud mask obtained from the satellite observation. The hit rate will be an objective assessment of the accuracy of the user's sky observations. Users with high hit rates will be identified automatically and their observations will be used globally to evaluate the performance of the MODIS cloud mask algorithm for Terra and Aqua and the VIIRS cloud mask algorithm for NPP. The user's assessment of the ground conditions will also be used to evaluate the cloud mask accuracy in selecting the correct surface type at the user's location, which is an important element in the decision path used internally by the cloud mask algorithm. This presentation will describe the SatCam application, how it is used, and show examples of SatCam observations.

Roughness Estimation from Point Clouds - A Comparison of Terrestrial Laser Scanning and Image Matching by Unmanned Aerial Vehicle Acquisitions

NASA Astrophysics Data System (ADS)

Rutzinger, Martin; Bremer, Magnus; Ragg, Hansjörg

2013-04-01

Recently, terrestrial laser scanning (TLS) and matching of images acquired by unmanned arial vehicles (UAV) are operationally used for 3D geodata acquisition in Geoscience applications. However, the two systems cover different application domains in terms of acquisition conditions and data properties i.e. accuracy and line of sight. In this study we investigate the major differences between the two platforms for terrain roughness estimation. Terrain roughness is an important input for various applications such as morphometry studies, geomorphologic mapping, and natural process modeling (e.g. rockfall, avalanche, and hydraulic modeling). Data has been collected simultaneously by TLS using an Optech ILRIS3D and a rotary UAV using an octocopter from twins.nrn for a 900 m² test site located in a riverbed in Tyrol, Austria (Judenbach, Mieming). The TLS point cloud has been acquired from three scan positions. These have been registered using iterative closest point algorithm and a target-based referencing approach. For registration geometric targets (spheres) with a diameter of 20 cm were used. These targets were measured with dGPS for absolute georeferencing. The TLS point cloud has an average point density of 19,000 pts/m², which represents a point spacing of about 5 mm. 15 images where acquired by UAV in a height of 20 m using a calibrated camera with focal length of 18.3 mm. A 3D point cloud containing RGB attributes was derived using APERO/MICMAC software, by a direct georeferencing approach based on the aircraft IMU data. The point cloud is finally co-registered with the TLS data to guarantee an optimal preparation in order to perform the analysis. The UAV point cloud has an average point density of 17,500 pts/m², which represents a point spacing of 7.5 mm. After registration and georeferencing the level of detail of roughness representation in both point clouds have been compared considering elevation differences, roughness and representation of different grain sizes. UAV closes the gap between aerial and terrestrial surveys in terms of resolution and acquisition flexibility. This is also true for the data accuracy. Considering these data collection and data quality properties of both systems they have their merit on its own in terms of scale, data quality, data collection speed and application.

A portable low-cost 3D point cloud acquiring method based on structure light

NASA Astrophysics Data System (ADS)

Gui, Li; Zheng, Shunyi; Huang, Xia; Zhao, Like; Ma, Hao; Ge, Chao; Tang, Qiuxia

2018-03-01

A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.

ASTER Images the Island of Hawaii

NASA Image and Video Library

2000-04-26

These images of the Island of Hawaii were acquired on March 19, 2000 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet. Data are shown from the short wavelength and thermal infrared spectral regions, illustrating how different and complementary information is contained in different parts of the spectrum. Left image: This false-color image covers an area 60 kilometers (37 miles) wide and 120 kilometers (75 miles) long in three bands of the short wavelength infrared region. While, much of the island was covered in clouds, the dominant central Mauna Loa volcano, rising to an altitude of 4115 meters (13,500 feet), is cloud-free. Lava flows can be seen radiating from the central crater in green and black tones. As they reach lower elevations, the flows become covered with vegetation, and their image color changes to yellow and orange. Mauna Kea volcano to the north of Mauna Loa has a thin cloud-cover, producing a bluish tone on the image. The ocean in the lower right appears brown due to the color processing. Right image: This image is a false-color composite of three thermal infrared bands. The brightness of the colors is proportional to the temperature, and the hues display differences in rock composition. Clouds are black, because they are the coldest objects in the scene. The ocean and thick vegetation appear dark green because they are colder than bare rock surfaces, and have no thermal spectral features. Lava flows are shades of magenta, green, pink and yellow, reflecting chemical changes due to weathering and relative age differences. http://photojournal.jpl.nasa.gov/catalog/PIA02604

A cloud cover model based on satellite data

NASA Technical Reports Server (NTRS)

Somerville, P. N.; Bean, S. J.

1980-01-01

A model for worldwide cloud cover using a satellite data set containing infrared radiation measurements is proposed. The satellite data set containing day IR, night IR and incoming and absorbed solar radiation measurements on a 2.5 degree latitude-longitude grid covering a 45 month period was converted to estimates of cloud cover. The global area was then classified into homogeneous cloud cover regions for each of the four seasons. It is noted that the developed maps can be of use to the practicing climatologist who can obtain a considerable amount of cloud cover information without recourse to large volumes of data.

Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Gatebe, Charles K.; King, Michael D.

2016-01-01

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

NASA Technical Reports Server (NTRS)

Li, Jing

2011-01-01

This poster is to present the development of a cellphone sensor network for extended chemical sensing. The nanosensors using carbon nanotubes and other nanostructures are used with low power and high sensitivity for chemical detection. The sensing module has been miniaturized to a small size that can plug in or clip on to a smartphone. The chemical information detected by the nanosensors are acquired by a smartphone and transmitted via cellphone 3g or WiFi network to an internet server. The whole integrated sensing system from sensor to cellphone to a cloud will provide an extended chemical sensing network that can cover nation wide and even cover global wide for early warning of a hazardous event.

Assessment of the NASA-USGS Global Land Survey (GLS) Datasets

USGS Publications Warehouse

Gutman, Garik; Huang, Chengquan; Chander, Gyanesh; Noojipady, Praveen; Masek, Jeffery G.

2013-01-01

The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from four sensors: Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. In general, the three latest GLS datasets are of a better quality than the GLS-1990 and GLS-1975 datasets, with most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This paper provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.

VizieR Online Data Catalog: Star clusters automatically detected in the LMC (Bitsakis+, 2017)

NASA Astrophysics Data System (ADS)

Bitsakis, T.; Bonfini, P.; Gonzalez-Lopezlira, R. A.; Ramirez-Siordia, V. H.; Bruzual, G.; Charlot, S.; Maravelias, G.; Zaritsky, D.

2018-03-01

The archival data used in this work were acquired from several diverse large surveys, which mapped the Magellanic Clouds at various bands. Simons+ (2014AdSpR..53..939S) composed a mosaic using archival data from the Galaxy Evolution Explorer (GALEX) at the near-ultraviolet (NUV) band (λeff=2275Å). The mosaic covers an area of 15deg2 on the LMC. the central ~3x1deg2 of the LMC (the bar-region) was later observed by the Swift Ultraviolet-Optical Telescope (UVOT) Magellanic Clouds Survey (SUMAC; Siegel+ 2014AJ....148..131S). The optical data used here are from the Magellanic Cloud Photometric Survey (MCPS; Zaritsky+ 2004, J/AJ/128/1606). These authors observed the central 64deg2 of the LMC with 3.8-5.2 minute exposures at the Johnson U, B, V, and Gunn i filters of the Las Campanas Swope Telescope. Meixner+ (2006, J/AJ/132/2268) performed a uniform and unbiased imaging survey of the LMC (called Surveying the Agents of a Galaxy's Evolution, or SAGE), covering the central 7deg2 with both the Infrared Array Camera (IRAC) and the Multiband Imaging Photometer (MIPS) on-board the Spitzer Space Telescope. (1 data file).

Satellite Studies of Cirrus Clouds for Project Fire

NASA Technical Reports Server (NTRS)

1997-01-01

Examine global cloud climatologies for evidence of human caused changes in cloud cover and their effect on the Earth's heat budget through radiative processes. Quantify climatological changes in global cloud cover and estimate their effect on the Earth's heat budget. Improve our knowledge of global cloud cover and its changes through the merging of several satellite data sets.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

Opening the Landsat Archive

USGS Publications Warehouse

,

2008-01-01

The USGS Landsat archive holds an unequaled 36-year record of the Earth's surface that is invaluable to climate change studies, forest and resource management activities, and emergency response operations. An aggressive effort is taking place to provide all Landsat imagery [scenes currently held in the USGS Earth Resources Observation and Science (EROS) Center archive, as well as newly acquired scenes daily] free of charge to users with electronic access via the Web by the end of December 2008. The entire Landsat 7 Enhanced Thematic Mapper Plus (ETM+) archive acquired since 1999 and any newly acquired Landsat 7 ETM+ images that have less than 40 percent cloud cover are currently available for download. When this endeavor is complete all Landsat 1-5 data will also be available for download. This includes Landsat 1-5 Multispectral Scanner (MSS) scenes, as well as Landsat 4 and 5 Thematic Mapper (TM) scenes.

Hayman Fire, Colorado

NASA Image and Video Library

2002-06-18

The Hayman forest fire, started on June 8, is continuing to burn in the Pike National Forest, 57 km (35 miles) south-southwest of Denver. According to the U.S. Forest Service, the fire has consumed more than 90,000 acres and has become Colorado's worst fire ever. In this ASTER image, acquired Sunday, June 16, 2002 at 10:30 am MST, the dark blue area is burned vegetation and the green areas are healthy vegetation. Red areas are active fires, and the blue cloud at the top center is smoke. Meteorological clouds are white. The image covers an area of 32.2 x 35.2 km (20.0 x 21.8 miles), and displays ASTER bands 8-3-2 in red, green and blue. http://photojournal.jpl.nasa.gov/catalog/PIA03499

Relationships between nocturnal winter road slipperiness, cloud cover and surface temperature

NASA Astrophysics Data System (ADS)

Grimbacher, T.; Schmid, W.

2003-04-01

Ice and Snow are important risks for road traffic. In this study we show several events of slipperiness in Switzerland, mainly caused by rain or snow falling on a frozen surface. Other reasons for slippery conditions are frost or freezing dew in clear nights and nocturnal clearing after precipitation, which goes along with radiative cooling. The main parameters of road weather forecasts are precipitation, cloudiness and surface temperature. Precipitation is well predictable with weather radars and radar nowcasting algorithms. Temperatures are often taken from numerical weather prediction models, but because of changes in cloud cover these model values are inaccurate in terms of predicting the onset of freezing. Cloudiness, especially the advection, formation and dissipation of clouds and their interaction with surface temperatures, is one of the major unsolved problems of road weather forecasts. Cloud cover and the temperature difference between air and surface temperature are important parameters of the radiation balance. In this contribution, we show the relationship between them, proved at several stations all over Switzerland. We found a quadratic correlation coefficient of typically 60% and improved it considering other meteorological parameters like wind speed and surface water. The acquired relationship may vary from one station to another, but we conclude that temperature difference is a signature for nocturnal cloudiness. We investigated nocturnal cloudiness for two cases from winters 2002 and 2003 in the canton of Lucerne in central Switzerland. There, an ultra-dense combination of two networks with together 55 stations within 50x50 km^2 is operated, measuring air and surface temperature, wind and other road weather parameters. With the aid of our equations, temperature differences detected from this network were converted into cloud maps. A comparison between precipitation seen by radar, cloud maps and surface temperatures shows that there are similar structures in all data. Depending on the situation, we also identified additional effects influencing the temperature differences, for instance the advection of could air or the influence of melting heat at or after a snow event. All these findings help to further understand the phenomena, and hence will contribute to a better predictability of winter road slipperiness.

On the response of MODIS cloud coverage to global mean surface air temperature

NASA Astrophysics Data System (ADS)

Yue, Qing; Kahn, Brian H.; Fetzer, Eric J.; Wong, Sun; Frey, Richard; Meyer, Kerry G.

2017-01-01

The global surface temperature change (ΔTs) mediated cloud cover response is directly related to cloud-climate feedback. Using satellite remote sensing data to relate cloud and climate requires a well-calibrated, stable, and consistent long-term cloud data record. The Collection 5.1 (C5) Moderate Resolution Imaging Spectroradiometer (MODIS) cloud observations have been widely used for this purpose. However, the MODIS data quality varies greatly with the surface type, spectral region, cloud type, and time periods of study, which calls for additional caution when applying such data to studies on cloud cover temporal trends and variability. Using 15 years of cloud observations made by Terra and Aqua MODIS, we analyze the ΔTs-mediated cloud cover response for different cloud types by linearly regressing the monthly anomaly of cloud cover (ΔC) with the monthly anomaly of global Ts. The Collection 6 (C6) Aqua data exhibit a similar cloud response to the long-term counterpart simulated by advanced climate models. A robust increase in altitude with increasing ΔTs is found for high clouds, while a robust decrease of ΔC is noticed for optically thick low clouds. The large differences between C5 and C6 results are from improvements in calibration and cloud retrieval algorithms. The large positive cloud cover responses with data after 2010 and the strong sensitivity to time period obtained from the Terra (C5 and C6) data are likely due to calibration drift that has not been corrected, suggesting that the previous estimate of the short-term cloud cover response from the these data should be revisited.

Using polarimetry to retrieve the cloud coverage of Earth-like exoplanets

NASA Astrophysics Data System (ADS)

Rossi, L.; Stam, D. M.

2017-11-01

Context. Clouds have already been detected in exoplanetary atmospheres. They play crucial roles in a planet's atmosphere and climate and can also create ambiguities in the determination of atmospheric parameters such as trace gas mixing ratios. Knowledge of cloud properties is required when assessing the habitability of a planet. Aims: We aim to show that various types of cloud cover such as polar cusps, subsolar clouds, and patchy clouds on Earth-like exoplanets can be distinguished from each other using the polarization and flux of light that is reflected by the planet. Methods: We have computed the flux and polarization of reflected starlight for different types of (liquid water) cloud covers on Earth-like model planets using the adding-doubling method, that fully includes multiple scattering and polarization. Variations in cloud-top altitudes and planet-wide cloud cover percentages were taken into account. Results: We find that the different types of cloud cover (polar cusps, subsolar clouds, and patchy clouds) can be distinguished from each other and that the percentage of cloud cover can be estimated within 10%. Conclusions: Using our proposed observational strategy, one should be able to determine basic orbital parameters of a planet such as orbital inclination and estimate cloud coverage with reduced ambiguities from the planet's polarization signals along its orbit.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

NASA Astrophysics Data System (ADS)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

NASA Technical Reports Server (NTRS)

Franks, Shannon; Masek, Jeffrey G.; Headley, Rachel M.; Gasch, John; Arvidson, Terry

2009-01-01

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

Possible external sources of terrestrial cloud cover variability: the solar wind

NASA Astrophysics Data System (ADS)

Voiculescu, Mirela; Usoskin, Ilya; Condurache-Bota, Simona

2014-05-01

Cloud cover plays an important role in the terrestrial radiation budget. The possible influence of the solar activity on cloud cover is still an open question with contradictory answers. An extraterrestrial factor potentially affecting the cloud cover is related to fields associated with solar wind. We focus here on a derived quantity, the interplanetary electric field (IEF), defined as the product between the solar wind speed and the meridional component, Bz, of the interplanetary magnetic field (IMF) in the Geocentric Solar Magnetospheric (GSM) system. We show that cloud cover at mid-high latitudes systematically correlates with positive IEF, which has a clear energetic input into the atmosphere, but not with negative IEF, in general agreement with predictions of the global electric circuit (GEC)-related mechanism. Since the IEF responds differently to solar activity than, for instance, cosmic ray flux or solar irradiance, we also show that such a study allows distinguishing one solar-driven mechanism of cloud evolution, via the GEC, from others. We also present results showing that the link between cloud cover and IMF varies depending on composition and altitude of clouds.

Filament formation in wind-cloud interactions- II. Clouds with turbulent density, velocity, and magnetic fields

NASA Astrophysics Data System (ADS)

Banda-Barragán, W. E.; Federrath, C.; Crocker, R. M.; Bicknell, G. V.

2018-01-01

We present a set of numerical experiments designed to systematically investigate how turbulence and magnetic fields influence the morphology, energetics, and dynamics of filaments produced in wind-cloud interactions. We cover 3D, magnetohydrodynamic systems of supersonic winds impacting clouds with turbulent density, velocity, and magnetic fields. We find that lognormal density distributions aid shock propagation through clouds, increasing their velocity dispersion and producing filaments with expanded cross-sections and highly magnetized knots and subfilaments. In self-consistently turbulent scenarios, the ratio of filament to initial cloud magnetic energy densities is ∼1. The effect of Gaussian velocity fields is bound to the turbulence Mach number: Supersonic velocities trigger a rapid cloud expansion; subsonic velocities only have a minor impact. The role of turbulent magnetic fields depends on their tension and is similar to the effect of radiative losses: the stronger the magnetic field or the softer the gas equation of state, the greater the magnetic shielding at wind-filament interfaces and the suppression of Kelvin-Helmholtz instabilities. Overall, we show that including turbulence and magnetic fields is crucial to understanding cold gas entrainment in multiphase winds. While cloud porosity and supersonic turbulence enhance the acceleration of clouds, magnetic shielding protects them from ablation and causes Rayleigh-Taylor-driven subfilamentation. Wind-swept clouds in turbulent models reach distances ∼15-20 times their core radius and acquire bulk speeds ∼0.3-0.4 of the wind speed in one cloud-crushing time, which are three times larger than in non-turbulent models. In all simulations, the ratio of turbulent magnetic to kinetic energy densities asymptotes at ∼0.1-0.4, and convergence of all relevant dynamical properties requires at least 64 cells per cloud radius.

Instrumentation for Aerosol and Gas Speciation

NASA Technical Reports Server (NTRS)

Coggiola, Michael J.

1998-01-01

Using support from NASA Grant No. NAG 2-963, SRI International successfully completed the project, entitled, 'Instrumentation for Aerosol and Gas Speciation.' This effort (SRI Project 7383) covered the design, fabrication, testing, and deployment of a real-time aerosol speciation instrument in NASA's DC-8 aircraft during the Spring 1996 SUbsonic aircraft: Contrail and Cloud Effects Special Study (SUCCESS) mission. This final technical report describes the pertinent details of the instrument design, its abilities, its deployment during SUCCESS and the data acquired from the mission, and the post-mission calibration, data reduction, and analysis.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Point Cloud Management Through the Realization of the Intelligent Cloud Viewer Software

NASA Astrophysics Data System (ADS)

Costantino, D.; Angelini, M. G.; Settembrini, F.

2017-05-01

The paper presents a software dedicated to the elaboration of point clouds, called Intelligent Cloud Viewer (ICV), made in-house by AESEI software (Spin-Off of Politecnico di Bari), allowing to view point cloud of several tens of millions of points, also on of "no" very high performance systems. The elaborations are carried out on the whole point cloud and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc), maths (BLAS, EIGEN), computational geometry (CGAL, Computational Geometry Algorithms Library), registration and advanced algorithms for point clouds (PCL, Point Cloud Library), advanced data structures (BOOST, Basic Object Oriented Supporting Tools), etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between clouds, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner) data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level) and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.

Smoke and Pollution Aerosol Effect on Cloud Cover

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Koren, Ilan

2006-01-01

Pollution and smoke aerosols can increase or decrease the cloud cover. This duality in the effects of aerosols forms one of the largest uncertainties in climate research. Using solar measurements from Aerosol Robotic Network sites around the globe, we show an increase in cloud cover with an increase in the aerosol column concentration and an inverse dependence on the aerosol absorption of sunlight. The emerging rule appears to be independent of geographical location or aerosol type, thus increasing our confidence in the understanding of these aerosol effects on the clouds and climate. Preliminary estimates suggest an increase of 5% in cloud cover.

Representing the Seasonal Variation of Marine Stratus and Stratocumulus near the Western Coast of Continents

NASA Astrophysics Data System (ADS)

He, Y.; Dickinson, R.

2005-12-01

The seasonal variation of marine stratus and stratocumulus (MSC) plays a significant role in ocean- atmosphere-land interaction during the seasonal transition of basic climate in the Eastern Pacific. A key factor in parameterization of MSC cloud cover is atmospheric stability. In this study, we examine the importance of lower troposphere stability for Marine Stratus and Stratocumulus (MSC) cloud cover variations over subtropical oceans on monthly and seasonal timescales. Our approach is to consider a two-layer conceptual model with moist denser boundary layer air topped by dry lighter free air beneath a trade wind inversion at around 700 mb.The vertical integrated dry static energy is of central importance in the lower troposphere. The variation of dry static energy transport and latent heat release leads to the variation of cloud top radiative forcing, which is a function of low cloud cover. A diagnostic cloud cover scheme derived from the model is a nonlinear function of lower troposphere stability and large-scale subsidence. Use ERA-40 and ISCCP-FD data as input, the scheme reproduces well the seasonal variation of low cloud cover in four MSC regions near the western coast of continents. NCAR CAM linear empirical cloud cover scheme could explain 16% of the observed ISCCP monthly covariance in the southeast subtropical Pacific during 1990 to 2000 period; while the new cloud cover scheme could explain 50% of the total covariance. When implementing new scheme into NCAR CAM3.1, it is found that the seasonal phase of MSC is better simulated near the Peruvian region, but the seasonal amplitudes of MSC cloud cover in four MSC regions using both schemes have systematic problems. Possible causes for model cloud biases are investigated through numerical experiments. The importance of MSC cloud cover in the eastern Pacific on local mean climate is also discussed.

Evaluation of a rule-based compositing technique for Landsat-5 TM and Landsat-7 ETM+ images

NASA Astrophysics Data System (ADS)

Lück, W.; van Niekerk, A.

2016-05-01

Image compositing is a multi-objective optimization process. Its goal is to produce a seamless cloud and artefact-free artificial image. This is achieved by aggregating image observations and by replacing poor and cloudy data with good observations from imagery acquired within the timeframe of interest. This compositing process aims to minimise the visual artefacts which could result from different radiometric properties, caused by atmospheric conditions, phenologic patterns and land cover changes. It has the following requirements: (1) image compositing must be cloud free, which requires the detection of clouds and shadows, and (2) the image composite must be seamless, minimizing artefacts and visible across inter image seams. This study proposes a new rule-based compositing technique (RBC) that combines the strengths of several existing methods. A quantitative and qualitative evaluation is made of the RBC technique by comparing it to the maximum NDVI (MaxNDVI), minimum red (MinRed) and maximum ratio (MaxRatio) compositing techniques. A total of 174 Landsat TM and ETM+ images, covering three study sites and three different timeframes for each site, are used in the evaluation. A new set of quantitative/qualitative evaluation techniques for compositing quality measurement was developed and showed that the RBC technique outperformed all other techniques, with MaxRatio, MaxNDVI, and MinRed techniques in order of performance from best to worst.

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data.

PubMed

Shang, Huazhe; Letu, Husi; Nakajima, Takashi Y; Wang, Ziming; Ma, Run; Wang, Tianxing; Lei, Yonghui; Ji, Dabin; Li, Shenshen; Shi, Jiancheng

2018-01-18

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Do Clouds Save the Great Barrier Reef? Satellite Imagery Elucidates the Cloud-SST Relationship at the Local Scale

PubMed Central

Leahy, Susannah M.; Kingsford, Michael J.; Steinberg, Craig R.

2013-01-01

Evidence of global climate change and rising sea surface temperatures (SSTs) is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an “ocean thermostat” and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR) shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006) and two relatively cool summers (2007 and 2008). Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005) and La Niña (2008) study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs. PMID:23894649

Distributed MRI reconstruction using Gadgetron-based cloud computing.

PubMed

Xue, Hui; Inati, Souheil; Sørensen, Thomas Sangild; Kellman, Peter; Hansen, Michael S

2015-03-01

To expand the open source Gadgetron reconstruction framework to support distributed computing and to demonstrate that a multinode version of the Gadgetron can be used to provide nonlinear reconstruction with clinically acceptable latency. The Gadgetron framework was extended with new software components that enable an arbitrary number of Gadgetron instances to collaborate on a reconstruction task. This cloud-enabled version of the Gadgetron was deployed on three different distributed computing platforms ranging from a heterogeneous collection of commodity computers to the commercial Amazon Elastic Compute Cloud. The Gadgetron cloud was used to provide nonlinear, compressed sensing reconstruction on a clinical scanner with low reconstruction latency (eg, cardiac and neuroimaging applications). The proposed setup was able to handle acquisition and 11 -SPIRiT reconstruction of nine high temporal resolution real-time, cardiac short axis cine acquisitions, covering the ventricles for functional evaluation, in under 1 min. A three-dimensional high-resolution brain acquisition with 1 mm(3) isotropic pixel size was acquired and reconstructed with nonlinear reconstruction in less than 5 min. A distributed computing enabled Gadgetron provides a scalable way to improve reconstruction performance using commodity cluster computing. Nonlinear, compressed sensing reconstruction can be deployed clinically with low image reconstruction latency. © 2014 Wiley Periodicals, Inc.

Predicting the temporal and spatial probability of orographic cloud cover in the Luquillo Experimental Forest in Puerto Rico using generalized linear (mixed) models.

Treesearch

Wei Wu; Charlesb Hall; Lianjun Zhang

2006-01-01

We predicted the spatial pattern of hourly probability of cloud cover in the Luquillo Experimental Forest (LEF) in North-Eastern Puerto Rico using four different models. The probability of cloud cover (defined as “the percentage of the area covered by clouds in each pixel on the map” in this paper) at any hour and any place is a function of three topographic variables...

Global surface-based cloud observation for ISCCP

NASA Technical Reports Server (NTRS)

1994-01-01

Visual observations of cloud cover are hindered at night due to inadequate illumination of the clouds. This usually leads to an underestimation of the average cloud cover at night, especially for the amounts of middle and high clouds, in climatologies on surface observations. The diurnal cycles of cloud amounts, if based on all the surface observations, are therefore in error, but they can be obtained more accurately if the nighttime observations are screened to select those made under sufficient moonlight. Ten years of nighttime weather observations from the northern hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 degrees or from a partial moon at higher elevation, or twilight from the sun less than 9 degrees below the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. Cloud cover is greater at night than during the day over the open oceans far from the continents, particularly in summer. However, near noon maxima are still evident in the coastal regions, so that the global annual average oceanic cloud cover is still slightly greater during the day than at night, by 0.3%. Over land, where daytime maxima are still obtained but with reduced amplitude, average cloud cover is 3.3% greater during the daytime. The diurnal cycles of total cloud cover we obtain are compared with those of ISCCP for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed ten years (1982-1991) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog and precipitation The global average cloud cover (average of day and night) is about 2% higher if we impose the moonlight criterion than if we use all observations. The difference is greater in winter than in summer, because of the fewer hours of darkness in the summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-1991 is found to be 55% for northern hemisphere land, 53% for southern hemisphere land, 66% for northern hemisphere ocean, and 70% for southern hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6% for nighttime 63.3%.

Clouds and the Near-Earth Environment: Possible Links

NASA Astrophysics Data System (ADS)

Condurache-Bota, Simona; Voiculescu, Mirela; Dragomir, Carmelia

2015-12-01

Climate variability is a hot topic not only for scientists and policy-makers, but also for each and every one of us. The anthropogenic activities are considered to be responsible for most climate change, however there are large uncertainties about the magnitude of effects of solar variability and other extraterrestrial influences, such as galactic cosmic rays on terrestrial climate. Clouds play an important role due to feedbacks of the radiation budget: variation of cloud cover/composition affects climate, which, in turn, affects cloud cover via atmospheric dynamics and sea temperature variations. Cloud formation and evolution are still under scientific scrutiny, since their microphysics is still not understood. Besides atmospheric dynamics and other internal climatic parameters, extraterrestrial sources of cloud cover variation are considered. One of these is the solar wind, whose effect on cloud cover might be modulated by the global atmospheric electrical circuit. Clouds height and composition, their seasonal variation and latitudinal distribution should be considered when trying to identify possible mechanisms by which solar energy is transferred to clouds. The influence of the solar wind on cloud formation can be assessed also through the ap index - the geomagnetic storm index, which can be readily connected with interplanetary magnetic field, IMF structure. This paper proposes to assess the possible relationship between both cloud cover and solar wind proxies, as the ap index, function of cloud height and composition and also through seasonal studies. The data covers almost three solar cycles (1984-2009). Mechanisms are looked for by investigating observed trends or correlation at local/seasonal scale

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Cloud Cover Increase with Increasing Aerosol Absorptivity: A Counterexample to the Conventional Semidirect Aerosol Effect

NASA Technical Reports Server (NTRS)

Perlwitz, Jan; Miller, Ron L.

2010-01-01

We reexamine the aerosol semidirect effect using a general circulation model and four cases of the single-scattering albedo of dust aerosols. Contrary to the expected decrease in low cloud cover due to heating by tropospheric aerosols, we find a significant increase with increasing absorptivity of soil dust particles in regions with high dust load, except during Northern Hemisphere winter. The strongest sensitivity of cloud cover to dust absorption is found over land during Northern Hemisphere summer. Here even medium and high cloud cover increase where the dust load is highest. The cloud cover change is directly linked to the change in relative humidity in the troposphere as a result of contrasting changes in specific humidity and temperature. More absorption by aerosols leads to larger diabatic heating and increased warming of the column, decreasing relative humidity. However, a corresponding increase in the specific humidity exceeds the temperature effect on relative humidity. The net effect is more low cloud cover with increasing aerosol absorption. The higher specific humidity where cloud cover strongly increases is attributed to an enhanced convergence of moisture driven by dust radiative heating. Although in some areas our model exhibits a reduction of low cloud cover due to aerosol heating consistent with the conventional description of the semidirect effect, we conclude that the link between aerosols and clouds is more varied, depending also on changes in the atmospheric circulation and the specific humidity induced by the aerosols. Other absorbing aerosols such as black carbon are expected to have a similar effect.

Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations

NASA Astrophysics Data System (ADS)

Morrison, A. L.; Kay, J. E.; Chepfer, H.; Guzman, R.; Yettella, V.

2018-01-01

While the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two-way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid-containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long-term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.

A new NASA/MSFC mission analysis global cloud cover data base

NASA Technical Reports Server (NTRS)

Brown, S. C.; Jeffries, W. R., III

1985-01-01

A global cloud cover data set, derived from the USAF 3D NEPH Analysis, was developed for use in climate studies and for Earth viewing applications. This data set contains a single parameter - total sky cover - separated in time by 3 or 6 hr intervals and in space by approximately 50 n.mi. Cloud cover amount is recorded for each grid point (of a square grid) by a single alphanumeric character representing each 5 percent increment of sky cover. The data are arranged in both quarterly and monthly formats. The data base currently provides daily, 3-hr observed total sky cover for the Northern Hemisphere from 1972 through 1977 less 1976. For the Southern Hemisphere, there are data at 6-hr intervals for 1976 through 1978 and at 3-hr intervals for 1979 and 1980. More years of data are being added. To validate the data base, the percent frequency of or = 0.3 and or = 0.8 cloud cover was compared with ground observed cloud amounts at several locations with generally good agreement. Mean or other desired cloud amounts can be calculated for any time period and any size area from a single grid point to a hemisphere. The data base is especially useful in evaluating the consequence of cloud cover on Earth viewing space missions. The temporal and spatial frequency of the data allow simulations that closely approximate any projected viewing mission. No adjustments are required to account for cloud continuity.

Intra-annual variability of cloud cover over the Mediterranean region based on NCEP/NCAR, MODIS and ECAD data sets

NASA Astrophysics Data System (ADS)

Ioannidis, Eleftherios; Lolis, Christos J.; Papadimas, Christos D.; Hatzianastassiou, Nikolaos; Bartzokas, Aristides

2017-04-01

The seasonal variability of total cloud cover in the Mediterranean region is examined for the period 1948-2014 using a multivariate statistical methodology. The data used consist of: i) daily gridded (1.875°x1.905°) values of total cloud cover over the broader Mediterranean region for the 66-year period 1948-2014, obtained from NCEP/NCAR Reanalysis data set, ii) daily gridded (1°x1°) values of total cloud cover for the period 2003-2014 obtained from the Moderate resolution Imaging Spectroradiometer (MODIS) satellite data set and iii) daily station cloud cover data for the period 2003-2014 obtained from the European Climate Assessment & Dataset (ECA&D). At first, the multivariate statistical method of Factor Analysis (S-mode) with varimax rotation is applied as a dimensionality reduction tool on the mean day to day intra-annual variation of NCEP/NCAR cloud cover for the period 1948-2014. According to the results, three main modes of intra-annual variation of cloud cover are found. The first mode is characterized by a winter maximum and a summer minimum and prevails mainly over the sea; a weak see-saw teleconnection over the Alps represents the opposite intra-annual marching. The second mode presents maxima in early autumn and late spring, and minima in late summer and winter, and prevails over the SW Europe and NW Africa inland regions. The third mode shows a maximum in June and a minimum in October and prevails over the eastern part of central Europe. Next, the mean day to day intra-annual variation of NCEP/NCAR cloud cover over the core regions of the above factors is calculated for the entire period 1948-2014 and the three 22-year sub-periods 1948-70, 1970-92 and 1992-2014. A comparison is carried out between each of the three sub-periods and the total period in order to reveal possible long-term changes in seasonal march of total cloud cover. The results show that cloud cover was reduced above all regions during the last 22-year sub-period 1992-2014 throughout the year, but especially in winter. Finally, given the different nature of the utilized NCEP/NCAR (Reanalysis), MODIS (satellite) and ECAD (stations) cloud cover data sets, an inter-comparison is made among them as it concerns the intra-annual variation of cloud cover for the common period 2003-2014. The results show a nice similarity among the three datasets, with some differences in magnitude during the cold period of the year.

Cloud shading and fog drip influence the metabolism of a coastal pine ecosystem.

PubMed

Carbone, Mariah S; Park Williams, A; Ambrose, Anthony R; Boot, Claudia M; Bradley, Eliza S; Dawson, Todd E; Schaeffer, Sean M; Schimel, Joshua P; Still, Christopher J

2013-02-01

Assessing the ecological importance of clouds has substantial implications for our basic understanding of ecosystems and for predicting how they will respond to a changing climate. This study was conducted in a coastal Bishop pine forest ecosystem that experiences regular cycles of stratus cloud cover and inundation in summer. Our objective was to understand how these clouds impact ecosystem metabolism by contrasting two sites along a gradient of summer stratus cover. The site that was under cloud cover ~15% more of the summer daytime hours had lower air temperatures and evaporation rates, higher soil moisture content, and received more frequent fog drip inputs than the site with less cloud cover. These cloud-driven differences in environmental conditions translated into large differences in plant and microbial activity. Pine trees at the site with greater cloud cover exhibited less water stress in summer, larger basal area growth, and greater rates of sap velocity. The difference in basal area growth between the two sites was largely due to summer growth. Microbial metabolism was highly responsive to fog drip, illustrated by an observed ~3-fold increase in microbial biomass C with increasing summer fog drip. In addition, the site with more cloud cover had greater total soil respiration and a larger fractional contribution from heterotrophic sources. We conclude that clouds are important to the ecological functioning of these coastal forests, providing summer shading and cooling that relieve pine and microbial drought stress as well as regular moisture inputs that elevate plant and microbial metabolism. These findings are important for understanding how these and other seasonally dry coastal ecosystems will respond to predicted changes in stratus cover, rainfall, and temperature. © 2012 Blackwell Publishing Ltd.

Cloud cover analysis associated to cut-off low-pressure systems over Europe using Meteosat Imagery

NASA Astrophysics Data System (ADS)

Delgado, G.; Redaño, A.; Lorente, J.; Nieto, R.; Gimeno, L.; Ribera, P.; Barriopedro, D.; García-Herrera, R.; Serrano, A.

2007-04-01

This paper reports a cloud cover analysis of cut-off low pressure systems (COL) using a pattern recognition method applied to IR and VIS bispectral histograms. 35 COL occurrences were studied over five years (1994-1998). Five cloud types were identified in COLs, of which high clouds (HCC) and deep convective clouds (DCC) were found to be the most relevant to characterize COL systems, though not the most numerous. Cloud cover in a COL is highly dependent on its stage of development, but a higher percentage of cloud cover is always present in the frontal zone, attributable due to higher amounts of high and deep convective clouds. These general characteristics are most marked during the first stage (when the amplitude of the geopotencial wave increases) and second stage (characterized by the development of a cold upper level low), closed cyclonic circulation minimizing differences between rearward and frontal zones during the third stage. The probability of heavy rains during this stage decreases considerably. The centres of mass of high and deep convective clouds move towards the COL-axis centre during COL evolution.

Cloud Height Maps for Hurricanes Frances and Ivan

NASA Technical Reports Server (NTRS)

2004-01-01

NASA's Multi-angle Imaging SpectroRadiometer (MISR) captured these images and cloud-top height retrievals of Hurricane Frances on September 4, 2004, when the eye sat just off the coast of eastern Florida, and Hurricane Ivan on September 5th, after this cyclone had devastated Grenada and was heading toward the central and western Caribbean. Hurricane Frances made landfall in the early hours of September 5, and was downgraded to Tropical Storm status as it swept inland through the Florida panhandle and continued northward. On the heels of Frances is Hurricane Ivan, which is on record as the strongest tropical cyclone to form at such a low latitude in the Atlantic, and was the most powerful hurricane to have hit the Caribbean in nearly a decade.

The ability of forecasters to predict the intensity and amount of rainfall associated with hurricanes still requires improvement, especially on the 24 to 48 hour timescale vital for disaster planning. To improve the operational models used to make hurricane forecasts, scientists need to better understand the multi-scale interactions at the cloud, mesoscale and synoptic scales that lead to hurricane intensification and dissipation, and the various physical processes that affect hurricane intensity and rainfall distributions. Because these uncertainties with regard to how to represent cloud processes still exist, it is vital that the model findings be evaluated against hurricane observations whenever possible. Two-dimensional maps of cloud height such as those shown here offer an unprecedented opportunity for comparing simulated cloud fields against actual hurricane observations.

The left-hand panel in each image pair is a natural color view from MISR's nadir camera. The right-hand panels are cloud-top height retrievals produced by automated computer recognition of the distinctive spatial features between images acquired at different view angles. These results indicate that at the time that these images were acquired, clouds within Frances and Ivan had attained altitudes of 15 kilometers and 16 kilometers above sea level, respectively. The height fields pictured here are uncorrected for the effects of cloud motion. Wind-corrected heights (which have higher accuracy but sparser spatial coverage) are within about 1 kilometer of the heights shown here.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. These data products were generated from a portion of the imagery acquired during Terra orbits 25081 and 25094. The panels cover an area of 380 kilometers x 924 kilometers, and utilize data from within blocks 65 to 87 within World Reference System-2 paths 14 and 222, respectively.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California In

The Clouds of Isidore

NASA Technical Reports Server (NTRS)

2002-01-01

These views of Hurricane Isidore were acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on September 20, 2002. After bringing large-scale flooding to western Cuba, Isidore was upgraded (on September 21) from a tropical storm to a category 3hurricane. Sweeping westward to Mexico's Yucatan Peninsula, the hurricane caused major destruction and left hundreds of thousands of people homeless. Although weakened after passing over the Yucatan landmass, Isidore regained strength as it moved northward over the Gulf of Mexico.

At left is a colorful visualization of cloud extent that superimposes MISR's radiometric camera-by-camera cloud mask (RCCM) over natural-color radiance imagery, both derived from data acquired with the instrument's vertical-viewing (nadir) camera. Using brightness and statistical metrics, the RCCM is one of several techniques MISR uses to determine whether an area is clear or cloudy. In this rendition, the RCCM has been color-coded, and purple = cloudy with high confidence, blue = cloudy with low confidence, green = clear with low confidence, and red = clear with high confidence.

In addition to providing information on meteorological events, MISR's data products are designed to help improve our understanding of the influences of clouds on climate. Cloud heights and albedos are among the variables that govern these influences. (Albedo is the amount of sunlight reflected back to space divided by the amount of incident sunlight.) The center panel is the cloud-top height field retrieved using automated stereoscopic processing of data from multiple MISR cameras. Areas where heights could not be retrieved are shown in dark gray. In some areas, such as the southern portion of the image, the stereo retrieval was able to detect thin, high clouds that were not picked up by the RCCM's nadir view. Retrieved local albedo values for Isidore are shown at right. Generation of the albedo product is dependent upon observed cloud radiances as a function of viewing angle as well as the height field. Note that over the short distances (2.2 kilometers) that the local albedo product is generated, values can be greater than 1.0 due to contributions from cloud sides. Areas where albedo could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 14669. The panels cover an area of about 380 kilometers x 704 kilometers, and utilize data from blocks 70 to 79within World Reference System-2 path 17.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air temperature.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Cloud Spirals and Outflow in Tropical Storm Katrina

NASA Technical Reports Server (NTRS)

2005-01-01

On Tuesday, August 30, 2005, NASA's Multi-angle Imaging SpectroRadiometer retrieved cloud-top heights and cloud-tracked wind velocities for Tropical Storm Katrina, as the center of the storm was situated over the Tennessee valley. At this time Katrina was weakening and no longer classified as a hurricane, and would soon become an extratropical depression. Measurements such as these can help atmospheric scientists compare results of computer-generated hurricane simulations with observed conditions, ultimately allowing them to better represent and understand physical processes occurring in hurricanes.

Because air currents are influenced by the Coriolis force (caused by the rotation of the Earth), Northern Hemisphere hurricanes are characterized by an inward counterclockwise (cyclonic) rotation towards the center. It is less widely known that, at high altitudes, outward-spreading bands of cloud rotate in a clockwise (anticyclonic) direction. The image on the left shows the retrieved cloud-tracked winds as red arrows superimposed across the natural color view from MISR's nadir (vertical-viewing) camera. Both the counter-clockwise motion for the lower-level storm clouds and the clockwise motion for the upper clouds are apparent in these images. The speeds for the clockwise upper level winds have typical values between 40 and 45 m/s (144-162 km/hr). The low level counterclockwise winds have typical values between 7 and 24 m/s (25-86 km/hr), weakening with distance from the storm center. The image on the right displays the cloud-top height retrievals. Areas where cloud heights could not be retrieved are shown in dark gray. Both the wind velocity vectors and the cloud-top height field were produced by automated computer recognition of displacements in spatial features within successive MISR images acquired at different view angles and at slightly different times.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the entire globe between 82o north and 82o south latitude every nine days. This image covers an area of about 380 kilometers by 1970 kilometers. These data products were generated from a portion of the imagery acquired during Terra orbit 30324 and utilize data from blocks 55-68 within World Reference System-2 path 22.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is managed for NASA by the California Institute of Technology.

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Cloud Arcs in the Western Pacific

NASA Technical Reports Server (NTRS)

2002-01-01

Small cumulus clouds in this natural-color view from the Multi-angle Imaging SpectroRadiometer have formed a distinctive series of quasi-circular arcs. Clues regarding the formation of these arcs can be found by noting that larger clouds exist in the interior of each arc.

The interior clouds are thicker and likely to be more convectively active than the other clouds, causing much of the air near the centers of the arcs to rise. This air spreads out horizontally in all directions as it rises and continues to spread out as it begins to sink back to the surface. This pushes any existing small cumulus clouds away from the central region of convection.

As the air sinks, it also warms, preventing other small clouds from forming, so that the regions just inside the arcs are kept clear. At the arcs, the horizontal flow of sinking air is now quite weak and on meeting the undisturbed air it can rise again slightly -- possibly assisting in the formation of new small cumulus clouds. Although examples of the continuity of air, in which every rising air motion must be compensated by a sinking motion elsewhere, are very common, the degree of organization exhibited here is relatively rare, as the wind field at different altitudes usually disrupts such patterns. The degree of self organization of this cloud image, whereby three or four such circular events form a quasi-periodic pattern, probably also requires a relatively uncommon combination of wind, temperature and humidity conditions for it to occur.

The image was acquired by MISR's nadir camera on March 11, 2002, and is centered west of the Marshall Islands. Enewetak Atoll is discernible through thin cloud as the turquoise band near the right-hand edge of the image.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and views almost the entire globe every 9 days. This image is a portion of the data acquired during Terra orbit 11863, and covers an area of about 380 kilometers x 345 kilometers. It utilizes data from blocks 80 to 82 within World Reference System-2 path 90.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Clouds at CTIO and the Dark Energy Survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neilsen, Jr., Eric

An understanding of the weather patters at Cerro-Tololo Inter-American (CTIO) Observatory, the observing site for the Dark Energy Survey (DES), is important for assessing the efciency of DES operations in using observing time and for planning future operations. CTIO has maintained records of cloud-cover by quarters of nights since 1975. A comparison between these cloud records in the 2013-2014 DES observing season (DES year 1) and achieved observing efciency and exposure quality allows the DES collaboration to make better use of the historical records in survey planning. Plots and tables here relate human recorded cloud-cover to collection of good DESmore » data, show the variation of typical cloud-cover by month, and evaluate the relationship between the El Niño weather pattern and cloud-cover at CTIO.« less

NASA Satellite Images Erupting Russian Volcano

NASA Image and Video Library

2017-08-22

Klyuchevskoi, one of the world's most active volcanoes, is seen poking through above a solid cloud deck, with an ash plume streaming to the west. Located on the Kamchatka Peninsula in far eastern Russia, it is one of many active volcanoes on the Peninsula. Nearby, to the south, the smaller Bezymianny volcano can be seem with a small steam plume coming from its summit. The image was acquired Aug. 20, 2017, covers an area of 12 by 14 miles (19.5 by 22.7 kilometers), and is located at 56.1 degrees north, 160.6 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA21878

Cloud cover and solar disk state estimation using all-sky images: deep neural networks approach compared to routine methods

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey

2017-04-01

Shortwave radiation is an important component of surface heat budget over sea and land. To estimate them accurate observations of cloud conditions are needed including total cloud cover, spatial and temporal cloud structure. While massively observed visually, for building accurate SW radiation parameterizations cloud structure needs also to be quantified using precise instrumental measurements. While there already exist several state of the art land-based cloud-cameras that satisfy researchers needs, their major disadvantages are associated with inaccuracy of all-sky images processing algorithms which typically result in the uncertainties of 2-4 octa of cloud cover estimates with the resulting true-scoring cloud cover accuracy of about 7%. Moreover, none of these algorithms determine cloud types. We developed an approach for cloud cover and structure estimating, which provides much more accurate estimates and also allows for measuring additional characteristics. This method is based on the synthetic controlling index, namely the "grayness rate index", that we introduced in 2014. Since then this index has already demonstrated high efficiency being used along with the technique namely the "background sunburn effect suppression", to detect thin clouds. This made it possible to significantly increase the accuracy of total cloud cover estimation in various sky image states using this extension of routine algorithm type. Errors for the cloud cover estimates significantly decreased down resulting the mean squared error of about 1.5 octa. Resulting true-scoring accuracy is more than 38%. The main source of this approach uncertainties is the solar disk state determination errors. While the deep neural networks approach lets us to estimate solar disk state with 94% accuracy, the final result of total cloud estimation still isn`t satisfying. To solve this problem completely we applied the set of machine learning algorithms to the problem of total cloud cover estimation directly. The accuracy of this approach varies depending on algorithm choice. Deep neural networks demonstrated the best accuracy of more than 96%. We will demonstrate some approaches and the most influential statistical features of all-sky images that lets the algorithm reach that high accuracy. With the use of our new optical package a set of over 480`000 samples has been collected in several sea missions in 2014-2016 along with concurrent standard human observed and instrumentally recorded meteorological parameters. We will demonstrate the results of the field measurements and will discuss some still remaining problems and the potential of the further developments of machine learning approach.

Improving Cloud Detection in Satellite Images of Coral Reef Environments Using Space Shuttle Photographs and High-Definition Television

NASA Technical Reports Server (NTRS)

Andrefeouet, Serge; Robinson, Julie

2000-01-01

Coral reefs worldwide are suffering from severe and rapid degradation (Bryant et A, 1998; Hoegh-Guldberg, 1999). Quick, consistent, large-scale assessment is required to assess and monitor their status (e.g., USDOC/NOAA NESDIS et al., 1999). On-going systematic collection of high resolution digital satellite data will exhaustively complement the relatively small number of SPOT, Landsat 4-5, and IRS scenes acquired for coral reefs the last 20 years. The workhorse for current image acquisition is the Landsat 7 ETM+ Long Term Acquisition Plan (Gasch et al. 2000). Coral reefs are encountered in tropical areas and cloud contamination in satellite images is frequently a problem (Benner and Curry 1998), despite new automated techniques of cloud cover avoidance (Gasch and Campana 2000). Fusion of multidate acquisitions is a classical solution to solve the cloud problems. Though elegant, this solution is costly since multiple images must be purchased for one location; the cost may be prohibitive for institutions in developing countries. There are other difficulties associated with fusing multidate images as well. For example, water quality or surface state can significantly change through time in coral reef areas making the bathymetric processing of a mosaiced image strenuous. Therefore, another strategy must be selected to detect clouds and improve coral reefs mapping. Other supplemental data could be helpful and cost-effective for distinguishing clouds and generating the best possible reef maps in the shortest amount of time. Photographs taken from the 1960s to the present from the Space Shuttle and other human-occupied spacecraft are one under-used source of alternative multitemporal data (Lulla et al. 1996). Nearly 400,000 photographs have been acquired during this period, an estimated 28,000 of these taken to date are of potential value for reef remote sensing (Robinson et al. 2000a). The photographic images can be digitized into three bands (red, green and blue) and processed for various applications (e.g., Benner and Curry 1998, Nedeltchev 1999, Glasser and Lulla 2000, Robinson et al. 2000c, Webb et al, in press).

Shuttle landing facility cloud cover study: Climatological analysis and two tenths cloud cover rule evaluation

NASA Technical Reports Server (NTRS)

Atchison, Michael K.; Schumann, Robin; Taylor, Greg; Warburton, John; Wheeler, Mark; Yersavich, Ann

1993-01-01

The two-tenths cloud cover rule in effect for all End Of Mission (EOM) STS landings at the Kennedy Space Center (KSC) states: 'for scattered cloud layers below 10,000 feet, cloud cover must be observed to be less than or equal to 0.2 at the de-orbit burn go/no-go decision time (approximately 90 minutes before landing time)'. This rule was designed to protect against a ceiling (below 10,000 feet) developing unexpectedly within the next 90 minutes (i.e., after the de-orbit burn decision and before landing). The Applied Meteorological Unit (AMU) developed and analyzed a database of cloud cover amounts and weather conditions at the Shuttle Landing Facility for a five-year (1986-1990) period. The data indicate the best time to land the shuttle at KSC is during the summer while the worst time is during the winter. The analysis also shows the highest frequency of landing opportunities occurs for the 0100-0600 UTC and 1300-1600 UTC time periods. The worst time of the day to land a shuttle is near sunrise and during the afternoon. An evaluation of the two-tenths cloud cover rule for most data categorizations has shown that there is a significant difference in the proportions of weather violations one and two hours subsequent to initial conditions of 0.2 and 0.3 cloud cover. However, for May, Oct., 700 mb northerly wind category, 1500 UTC category, and 1600 UTC category there is some evidence that the 0.2 cloud cover rule may be overly conservative. This possibility requires further investigation. As a result of these analyses, the AMU developed nomograms to help the Spaceflight Meteorological Group (SMG) and the Cape Canaveral Forecast Facility (CCFF) forecast cloud cover for EOM and Return to Launch Site (RTLS) at KSC. Future work will include updating the two tenths database, further analysis of the data for several categorizations, and developing a proof of concept artificial neural network to provide forecast guidance of weather constraint violations for shuttle landings.

350 Year Cloud Reconstruction Deduced from Northeast Caribbean Coral Proxies

NASA Astrophysics Data System (ADS)

Winter, A.; Sammarco, P. W.; Mikolajewicz, U.; Jury, M.; Zanchettin, D.

2014-12-01

Clouds are a major factor influencing the global climate and its response to external forcing through their implications for the global hydrological cycle, and hence for the planetary radiative budget. Clouds also contribute to regional climates and their variability through, e.g., the changes they induce in regional precipitation patterns. There have been very few studies of decadal and longer-term changes in cloud cover in the tropics and sub-tropics, both over land and the ocean. In the tropics, there is great uncertainty regarding how global warming will affect cloud cover. Observational satellite data are too short to unambiguously discern any temporal trends in cloud cover. Corals generally live in well-mixed coastal regions and can often record environmental conditions of large areas of the upper ocean. This is particularly the case at low latitudes. Scleractinian corals are sessile, epibenthic fauna, and the type of environmental information recorded at the location where the coral has been living is dependent upon the species of coral considered and proxy index of interest. Skeletons of scleractinian corals are considered to provide among the best records of high-resolution (sub-annual) environmental variability in the tropical and sub-tropical oceans. Zooxanthellate hermatypic corals in tropical and sub-tropical seas precipitate CaCO3 skeletons as they grow. This growth is made possible through the manufacture of CaCO3crystals, facilitated by the zooxanthellae. During the process of crystallization, the holobiont binds carbon of different isotopes into the crystals. Stable carbon isotope concentrations vary with a variety of environmental conditions. In the Caribbean, d13C in corals of the species Montastraea faveolata can be used as a proxy for changes in cloud cover. In this contribution, we will demonstrate that the stable isotope 13C varies concomitantly with cloud cover for the northeastern Caribbean region. Using this proxy we have been able to reconstruct cloud cover conditions back to the year 1760 and thus determine historical cloud cover prior to the recent use of instrumental records. We will also discuss how our coral proxy record of cloud cover compares to paleo-climate model runs for the same time period.

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

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

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.

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Snow Cover Mapping and Ice Avalanche Monitoring from the Satellite Data of the Sentinels

NASA Astrophysics Data System (ADS)

Wang, S.; Yang, B.; Zhou, Y.; Wang, F.; Zhang, R.; Zhao, Q.

2018-04-01

In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.

Temporal variability of total cloud cover at a Mediterranean megacity in the 20th century: Evidence from visual observations and climate models

NASA Astrophysics Data System (ADS)

Founda, Dimitra; Giannakopoulos, Christos; Pierros, Fragiskos

2013-04-01

Cloud cover is one of the major factors that determine the radiation budget and the climate system of the Earth. Moreover, the response of clouds has always been an important source of uncertainty in global climate models. Visual surface observations of clouds have been conducted at the National Observatory of Athens (NOA) since the mid 19th century. The historical archive of cloud reports at NOA since 1860 has been digitized and updated, spanning now a period of one and a half century. Mean monthly values of total cloud cover were derived by averaging subdaily observations of cloud cover (3 observations/day). Changes in observational practice (e.g. from 1/10 to 1/8 units) were considered, however, subjective measures of cloud cover from trained observers introduces some kind of uncertainty in the time series. Data before 1884 were considered unreliable, so the analysis was restricted to the series from 1884 to 2012. The time series of total cloud cover at NOA is validated and correlated with historical time series of other (physically related) variables such as the total sunshine duration as well as DTR (Diurnal Temperature Range) which are independently measured. Trend analysis was performed on the mean annual and seasonal series of total cloud cover from 1884-2012. The mean annual values show a marked temporal variability with sub periods of decreasing and increasing tendencies, however, the overall linear trend is positive and statistically significant (p <0.001) amounting to +2% per decade and implying a total increase of almost 25% for the whole analysed period. These results are in agreement qualitatively with the trends reported in other studies worldwide, especially concerning the period before the mid 20th century. On a seasonal basis, spring and summer series present outstanding positive long term trends, while in winter and autumn total cloud cover reveals also positive but less pronounced long term trends Additionally, an evaluation of cloud cover and/or sunshine duration/diurnal temperature range as depicted by regional climate models over Athens will be performed. Regional climate models are valuable tools for projections of future climate change but their performance is typically assessed only in terms of temperature and precipitation. The representation of non-standard parameters such as cloud cover and/or sunshine duration/diurnal temperature range has so far seen little or no evaluation in the models and can therefore be prone to large uncertainties. Regional climate models developed in the framework of recent EU projects, such as the ENSEMBLES (www.ensembles-eu.org) and the CIRCE (www.circeproject.eu) projects, will be used and an initial validation of these parameters against the historical archive of NOA will be performed.

Geo-spatial distribution of cloud cover and influence of cloud induced attenuation and noise temperature on satellite signal propagation over Nigeria

NASA Astrophysics Data System (ADS)

Ojo, Joseph Sunday

2017-05-01

The study of the influence of cloud cover on satellite propagation links is becoming more demanding due to the requirement of larger bandwidth for different satellite applications. Cloud attenuation is one of the major factors to consider for optimum performance of Ka/V and other higher frequency bands. In this paper, the geo-spatial distribution of cloud coverage over some chosen stations in Nigeria has been considered. The substantial scale spatial dispersion of cloud cover based on synoptic meteorological data and the possible impact on satellite communication links at higher frequency bands was also investigated. The investigation was based on 5 years (2008-2012) achieved cloud cover data collected by the Nigerian Meteorological Agency (NIMET) Federal Ministry of Aviation, Oshodi Lagos over four synoptic hours of the day covering day and night. The performances of satellite signals as they traverse through the cloud and cloud noise temperature at different seasons and over different hours of days at Ku/W-bands frequency are also examined. The overall result shows that the additional total atmospheric noise temperature due to the clear air effect and the noise temperature from the cloud reduces the signal-to-noise ratio of the satellite receiver systems, leading to more signal loss and if not adequately taken care of may lead to significant outage. The present results will be useful for Earth-space link budgeting, especially for the proposed multi-sensors communication satellite systems in Nigeria.

Interleaved Observation Execution and Rescheduling on Earth Observing Systems

NASA Technical Reports Server (NTRS)

Khatib, Lina; Frank, Jeremy; Smith, David; Morris, Robert; Dungan, Jennifer

2003-01-01

Observation scheduling for Earth orbiting satellites solves the following problem: given a set of requests for images of the Earth, a set of instruments for acquiring those images distributed on a collecting of orbiting satellites, and a set of temporal and resource constraints, generate a set of assignments of instruments and viewing times to those requests that satisfy those constraints. Observation scheduling is often construed as a constrained optimization problem with the objective of maximizing the overall utility of the science data acquired. The utility of an image is typically based on the intrinsic importance of acquiring it (for example, its importance in meeting a mission or science campaign objective) as well as the expected value of the data given current viewing conditions (for example, if the image is occluded by clouds, its value is usually diminished). Currently, science observation scheduling for Earth Observing Systems is done on the ground, for periods covering a day or more. Schedules are uplinked to the satellites and are executed rigorously. An alternative to this scenario is to do some of the decision-making about what images are to be acquired on-board. The principal argument for this capability is that the desirability of making an observation can change dynamically, because of changes in meteorological conditions (e.g. cloud cover), unforeseen events such as fires, floods, or volcanic eruptions, or un-expected changes in satellite or ground station capability. Furthermore, since satellites can only communicate with the ground between 5% to 10% of the time, it may be infeasible to make the desired changes to the schedule on the ground, and uplink the revisions in time for the on-board system to execute them. Examples of scenarios that motivate an on-board capability for revising schedules include the following. First, if a desired visual scene is completely obscured by clouds, then there is little point in taking it. In this case, satellite resources, such as power and storage space can be better utilized taking another image that is higher quality. Second, if an unexpected but important event occurs (such as a fire, flood, or volcanic eruption), there may be good reason to take images of it, instead of expending satellite resources on some of the lower priority scheduled observations. Finally, if there is unexpected loss of capability, it may be impossible to carry out the schedule of planned observations. For example, if a ground station goes down temporarily, a satellite may not be able to free up enough storage space to continue with the remaining schedule of observations. This paper describes an approach for interleaving execution of observation schedules with dynamic schedule revision based on changes to the expected utility of the acquired images. We describe the problem in detail, formulate an algorithm for interleaving schedule revision and execution, and discuss refinements to the algorithm based on the need for search efficiency. We summarize with a brief discussion of the tests performed on the system.

Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

DTIC Science & Technology

2013-09-30

Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys Axel...how changes in sea ice and sea surface conditions in the SIZ affect changes in cloud properties and cover . • Determine the role additional atmospheric...REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the

The impact of low-level cloud over the eastern subtropical Pacific on the ``Double ITCZ'' in LASG FGCM-0

NASA Astrophysics Data System (ADS)

Dai, Fushan; Yu, Rucong; Zhang, Xuehong; Yu, Yongqiang; Li, Jianglong

2003-05-01

Like many other coupled models, the Flexible coupled General Circulation Model (FGCM-0) suffers from the spurious “Double ITCZ”. In order to understand the “Double ITCZ” in FGCM-0, this study first examines the low-level cloud cover and the bulk stability of the low troposphere over the eastern subtropical Pacific simulated by the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3), which is the atmosphere component model of FGCM-0. It is found that the bulk stability of the low troposphere simulated by CCM3 is very consistent with the one derived from the National Center for Environmental Prediction (NCEP) reanalysis, but the simulated low-level cloud cover is much less than that derived from the International Satellite Cloud Climatology Project (ISCCP) D2 data. Based on the regression equations between the low-level cloud cover from the ISCCP data and the bulk stability of the low troposphere derived from the NCEP reanalysis, the parameterization scheme of low-level cloud in CCM3 is modified and used in sensitivity experiments to examine the impact of low-level cloud over the eastern subtropical Pacific on the spurious “Double ITCZ” in FGCM-0. Results show that the modified scheme causes the simulated low-level cloud cover to be improved locally over the cold oceans. Increasing the low-level cloud cover off Peru not only significantly alleviates the SST warm biases in the southeastern tropical Pacific, but also causes the equatorial cold tongue to be strengthened and to extend further west. Increasing the low-level cloud fraction off California effectively reduces the SST warm biases in ITCZ north of the equator. In order to examine the feedback between the SST and low-level cloud cover off Peru, one additional sensitivity experiment is performed in which the SST over the cold ocean off Peru is restored. It shows that decreasing the SST results in similar impacts over the wide regions from the southeastern tropical Pacific northwestwards to the western/central equatorial Pacific as increasing the low-level cloud cover does.

Indirect and semi-direct aerosol campaign: The impact of Arctic aerosols on clouds

DOE PAGES

McFarquhar, Greg M.; Ghan, Steven; Verlinde, Johannes; ...

2011-02-01

A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41more » stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, within, and below the single-layer stratocumulus on 8 and 26 April are enabling a process-oriented understanding of how aerosols affect arctic clouds. Inhomogeneities in reflectivity, a close coupling of upward and downward Doppler motion, and a nearly constant ice profile in the single-layer stratocumulus suggests that vertical mixing is responsible for its longevity observed during ISDAC. Data acquired in cirrus on flights between Barrow and Fairbanks, Alaska, are improving the understanding of the performance of cloud probes in ice. Furthermore, ISDAC data will improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and determine the extent to which surface measurements can provide retrievals of aerosols, clouds, precipitation, and radiative heating.« less

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

NASA Technical Reports Server (NTRS)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

The effect of moonlight on observation of cloud cover at night, and application to cloud climatology

NASA Technical Reports Server (NTRS)

Hahn, Carole J.; Warren, Stephen G.; London, Julius

1995-01-01

Ten years of nighttime weather observations from the Northern Hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 deg, light from a partial moon at higher elevation, or twilight from the sun less than 9 deg bvelow the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. The diurnal cycles of total cloud cover we obtain are compared with those of the International Satellite Cloud Climatology Project (ISCCP) for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed 10 years (1982-91) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog, and precipitation. The global average cloud cover (average of day and night) is about 2% higher if the moonlight criterion is imposed than if all observations are used. The difference is greater in winter than in summer, because of the fewer hours of darkness in summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-91 is found to be 55% for Northern Hemisphere land, 53% for Southern Hemisphere land, 66% for Northern Hemisphere ocean, and 70% for Southern Hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6%; for nighttime 63.3%.

Trends and uncertainties in U.S. cloud cover from weather stations and satellite data

NASA Astrophysics Data System (ADS)

Free, M. P.; Sun, B.; Yoo, H. L.

2014-12-01

Cloud cover data from ground-based weather observers can be an important source of climate information, but the record of such observations in the U.S. is disrupted by the introduction of automated observing systems and other artificial shifts that interfere with our ability to assess changes in cloudiness at climate time scales. A new dataset using 54 National Weather Service (NWS) and 101 military stations that continued to make human-augmented cloud observations after the 1990s has been adjusted using statistical changepoint detection and visual scrutiny. The adjustments substantially reduce the trends in U.S. mean total cloud cover while increasing the agreement between the cloud cover time series and those of physically related climate variables such as diurnal temperature range and number of precipitation days. For 1949-2009, the adjusted time series give a trend in U.S. mean total cloud of 0.11 ± 0.22 %/decade for the military data, 0.55 ± 0.24 %/decade for the NWS data, and 0.31 ± 0.22 %/decade for the combined dataset. These trends are less than half those in the original data. For 1976-2004, the original data give a significant increase but the adjusted data show an insignificant trend of -0.17 (military stations) to 0.66 %/decade (NWS stations). The differences between the two sets of station data illustrate the uncertainties in the U.S. cloud cover record. We compare the adjusted station data to cloud cover time series extracted from several satellite datasets: ISCCP (International Satellite Cloud Climatology Project), PATMOS-x (AVHRR Pathfinder Atmospheres Extended) and CLARA-a1 (CM SAF cLoud Albedo and RAdiation), and the recently developed PATMOS-x diurnally corrected dataset. Like the station data, satellite cloud cover time series may contain inhomogeneities due to changes in the observing systems and problems with retrieval algorithms. Overall we find good agreement between interannual variability in most of the satellite data and that in our station data, with the diurnally corrected PATMOS-x product generally showing the best match. For the satellite period 1984-2007, trends in the U.S. mean cloud cover from satellite data vary widely among the datasets, and all are more negative than those in the station data, with PATMOS-x having the trends closest to those in the station data.

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

NASA Astrophysics Data System (ADS)

Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

2015-10-01

This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

New optical package and algorithms for accurate estimation and interactive recording of the cloud cover information over land and sea

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail; Sinitsyn, Alexey; Gulev, Sergey

2014-05-01

Cloud fraction is a critical parameter for the accurate estimation of short-wave and long-wave radiation - one of the most important surface fluxes over sea and land. Massive estimates of the total cloud cover as well as cloud amount for different layers of clouds are available from visual observations, satellite measurements and reanalyses. However, these data are subject of different uncertainties and need continuous validation against highly accurate in-situ measurements. Sky imaging with high resolution fish eye camera provides an excellent opportunity for collecting cloud cover data supplemented with additional characteristics hardly available from routine visual observations (e.g. structure of cloud cover under broken cloud conditions, parameters of distribution of cloud dimensions). We present operational automatic observational package which is based on fish eye camera taking sky images with high resolution (up to 1Hz) in time and a spatial resolution of 968x648px. This spatial resolution has been justified as an optimal by several sensitivity experiments. For the use of the package at research vessel when the horizontal positioning becomes critical, a special extension of the hardware and software to the package has been developed. These modules provide the explicit detection of the optimal moment for shooting. For the post processing of sky images we developed a software realizing the algorithm of the filtering of sunburn effect in case of small and moderate could cover and broken cloud conditions. The same algorithm accurately quantifies the cloud fraction by analyzing color mixture for each point and introducing the so-called "grayness rate index" for every pixel. The accuracy of the algorithm has been tested using the data collected during several campaigns in 2005-2011 in the North Atlantic Ocean. The collection of images included more than 3000 images for different cloud conditions supplied with observations of standard parameters. The system is fully autonomous and has a block for digital data collection at the hard disk. The system has been tested for a wide range of open ocean cloud conditions and we will demonstrate some pilot results of data processing and physical interpretation of fractional cloud cover estimation.

ULF geomagnetic activity effects on tropospheric temperature, specific humidity, and cloud cover in Antarctica, during 2003-2010

NASA Astrophysics Data System (ADS)

Regi, Mauro; Redaelli, Gianluca; Francia, Patrizia; De Lauretis, Marcello

2017-06-01

In the present study we investigated the possible relationship between the ULF geomagnetic activity and the variations of several atmospheric parameters. In particular, we compared the ULF activity in the Pc1-2 frequency band (100 mHz-5 Hz), computed from geomagnetic field measurements at Terra Nova Bay in Antarctica, with the tropospheric temperature T, specific humidity Q, and cloud cover (high cloud cover, medium cloud cover, and low cloud cover) obtained from reanalysis data set. The statistical analysis was conducted during the years 2003-2010, using correlation and Superposed Epoch Analysis approaches. The results show that the atmospheric parameters significantly change following the increase of geomagnetic activity within 2 days. These changes are evident in particular when the interplanetary magnetic field Bz component is oriented southward (Bz<0) and the By component duskward (By>0). We suggest that both the precipitation of electrons induced by Pc1-2 activity and the intensification of the polar cap potential difference, modulating the microphysical processes in the clouds, can affect the atmosphere conditions.

Jupiter in True and False Color

NASA Image and Video Library

2001-01-23

These color composite frames of the mid-section of Jupiter were of narrow angle images acquired on December 31, 2000, a day after Cassini's closest approach to the planet. The smallest features in these frames are roughly ~ 60 kilometers. The left is natural color, composited to yield the color that Jupiter would have if seen by the naked eye. The right frame is composed of 3 images: two were taken through narrow band filters centered on regions of the spectrum where the gaseous methane in Jupiter's atmosphere absorbs light, and the third was taken in a red continuum region of the spectrum, where Jupiter has no absorptions. The combination yields an image whose colors denote the height of the clouds. Red regions are deep water clouds, bright blue regions are high haze (like the blue covering the Great Red Spot). Small, intensely bright white spots are energetic lightning storms which have penetrated high into the atmosphere where there is no opportunity for absorption of light: these high cloud systems reflect all light equally. The darkest blue regions -- for example, the long linear regions which border the northern part of the equatorial zone, are the very deep "hot spots', seen in earlier images, from which Jovian thermal emission is free to escape to space. This is the first time that global images of Jupiter in all the methane and attendant continuum filters have been acquired by a spacecraft. From images like these, the stratigraphy of Jupiter's dynamic atmosphere will be determined. http://photojournal.jpl.nasa.gov/catalog/PIA02877

Seasonal and interannual variations of top-of-atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

NASA Astrophysics Data System (ADS)

Kato, Seiji; Loeb, Norman G.; Minnis, Patrick; Francis, Jennifer A.; Charlock, Thomas P.; Rutan, David A.; Clothiaux, Eugene E.; Sun-Mack, Szedung

2006-10-01

The daytime cloud fraction derived by the Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) radiances over the Arctic from March 2000 through February 2004 increases at a rate of 0.047 per decade. The trend is significant at an 80% confidence level. The corresponding top-of-atmosphere (TOA) shortwave irradiances derived from CERES radiance measurements show less significant trend during this period. These results suggest that the influence of reduced Arctic sea ice cover on TOA reflected shortwave radiation is reduced by the presence of clouds and possibly compensated by the increase in cloud cover. The cloud fraction and TOA reflected shortwave irradiance over the Antarctic show no significant trend during the same period.

Spatial characteristics of the tropical cloud systems: comparison between model simulation and satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Guang J.; Zurovac-Jevtic, Dance; Boer, Erwin R.

1999-10-01

A Lagrangian cloud classification algorithm is applied to the cloud fields in the tropical Pacific simulated by a high-resolution regional atmospheric model. The purpose of this work is to assess the model's ability to reproduce the observed spatial characteristics of the tropical cloud systems. The cloud systems are broadly grouped into three categories: deep clouds, mid-level clouds and low clouds. The deep clouds are further divided into mesoscale convective systems and nonmesoscale convective systems. It is shown that the model is able to simulate the total cloud cover for each category reasonably well. However, when the cloud cover is broken down into contributions from cloud systems of different sizes, it is shown that the simulated cloud size distribution is biased toward large cloud systems, with contribution from relatively small cloud systems significantly under-represented in the model for both deep and mid-level clouds. The number distribution and area contribution to the cloud cover from mesoscale convective systems are very well simulated compared to the satellite observations, so are low clouds as well. The dependence of the cloud physical properties on cloud scale is examined. It is found that cloud liquid water path, rainfall, and ocean surface sensible and latent heat fluxes have a clear dependence on cloud types and scale. This is of particular interest to studies of the cloud effects on surface energy budget and hydrological cycle. The diurnal variation of the cloud population and area is also examined. The model exhibits a varying degree of success in simulating the diurnal variation of the cloud number and area. The observed early morning maximum cloud cover in deep convective cloud systems is qualitatively simulated. However, the afternoon secondary maximum is missing in the model simulation. The diurnal variation of the tropospheric temperature is well reproduced by the model while simulation of the diurnal variation of the moisture field is poor. The implication of this comparison between model simulation and observations on cloud parameterization is discussed.

A study to develop improved spacecraft show survey methods using Skylab/EREP data: Demonstration of the utility of the S190 and S192 data. [Sierra Nevadas in California, Cascades in Washington and Oregon, Upper Columbia Basin in Idaho and Montana, and Salt-Verde Watershed in Arizona

NASA Technical Reports Server (NTRS)

Barnes, J. C. (Principal Investigator); Bowley, C. J.; Smallwood, M. D.

1974-01-01

The author has identified the following significant results. This interim report provides a demonstration of the utility of spacecraft acquired Skylab S190A and S190B photography and S192 imagery for mapping areal extent of snow cover in western United States test site areas. The data sample is from the SL-2 mission flown in June 1973. Results of the investigation indicate that areal snow cover extent can be mapped more accurately from the S190A and S190B photography than from any other spacecraft system, including ERTS. The results of a qualitative analysis of the S192 imagery indicate considerable potential for the utility of multispectral snow cover analysis; the potential for distinguishing snow from clouds automatically is particularly significant.

Computational provenance in hydrologic science: a snow mapping example.

PubMed

Dozier, Jeff; Frew, James

2009-03-13

Computational provenance--a record of the antecedents and processing history of digital information--is key to properly documenting computer-based scientific research. To support investigations in hydrologic science, we produce the daily fractional snow-covered area from NASA's moderate-resolution imaging spectroradiometer (MODIS). From the MODIS reflectance data in seven wavelengths, we estimate the fraction of each 500 m pixel that snow covers. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry, so we interpolate and smooth to produce our best estimate of the daily snow cover. To manage the data, we have developed the Earth System Science Server (ES3), a software environment for data-intensive Earth science, with unique capabilities for automatically and transparently capturing and managing the provenance of arbitrary computations. Transparent acquisition avoids the scientists having to express their computations in specific languages or schemas in order for provenance to be acquired and maintained. ES3 models provenance as relationships between processes and their input and output files. It is particularly suited to capturing the provenance of an evolving algorithm whose components span multiple languages and execution environments.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map. Then the combination snow fraction map is temporally reconstructed using MATLAB Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function to derive a completely daily cloud-free snow cover map under all the sky conditions.

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

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

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. PMID:27031693

Atmospheric movies acquired at the Mars Science Laboratory landing site: Cloud morphology, frequency and significance to the Gale Crater water cycle and Phoenix mission results

NASA Astrophysics Data System (ADS)

Moores, John E.; Lemmon, Mark T.; Rafkin, Scot C. R.; Francis, Raymond; Pla-Garcia, Jorge; de la Torre Juárez, Manuel; Bean, Keri; Kass, David; Haberle, Robert; Newman, Claire; Mischna, Michael; Vasavada, Ashwin; Rennó, Nilton; Bell, Jim; Calef, Fred; Cantor, Bruce; Mcconnochie, Timothy H.; Harri, Ari-Matti; Genzer, Maria; Wong, Michael; Smith, Michael D.; Javier Martín-Torres, F.; Zorzano, María-Paz; Kemppinen, Osku; McCullough, Emily

2015-05-01

We report on the first 360 sols (LS 150° to 5°), representing just over half a Martian year, of atmospheric monitoring movies acquired using the NavCam imager from the Mars Science Laboratory (MSL) Rover Curiosity. Such movies reveal faint clouds that are difficult to discern in single images. The data set acquired was divided into two different classifications depending upon the orientation and intent of the observation. Up to sol 360, 73 Zenith movies and 79 Supra-Horizon movies have been acquired and time-variable features could be discerned in 25 of each. The data set from MSL is compared to similar observations made by the Surface Stereo Imager (SSI) onboard the Phoenix Lander and suggests a much drier environment at Gale Crater (4.6°S) during this season than was observed in Green Valley (68.2°N) as would be expected based on latitude and the global water cycle. The optical depth of the variable component of clouds seen in images with features are up to 0.047 ± 0.009 with a granularity to the features observed which averages 3.8°. MCS also observes clouds during the same period of comparable optical depth at 30 and 50 km that would suggest a cloud spacing of 2.0 to 3.3 km. Multiple motions visible in atmospheric movies support the presence of two distinct layers of clouds. At Gale Crater, these clouds are likely caused by atmospheric waves given the regular spacing of features observed in many Zenith movies and decreased spacing towards the horizon in sunset movies consistent with clouds forming at a constant elevation. Reanalysis of Phoenix data in the light of the NavCam equatorial dataset suggests that clouds may have been more frequent in the earlier portion of the Phoenix mission than was previously thought.

Evaluating the feasibility of global climate models to simulate cloud cover effect controlled by Marine Stratocumulus regime transitions

NASA Astrophysics Data System (ADS)

Goren, Tom; Muelmenstaedt, Johannes; Rosenfeld, Daniel; Quaas, Johannes

2017-04-01

Marine stratocumulus clouds (MSC) occur in two main cloud regimes of open and closed cells that differ significantly by their cloud cover. Closed cells gradually get cleansed of high CCN concentrations in a process that involves initiation of drizzle that breaks the full cloud cover into open cells. The drizzle creates downdrafts that organize the convection along converging gust fronts, which in turn produce stronger updrafts that can sustain more cloud water that compensates the depletion of the cloud water by the rain. In addition, having stronger updrafts allow the clouds to grow relatively deep before rain starts to deplete its cloud water. Therefore, lower droplet concentrations and stronger rain would lead to lower cloud fraction, but not necessary also to lower liquid water path (LWP). The fundamental relationships between these key variables derived from global climate model (GCM) simulations are analyzed with respect to observations in order to determine whether the GCM parameterizations can represent well the governing physical mechanisms upon MSC regime transitions. The results are used to evaluate the feasibility of GCM's for estimating aerosol cloud-mediated radiative forcing upon MSC regime transitions, which are responsible for the largest aerosol cloud-mediated radiative forcing.

On the existence of tropical anvil clouds

NASA Astrophysics Data System (ADS)

Seeley, J.; Jeevanjee, N.; Langhans, W.; Romps, D.

2017-12-01

In the deep tropics, extensive anvil clouds produce a peak in cloud cover below the tropopause. The dominant paradigm for cloud cover attributes this anvil peak to a layer of enhanced mass convergence in the clear-sky upper-troposphere, which is presumed to force frequent detrainment of convective anvils. However, cloud cover also depends on the lifetime of cloudy air after it detrains, which raises the possibility that anvil clouds may be the signature of slow cloud decay rather than enhanced detrainment. Here we measure the cloud decay timescale in cloud-resolving simulations, and find that cloudy updrafts that detrain in the upper troposphere take much longer to dissipate than their shallower counterparts. We show that cloud lifetimes are long in the upper troposphere because the saturation specific humidity becomes orders of magnitude smaller than the typical condensed water loading of cloudy updrafts. This causes evaporative cloud decay to act extremely slowly, thereby prolonging cloud lifetimes in the upper troposphere. As a consequence, extensive anvil clouds still occur in a convecting atmosphere that is forced to have no preferential clear-sky convergence layer. On the other hand, when cloud lifetimes are fixed at a characteristic lower-tropospheric value, extensive anvil clouds do not form. Our results support a revised understanding of tropical anvil clouds, which attributes their existence to the microphysics of slow cloud decay rather than a peak in clear-sky convergence.

Spatial Correlations of Anomaly Time Series of AIRS Version-6 Land Surface Skin Temperatures with the Nino-4 Index

NASA Technical Reports Server (NTRS)

Susskind, Joel; Lee, Jae N.; Iredell, Lena

2013-01-01

The AIRS Science Team Version-6 data set is a valuable resource for meteorological studies. Quality Controlled earth's surface skin temperatures are produced on a 45 km x 45 km spatial scale under most cloud cover conditions. The same retrieval algorithm is used for all surface types under all conditions. This study used eleven years of AIRS monthly mean surface skin temperature and cloud cover products to show that land surface skin temperatures have decreased significantly in some areas and increased significantly in other areas over the period September 2002 through August 2013. These changes occurred primarily at 1:30 PM but not at 1:30 AM. Cooling land areas contained corresponding increases in cloud cover over this time period, with the reverse being true for warming land areas. The cloud cover anomaly patterns for a given month are affected significantly by El Nino/La Nina activity, and anomalies in cloud cover are a driving force behind anomalies in land surface skin temperature.

Enhancement of Cloud Cover and Suppression of Nocturnal Drizzle in Stratocumulus Polluted by Haze

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.; Coakley, J. A., Jr.; Gore, Warren J. (Technical Monitor)

2002-01-01

Recent satellite observations indicate a significant decrease of cloud water in ship tracks, in contrast to an ensemble of in situ ship-track measurements that show no average change in cloud water relative to the surrounding clouds. We find through large-eddy simulations of stratocumulus that the trend in the satellite data is likely an artifact of sampling only overcast clouds. The simulations instead show cloud cover increasing with droplet concentrations. Our simulations also show that increases in cloud water from drizzle suppression (by increasing droplet concentrations) are favored at night or at extremely low droplet concentrations.

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

NASA Technical Reports Server (NTRS)

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.

Optical Algorithm for Cloud Shadow Detection Over Water

DTIC Science & Technology

2013-02-01

REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT TYPE Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for Cloud...particularly over humid tropical regions. Throughout the year, about two-thirds of the Earth’s surface is always covered by clouds [1]. The problem...V. Khlopenkov and A. P. Trishchenko, "SPARC: New cloud, snow , cloud shadow detection scheme for historical I-km AVHHR data over Canada," / Atmos

Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

NASA Astrophysics Data System (ADS)

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 organized to collect distributed cloud data sets suitable for MODIS-CERES cloud radiation science and solar forecasting algorithm development. A low-cost and robust sensor design suitable for large scale fabrication and long term deployment has been developed during the project prototyping phase.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

Observational evidence for cloud cover enhancement over western European forests.

PubMed

Teuling, Adriaan J; Taylor, Christopher M; Meirink, Jan Fokke; Melsen, Lieke A; Miralles, Diego G; van Heerwaarden, Chiel C; Vautard, Robert; Stegehuis, Annemiek I; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-11

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas.

Observational evidence for cloud cover enhancement over western European forests

PubMed Central

Teuling, Adriaan J.; Taylor, Christopher M.; Meirink, Jan Fokke; Melsen, Lieke A.; Miralles, Diego G.; van Heerwaarden, Chiel C.; Vautard, Robert; Stegehuis, Annemiek I.; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-01

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas. PMID:28074840

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

NASA Technical Reports Server (NTRS)

Rind, David; Lonergan, P.; Shah, K.

1999-01-01

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Correction of thin cirrus effects in AVIRIS images using the sensitive 1.375-micron cirrus detecting channel

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yorman J.

1995-01-01

Using spectral imaging data acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) from an ER-2 aircraft at 20 km altitude during various field programs, it was found that narrow channels near the center of the strong 1.38-micrometer water vapor band are very effective in detecting think cirrus clouds. Based on this observation from AVIRIS data, Gao and Kaufman proposed to put a channel centered at 1.375 micrometers with a width of 30 nm on the Moderate Resolution Imaging Spectrometer (MODIS) for remote sensing of cirrus clouds from space. The sensitivity of the 1.375-micrometer MODIS channel to detect thin cirrus clouds during the day time is expected to be one to two orders of magnitude better than the current infrared emission techniques. As a result, much larger fraction of the satellite data is expected to be identified as being covered by cirrus clouds, some of them so thin that their obscuration of the surface is very small. In order to make better studies of surface reflectance properties, thin cirrus effects must be removed from satellite images. Therefore, there is a need to study radiative properties of thin cirrus clouds, so that a strategy for correction or removal of the thin cirrus effects, similar to the correction of atmospheric aerosol effect, can be formed. In this extended abstract, we describe an empirical approach for removing/correcting thin cirrus effects in AVIRIS images using channels near 1.375 microns - one step beyond the detection of cirrus clouds using these channels.

Arsia Mons Spiral Cloud

NASA Technical Reports Server (NTRS)

2002-01-01

One of the benefits of the Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) Extended Mission is the opportunity to observe how the planet's weather changes during a second full martian year. This picture of Arsia Mons was taken June 19, 2001; southern spring equinox occurred the same day. Arsia Mons is a volcano nearly large enough to cover the state of New Mexico. On this particular day (the first day of Spring), the MOC wide angle cameras documented an unusual spiral-shaped cloud within the 110 km (68 mi) diameter caldera--the summit crater--of the giant volcano. Because the cloud is bright both in the red and blue images acquired by the wide angle cameras, it probably consisted mostly of fine dust grains. The cloud's spin may have been induced by winds off the inner slopes of the volcano's caldera walls resulting from the temperature differences between the walls and the caldera floor, or by a vortex as winds blew up and over the caldera. Similar spiral clouds were seen inside the caldera for several days; we don't know if this was a single cloud that persisted throughout that time or one that regenerated each afternoon. Sunlight illuminates this scene from the left/upper left.

Malin Space Science Systems and the California Institute of Technology built the MOC using spare hardware from the Mars Observer mission. MSSS operates the camera from its facilities in San Diego, CA. The Jet Propulsion Laboratory's Mars Surveyor Operations Project operates the Mars Global Surveyor spacecraft with its industrial partner, Lockheed Martin Astronautics, from facilities in Pasadena, CA and Denver, CO.

Research on snow cover monitoring of Northeast China using Fengyun Geostationary Satellite

NASA Astrophysics Data System (ADS)

Wu, Tong; Gu, Lingjia; Ren, Ruizhi; Zhou, TIngting

2017-09-01

Snow cover information has great significance for monitoring and preventing snowstorms. With the development of satellite technology, geostationary satellites are playing more important roles in snow monitoring. Currently, cloud interference is a serious problem for obtaining accurate snow cover information. Therefore, the cloud pixels located in the MODIS snow products are usually replaced by cloud-free pixels around the day, which ignores snow cover dynamics. FengYun-2(FY-2) is the first generation of geostationary satellite in our country which complements the polar orbit satellite. The snow cover monitoring of Northeast China using FY-2G data in January and February 2016 is introduced in this paper. First of all, geometric and radiometric corrections are carried out for visible and infrared channels. Secondly, snow cover information is extracted according to its characteristics in different channels. Multi-threshold judgment methods for the different land types and similarity separation techniques are combined to discriminate snow and cloud. Furthermore, multi-temporal data is used to eliminate cloud effect. Finally, the experimental results are compared with the MOD10A1 and MYD10A1 (MODIS daily snow cover) product. The MODIS product can provide higher resolution of the snow cover information in cloudless conditions. Multi-temporal FY-2G data can get more accurate snow cover information in cloudy conditions, which is beneficial for monitoring snowstorms and climate changes.

The Cloud Detection and Ultraviolet Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, Louis M.; Loh, Eugene C.; Krizmanic, John F.; Sokolsky, Pierre; Streitmatter, Robert E.

2004-01-01

In this paper we describe a new balloon instrument - CLUE - which is designed to monitor ultraviolet (uv) nightglow levels and determine cloud cover and cloud heights with a CO2 slicing technique. The CO2 slicing technique is based on the MODIS instrument on NASA's Aqua and Terra spacecraft. CLUE will provide higher spatial resolution (0.5 km) and correlations between the uv and the cloud cover.

Using cloud and climate data to understand warm season hydrometeorology from diurnal to monthly timescales

NASA Astrophysics Data System (ADS)

Betts, A. K.; Tawfik, A. B.; Desjardins, R. L.

2016-12-01

We use 600 station years of hourly data from 14 stations on the Canadian Prairies to map the warm season hydrometeorology. The months from April (after snowmelt) to September, have a very similar coupling between surface thermodynamics and opaque cloud cover, which has been calibrated to give cloud radiative forcing. We can derive both the mean diurnal ranges and the diurnal imbalances as a function of opaque cloud cover. For the monthly diurnal climate, we compute the coupling coefficients with opaque cloud cover and lagged precipitation. In April the diurnal cycle climate has memory of precipitation back to freeze-up in November. During the growing season months of June, July and August, there is memory of precipitation back to March. Monthly mean temperature depends strongly on cloud but little on precipitation, while monthly mean mixing ratio depends on precipitation, but rather little on cloud. The coupling coefficients to cloud and precipitation change with increasing monthly precipitation anomaly. This observational climate analysis provides a firm basis for model evaluation.

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

NASA Astrophysics Data System (ADS)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

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

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail

2017-02-01

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

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Multi-layer Clouds Over the South Indian Ocean

NASA Image and Video Library

2003-05-07

The complex structure and beauty of polar clouds are highlighted by these images acquired by NASA Terra spacecraft on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean,

Extension of four-dimensional atmospheric models. [and cloud cover data bank

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Lisa, A. S.; Tung, S. L.

1975-01-01

The cloud data bank, the 4-D atmospheric model, and a set of computer programs designed to simulate meteorological conditions for any location above the earth are described in turns of space vehicle design and simulation of vehicle reentry trajectories. Topics discussed include: the relationship between satellite and surface observed cloud cover using LANDSAT 1 photographs and including the effects of cloud shadows; extension of the 4-D model to the altitude of 52 km; and addition of the u and v wind components to the 4-D model of means and variances at 1 km levels from the surface to 25 km. Results of the cloud cover analysis are presented along with the stratospheric model and the tropospheric wind profiles.

The budget of biologically active ultraviolet radiation in the earth-atmosphere system

NASA Technical Reports Server (NTRS)

Frederick, John E.; Lubin, Dan

1988-01-01

This study applies the concept of a budget to describe the interaction of solar ultraviolet (UV) radiation with the earth-atmosphere system. The wavelength ranges of interest are the biologically relevant UV-B between 280 and 320 nm and the UV-A from 32000 to 400 nm. The Nimbus 7 solar backscattered ultraviolet (SBUV) instrument provides measurements of total column ozone and information concerning cloud cover which, in combination with a simple model of radiation transfer, define the fractions of incident solar irradiance absorbed in the atmosphere, reflected to space, and absorbed at the ground. Results for the month of July quantify the contribution of fractional cloud cover and cloud optical thickness to the radiation budget's three components. Scattering within a thick cloud layer makes the downward radiation field at the cloud base more isotropic than is the case for clear skies. For small solar zenith angles, typical of summer midday conditions, the effective pathlength of this diffuse irradiance through tropospheric ozone is greater than that under clear-sky conditions. The result is an enhanced absorption of UV-B radiation in the troposphere during cloud-covered conditions. Major changes in global cloud cover or cloud optical thicknesses could alter the ultraviolet radiation received by the biosphere by an amount comparable to that predicted for long-term trends in ozone.

The variability of California summertime marine stratus: impacts on surface air temperatures

USGS Publications Warehouse

Iacobellis, Sam F.; Cayan, Daniel R.

2013-01-01

This study investigates the variability of clouds, primarily marine stratus clouds, and how they are associated with surface temperature anomalies over California, especially along the coastal margin. We focus on the summer months of June to September when marine stratus are the dominant cloud type. Data used include satellite cloud reflectivity (cloud albedo) measurements, hourly surface observations of cloud cover and air temperature at coastal airports, and observed values of daily surface temperature at stations throughout California and Nevada. Much of the anomalous variability of summer clouds is organized over regional patterns that affect considerable portions of the coast, often extend hundreds of kilometers to the west and southwest over the North Pacific, and are bounded to the east by coastal mountains. The occurrence of marine stratus is positively correlated with both the strength and height of the thermal inversion that caps the marine boundary layer, with inversion base height being a key factor in determining their inland penetration. Cloud cover is strongly associated with surface temperature variations. In general, increased presence of cloud (higher cloud albedo) produces cooler daytime temperatures and warmer nighttime temperatures. Summer daytime temperature fluctuations associated with cloud cover variations typically exceed 1°C. The inversion-cloud albedo-temperature associations that occur at daily timescales are also found at seasonal timescales.

Comparison of Envisat ASAR GM, AMSR-E Passive Microwave, and MODIS Optical Remote Sensing for Flood Monitoring in Australia

NASA Astrophysics Data System (ADS)

Ticehurst, C. J.; Bartsch, A.; Doubkova, M.; van Dijk, A. I. J. M.

2009-11-01

Continuous flood monitoring can support emergency response, water management and environmental monitoring. Optical sensors such as MODIS allow inundation mapping with high spatial and temporal resolution (250-1000 m, twice daily) but are affected by cloud cover. Passive microwave sensors also acquire observations at high temporal resolution, but coarser spatial resolution (e.g. ca. 5-70 km for AMSR-E) and smaller footprints are also affected by cloud and/or rain. ScanSAR systems allow all-weather monitoring but require spatial resolution to be traded off against coverage and/or temporal resolution; e.g. the ENVISAT ASAR Global Mode observes at ca. 1 km over large regions about twice a week. The complementary role of the AMSR-E and ASAR GM data to that of MODIS is here introduced for three flood events and locations across Australia. Additional improvements can be made by integrating digital elevation models and stream flow gauging data.

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

Using Space Lidar Observations to Decompose Longwave Cloud Radiative Effect Variations Over the Last Decade

NASA Astrophysics Data System (ADS)

Vaillant de Guélis, Thibault; Chepfer, Hélène; Noel, Vincent; Guzman, Rodrigo; Winker, David M.; Plougonven, Riwal

2017-12-01

Measurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).

Snow cover monitoring model and change over both time and space in pastoral area of northern China

NASA Astrophysics Data System (ADS)

Cui, Yan; Li, Suju; Wang, Ping; Zhang, Wei; Nie, Juan; Wen, Qi

2014-11-01

Snow disaster is a natural phenomenon owning to widespread snowfall for a long time and usually affect people's life, property and economic. During the whole disaster management circle, snow disaster in pastoral area of northern china which including Xinjiang, Inner Mongolia, Qinghai, Tibet has been paid more attention. Thus do a good job in snow cover monitoring then found snow disaster in time can help the people in disaster area to take effective rescue measures, which always been the central and local government great important work. Remote sensing has been used widely in snow cover monitoring for its wide range, high efficiency, less conditions, more methods and large information. NOAA/AVHRR data has been used for wide range, plenty bands information and timely acquired and act as an import data of Snow Cover Monitoring Model (SCMM). SCMM including functions list below: First after NOAA/AVHRR data has been acquired, geometric calibration, radiometric calibration and other pre-processing work has been operated. Second after band operation, four threshold conditions are used to extract snow spectrum information among water, cloud and other features in NOAA/AVHRR image. Third snow cover information has been analyzed one by one and the maximum snow cover from about twenty images in a week has been selected. Then selected image has been mosaic which covered the pastoral area of China. At last both time and space analysis has been carried out through this operational model ,such as analysis on the difference between this week and the same period of last year , this week and last week in three level regional. SCMM have been run successfully for three years, and the results have been take into account as one of the three factors which led to risk warning of snow disaster and analysis results from it always play an important role in disaster reduction and relief.

Point clouds segmentation as base for as-built BIM creation

NASA Astrophysics Data System (ADS)

Macher, H.; Landes, T.; Grussenmeyer, P.

2015-08-01

In this paper, a three steps segmentation approach is proposed in order to create 3D models from point clouds acquired by TLS inside buildings. The three scales of segmentation are floors, rooms and planes composing the rooms. First, floor segmentation is performed based on analysis of point distribution along Z axis. Then, for each floor, room segmentation is achieved considering a slice of point cloud at ceiling level. Finally, planes are segmented for each room, and planes corresponding to ceilings and floors are identified. Results of each step are analysed and potential improvements are proposed. Based on segmented point clouds, the creation of as-built BIM is considered in a future work section. Not only the classification of planes into several categories is proposed, but the potential use of point clouds acquired outside buildings is also considered.

Characterization of Polar Stratospheric Clouds With Spaceborne Lidar: CALIPSO and the 2006 Antarctic Season

NASA Technical Reports Server (NTRS)

Pitts, Michael C.; Thomason, L. W.; Poole, Lamont R.; Winker, David M.

2007-01-01

The role of polar stratospheric clouds in polar ozone loss has been well documented. The CALIPSO satellite mission offers a new opportunity to characterize PSCs on spatial and temporal scales previously unavailable. A PSC detection algorithm based on a single wavelength threshold approach has been developed for CALIPSO. The method appears to accurately detect PSCs of all opacities, including tenuous clouds, with a very low rate of false positives and few missed clouds. We applied the algorithm to CALIPSO data acquired during the 2006 Antarctic winter season from 13 June through 31 October. The spatial and temporal distribution of CALIPSO PSC observations is illustrated with weekly maps of PSC occurrence. The evolution of the 2006 PSC season is depicted by time series of daily PSC frequency as a function of altitude. Comparisons with virtual solar occultation data indicate that CALIPSO provides a different view of the PSC season than attained with previous solar occultation satellites. Measurement-based time series of PSC areal coverage and vertically-integrated PSC volume are computed from the CALIPSO data. The observed area covered with PSCs is significantly smaller than would be inferred from a temperature-based proxy such as TNAT but is similar in magnitude to that inferred from TSTS. The potential of CALIPSO measurements for investigating PSC microphysics is illustrated using combinations of lidar backscatter coefficient and volume depolarization to infer composition for two CALIPSO PSC scenes.

Dynamic resource allocation engine for cloud-based real-time video transcoding in mobile cloud computing environments

NASA Astrophysics Data System (ADS)

Adedayo, Bada; Wang, Qi; Alcaraz Calero, Jose M.; Grecos, Christos

2015-02-01

The recent explosion in video-related Internet traffic has been driven by the widespread use of smart mobile devices, particularly smartphones with advanced cameras that are able to record high-quality videos. Although many of these devices offer the facility to record videos at different spatial and temporal resolutions, primarily with local storage considerations in mind, most users only ever use the highest quality settings. The vast majority of these devices are optimised for compressing the acquired video using a single built-in codec and have neither the computational resources nor battery reserves to transcode the video to alternative formats. This paper proposes a new low-complexity dynamic resource allocation engine for cloud-based video transcoding services that are both scalable and capable of being delivered in real-time. Firstly, through extensive experimentation, we establish resource requirement benchmarks for a wide range of transcoding tasks. The set of tasks investigated covers the most widely used input formats (encoder type, resolution, amount of motion and frame rate) associated with mobile devices and the most popular output formats derived from a comprehensive set of use cases, e.g. a mobile news reporter directly transmitting videos to the TV audience of various video format requirements, with minimal usage of resources both at the reporter's end and at the cloud infrastructure end for transcoding services.

A 350 Year Cloud Cover Reconstruction Deduced from Caribbean Coral Proxies

NASA Astrophysics Data System (ADS)

Winter, Amos; Sammarco, Paul; Mikolajewicz, Uwe; Jury, Mark; Zanchettin, Davide

2015-04-01

Clouds are a major factor contributing to climate change with respect to a variety of effects on the earth's climates, primarily radiative effects, amelioration of heating, and regional changes in precipitation patterns. There have been very few studies of decadal and longer term changes in cloud cover in the tropics and sub-tropics, both over land and the ocean. In the tropics, there is great uncertainty regarding how global warming will affect cloud cover. Observational satellite data is so short that it is difficult to discern any temporal trends. The skeletons of scleractinian corals are considered to contain among the best records of high-resolution (sub-annual) environmental variability in the tropical and sub-tropical oceans. Corals generally live in well-mixed coastal regions and can often record environmental conditions of large areas of the upper ocean. This is particularly the case at low latitudes. Scleractinian corals are sessile, epibenthic fauna, and the type of environmental information recorded at the location where the coral has been living is dependent upon the species of coral considered and proxy index of interest. Zooxanthellate hermatypic corals in tropical and sub-tropical seas precipitate CaCO3 skeletons as they grow. This growth is made possible through the manufacture of CaCO3 crystals, facilitated by the zooxanthellae. During the process of crystallization, the holobiont binds carbon of different isotopes into the crystals. Stable carbon isotope concentrations vary with a variety of environmental conditions. In the Caribbean, δ13C in corals of the species Montastraea faveolata can be used as a proxy for changes in cloud cover. In this contribution, we will demonstrate that the stable isotope 13C varies concomitantly with cloud cover and present a new reconstruction of cloud cover over the Caribbean Sea that extends back to the year 1760. We will show that there is good agreement between the main features of our coral proxy record of cloud cover and of reanalysis and climate simulations for the same time period.

Some new worldwide cloud-cover models

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1981-01-01

Using daily measurements of day and night infrared, and incoming and absorbed solar radiation obtained from a Tiros satellite over a period of approximately 45 months, and integrated over 2.5 deg latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four 3-month periods, for each grid location, estimates a and b of the two parameters of the best-fit beta distribution were obtained. The (a, b) plane was divided into a number of regions. All the geographical locations whose (a, b) estimates were in the same region in the (a, b) plane were said to have the same cloud cover type for that season. For each season, the world is thus divided into separate cloud-cover types.

Cassini Imaging of Titan’s North Polar Cloud With the Visual and Infrared Mapping Spectrometer

NASA Astrophysics Data System (ADS)

Le Mouélic, S.; Rannou, P.; Rodriguez, S.; Sotin, C.; Le Corre, L.; Barnes, J. W.; Brown, R. H.; Griffith, C. A.; Baines, K. H.; Buratti, B. J.; Clark, R. N.; Nicholson, P.

2009-12-01

We report on the Visual and Infrared Mapping Spectrometer (VIMS) observations of a giant cloud over the north pole of Titan. Griffith et al. [Science, 2006] described the first evidence of a north polar feature having the form of an ubiquitous bright band at 51° to 68°N in VIMS images acquired in December 2004, August and September 2005. Rodriguez et al. [Nature, 2009] systematically detect spectral signatures of clouds with VIMS at latitudes higher than 50°N between July 2004 and December 2007, with no attempt to show the structure of each individual cloud. The first good opportunity to observe the fully illuminated north pole, that we described here, occurred on December 28, 2006. The north cloud was then continuously monitored in various geometries during 3 years after its first discovery. This cloud shows much less signal at 5-µm than southern and tropical clouds which are thought to be composed of liquid/solid methane. This indicates a lower backscattering at 5-µm. It is consistent with clouds composed of micron-sized particles made of solid ethane. A radiative transfer model in spherical geometry (SPDISORT) shows that it is found at an altitude between 30 and 40 km. This observation confirms the IPSL Titan global circulation model of Rannou et al. [Science 2006] that predicted the formation of large polar ethane clouds due to the downwelling of atmospheric streams exactly at the same latitudes. The limits of the observed northern cloud between 50-60°N corresponds to the limit between filled and dry lakes as observed by the RADAR of Cassini. The cloud cover appears less widespread in the last observations, which could indicate that it is progressively vanishing. This is also in agreement with the predictions of the IPSL general circulation model as we approach the equinox in August 2009. Dedicated observations by the Cassini spacecraft during the extended mission possibly up to 2017 should allow the observation of the forthcoming seasonal circulation turnover, with possibly the complete disappearance of this type of cloud that caps the north pole.

Cloud types and the tropical Earth radiation budget, revised

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.; Kyle, H. Lee

1989-01-01

Nimbus-7 cloud and Earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. The normal analysis was to consider net radiation as the independent variable and examine how cloud cover, cloud type, albedo and emitted radiation varied with the net radiation. Two recurring themes keep repeating on a local, regional, and zonal basis: the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. A common feature in the tropical oceans are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.

Applications of UAS-SfM for coastal vulnerability assessment: Geomorphic feature extraction and land cover classification from fine-scale elevation and imagery data

NASA Astrophysics Data System (ADS)

Sturdivant, E. J.; Lentz, E. E.; Thieler, E. R.; Remsen, D.; Miner, S.

2016-12-01

Characterizing the vulnerability of coastal systems to storm events, chronic change and sea-level rise can be improved with high-resolution data that capture timely snapshots of biogeomorphology. Imagery acquired with unmanned aerial systems (UAS) coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. Here we compare SfM-derived data to lidar and visual imagery for their utility in a) geomorphic feature extraction and b) land cover classification for coastal habitat assessment. At a beach and wetland site on Cape Cod, Massachusetts, we used UAS to capture photographs over a 15-hectare coastal area with a resulting pixel resolution of 2.5 cm. We used standard SfM processing in Agisoft PhotoScan to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM). The SfM-derived products have a horizontal uncertainty of +/- 2.8 cm. Using the point cloud in an extraction routine developed for lidar data, we determined the position of shorelines, dune crests, and dune toes. We used the output imagery and DEM to map land cover with a pixel-based supervised classification. The dense and highly precise SfM point cloud enabled extraction of geomorphic features with greater detail than with lidar. The feature positions are reported with near-continuous coverage and sub-meter accuracy. The orthomosaic image produced with SfM provides visual reflectance with higher resolution than those available from aerial flight surveys, which enables visual identification of small features and thus aids the training and validation of the automated classification. We find that the high-resolution and correspondingly high density of UAS data requires some simple modifications to existing measurement techniques and processing workflows, and that the types of data and the quality provided is equivalent to, and in some cases surpasses, that of data collected using other methods.

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

WindCam and MSPI: two cloud and aerosol instrument concepts derived from Terra/MISR heritage

NASA Astrophysics Data System (ADS)

Diner, David J.; Mischna, Michael; Chipman, Russell A.; Davis, Ab; Cairns, Brian; Davies, Roger; Kahn, Ralph A.; Muller, Jan-Peter; Torres, Omar

2008-08-01

The Multi-angle Imaging SpectroRadiometer (MISR) has been acquiring global cloud and aerosol data from polar orbit since February 2000. MISR acquires moderately high-resolution imagery at nine view angles from nadir to 70.5°, in four visible/near-infrared spectral bands. Stereoscopic parallax, time lapse among the nine views, and the variation of radiance with angle and wavelength enable retrieval of geometric cloud and aerosol plume heights, height-resolved cloud-tracked winds, and aerosol optical depth and particle property information. Two instrument concepts based upon MISR heritage are in development. The Cloud Motion Vector Camera, or WindCam, is a simplified version comprised of a lightweight, compact, wide-angle camera to acquire multiangle stereo imagery at a single visible wavelength. A constellation of three WindCam instruments in polar Earth orbit would obtain height-resolved cloud-motion winds with daily global coverage, making it a low-cost complement to a spaceborne lidar wind measurement system. The Multiangle SpectroPolarimetric Imager (MSPI) is aimed at aerosol and cloud microphysical properties, and is a candidate for the National Research Council Decadal Survey's Aerosol-Cloud-Ecosystem (ACE) mission. MSPI combines the capabilities of MISR with those of other aerosol sensors, extending the spectral coverage to the ultraviolet and shortwave infrared and incorporating high-accuracy polarimetric imaging. Based on requirements for the nonimaging Aerosol Polarimeter Sensor on NASA's Glory mission, a degree of linear polarization uncertainty of 0.5% is specified within a subset of the MSPI bands. We are developing a polarization imaging approach using photoelastic modulators (PEMs) to accomplish this objective.

77 FR 68122 - Formations of, Acquisitions by, and Mergers of Savings and Loan Holding Companies

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-15

..., Minneapolis, Minnesota 55480-0291: 1. The Miller Family 2012 Trust U/A Dated December 21, 2012, St. Cloud... Services of Saint Cloud, Inc., Saint Cloud, MN, and thereby indirectly acquire control of Liberty Savings Bank, FSB, Saint Cloud, Minnesota. Board of Governors of the Federal Reserve System, November 9, 2012...

Development and Evaluation of a Cloud-Gap-Filled MODIS Daily Snow-Cover Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Foster, James L.; Kumar, Sujay V.

2010-01-01

The utility of the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. We describe a cloud-gap-filled (CGF) daily snowcover map using a simple algorithm to track cloud persistence, to account for the uncertainty created by the age of the snow observation. Developed from the 0.050 resolution climate-modeling grid daily snow-cover product, MOD10C1, each grid cell of the CGF map provides a cloud-persistence count (CPC) that tells whether the current or a prior day was used to make the snow decision. Percentage of grid cells "observable" is shown to increase dramatically when prior days are considered. The effectiveness of the CGF product is evaluated by conducting a suite of data assimilation experiments using the community Noah land surface model in the NASA Land Information System (LIS) framework. The Noah model forecasts of snow conditions, such as snow-water equivalent (SWE), are updated based on the observations of snow cover which are obtained either from the MOD1 OC1 standard product or the new CGF product. The assimilation integrations using the CGF maps provide domain averaged bias improvement of -11 %, whereas such improvement using the standard MOD1 OC1 maps is -3%. These improvements suggest that the Noah model underestimates SWE and snow depth fields, and that the assimilation integrations contribute to correcting this systematic error. We conclude that the gap-filling strategy is an effective approach for increasing cloud-free observations of snow cover.

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

NASA Technical Reports Server (NTRS)

Kidder, Stanley Q.; Hafner, Jan

2001-01-01

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect climate and air quality. In this project the role that clouds play in this relationship was studied. Through GOES satellite observations and RAMS modeling of the Atlanta area, we found that in Atlanta (1) clouds are more frequent than in the surrounding rural areas; (2) clouds cool the surface by shading and thus tend to counteract the warming effect of urbanization; (3) clouds reflect sunlight, which might other wise be used to produce ozone; and (4) clouds decrease biogenic emission of ozone precursors, and they probably decrease ozone concentration. We also found that mesoscale modeling of clouds, especially of small, summertime clouds, needs to be improved and that coupled mesoscale and air quality models are needed to completely understand the mediating role that clouds play in the relationship between land use/land cover change and the climate and air quality of Atlanta. It is strongly recommended that more cities be studied to strengthen and extend these results.

Separating Real and Apparent Effects of Cloud, Humidity, and Dynamics on Aerosol Optical Thickness near Cloud Edges

NASA Technical Reports Server (NTRS)

Jeong, Myeong-Jae; Li, Zhanqing

2010-01-01

Aerosol optical thickness (AOT) is one of aerosol parameters that can be measured on a routine basis with reasonable accuracy from Sun-photometric observations at the surface. However, AOT-derived near clouds is fraught with various real effects and artifacts, posing a big challenge for studying aerosol and cloud interactions. Recently, several studies have reported correlations between AOT and cloud cover, pointing to potential cloud contamination and the aerosol humidification effect; however, not many quantitative assessments have been made. In this study, various potential causes of apparent correlations are investigated in order to separate the real effects from the artifacts, using well-maintained observations from the Aerosol Robotic Network, Total Sky Imager, airborne nephelometer, etc., over the Southern Great Plains site operated by the U.S. Department of Energy's Atmospheric Radiation Measurement Program. It was found that aerosol humidification effects can explain about one fourth of the correlation between the cloud cover and AOT. New particle genesis, cloud-processed particles, atmospheric dynamics, and aerosol indirect effects are likely to be contributing to as much as the remaining three fourth of the relationship between cloud cover and AOT.

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hart, W. D.

2005-01-01

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming.

The relationship of marine stratus to synoptic conditions

NASA Technical Reports Server (NTRS)

Wylie, Donald P.; Hinton, Barry; Grimm, Peter; Kloesel, Kevin A.

1990-01-01

The marine stratus which persistently covered most of the eastern Pacific Ocean, had large clear areas during the FIRE Intensive Field Operations (IFO) in 1987. Clear zones formed inside the large oceanic cloud mass on almost every day during the IFO. The location and size of the clear zones varied from day to day implying that they were related to dynamic weather conditions and not to oceanic conditions. Forecasting of cloud cover for aircraft operations during the IFO was directed towards predicting when and where the clear and broken zones would form inside the large marine stratus cloud mass. The clear zones often formed to the northwest of the operations area and moved towards it. However, on some days the clear zones appeared to form during the day in the operations area as part of the diurnal cloud burn off. The movement of the clear zones from day to day were hard to follow because of the large diurnal changes in cloud cover. Clear and broken cloud zones formed during the day only to distort in shape and fill during the following night. The field forecasters exhibited some skill in predicting when the clear and broken cloud patterns would form in the operations area. They based their predictions on the analysis and simulations of the models run by NOAA's Numeric Meteorological Center. How the atmospheric conditions analyzed by one NOAA/NMC model related to the cloud cover is discussed.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations. PMID:29057838

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

NASA Technical Reports Server (NTRS)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

PubMed

Belle, Jessica H; Chang, Howard H; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM 2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM 2.5 concentrations.

Terrestrial and Aerial Laser Scanning Data Integration Using Wavelet Analysis for the Purpose of 3D Building Modeling

PubMed Central

Kedzierski, Michal; Fryskowska, Anna

2014-01-01

Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1–5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed. PMID:25004157

Terrestrial and aerial laser scanning data integration using wavelet analysis for the purpose of 3D building modeling.

PubMed

Kedzierski, Michal; Fryskowska, Anna

2014-07-07

Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1-5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed.

The variation of cloud amount and light rainy days under heavy pollution over South China during 1960-2009.

PubMed

Fu, Chuanbo; Dan, Li

2018-01-01

The ground observation data was used to analyze the variation of cloud amount and light precipitation over South China during 1960-2009. The total cloud cover (TCC) decreases in this period, whereas the low cloud cover (LCC) shows the obvious opposite change with increasing trends. LCP defined as low cloud cover/total cloud cover has increased, and small rainy days (< 10 mm day -1 ) decreased significantly (passing 0.001 significance level) during the past 50 years, which is attributed to the enhanced levels of air pollution in the form of anthropogenic aerosols. The horizontal visibility and sunshine duration are used to depict the anthropogenic aerosol loading. When horizontal visibility declines to 20 km or sunshine duration decreases to 5 h per day, LCC increases 52% or more and LCP increases significantly. The correlation coefficients between LCC and horizontal visibility or sunshine duration are - 0.533 and - 0.927, and the values between LCP and horizontal visibility or sunshine duration are - 0.849 and - 0.641, which pass 0.001 significance level. The results indicated that aerosols likely impacted the long-term trend of cloud amount and light precipitation over South China.

SEMANTIC3D.NET: a New Large-Scale Point Cloud Classification Benchmark

NASA Astrophysics Data System (ADS)

Hackel, T.; Savinov, N.; Ladicky, L.; Wegner, J. D.; Schindler, K.; Pollefeys, M.

2017-05-01

This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show remarkable performance improvements over state-of-the-art. CNNs have become the de-facto standard for many tasks in computer vision and machine learning like semantic segmentation or object detection in images, but have no yet led to a true breakthrough for 3D point cloud labelling tasks due to lack of training data. With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks. Our semantic3D.net data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains 8 semantic classes and covers a wide range of urban outdoor scenes: churches, streets, railroad tracks, squares, villages, soccer fields and castles. We describe our labelling interface and show that our data set provides more dense and complete point clouds with much higher overall number of labelled points compared to those already available to the research community. We further provide baseline method descriptions and comparison between methods submitted to our online system. We hope semantic3D.net will pave the way for deep learning methods in 3D point cloud labelling to learn richer, more general 3D representations, and first submissions after only a few months indicate that this might indeed be the case.

Oregon Wildfire in Eclipse Zone Imaged by NASA Satellite

NASA Image and Video Library

2017-08-21

The Whitewater Fire in the Mount Jefferson Wilderness in Oregon was started by a lightning strike. As of Aug. 18, 2017, more than 117,000 acres and 30 miles (48 kilometers) of the Pacific Crest Trail are closed to the public in an area that had been expected to be popular with people there to view the August 21 solar eclipse. The smoke clouds sit over the burned area, just west-northwest of Mount Jefferson. The image was acquired Aug. 18, 2017, covers an area of 16 by 17 miles (26.1 by 27.2 kilometers), and is located at 44.7 degrees north, 121.8 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA21877

Simmering Vanuatu Volcano Imaged by NASA Satellite

NASA Image and Video Library

2017-10-06

On Sept. 28, 2017, Manaro Voui volcano on Ambae island in Vanuatu began spewing ash in a moderate eruption, prompting authorities to order the evacuation of all 11,000 residents. This nighttime thermal infrared image from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), acquired on Oct. 7, shows a hot spot (white) on the volcano's summit crater, but no large eruption. Cold clouds are dark gray, the warmer island is gray, and the ocean, (warmer than the island), is light gray. The image covers an area of 17 by 26 miles (27 by 42.4 kilometers), and is centered at 15.4 degrees south, 167.8 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA22045

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-01

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 Wṡm-2) and a surface cooling (-5 to -8 Wṡm-2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds.

PubMed

Fan, Jiwen; Leung, L Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-26

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ~27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 W m(-2)) and a surface cooling (-5 to -8 W m(-2)). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet.

PubMed

Hofer, Stefan; Tedstone, Andrew J; Fettweis, Xavier; Bamber, Jonathan L

2017-06-01

The Greenland Ice Sheet (GrIS) has been losing mass at an accelerating rate since the mid-1990s. This has been due to both increased ice discharge into the ocean and melting at the surface, with the latter being the dominant contribution. This change in state has been attributed to rising temperatures and a decrease in surface albedo. We show, using satellite data and climate model output, that the abrupt reduction in surface mass balance since about 1995 can be attributed largely to a coincident trend of decreasing summer cloud cover enhancing the melt-albedo feedback. Satellite observations show that, from 1995 to 2009, summer cloud cover decreased by 0.9 ± 0.3% per year. Model output indicates that the GrIS summer melt increases by 27 ± 13 gigatons (Gt) per percent reduction in summer cloud cover, principally because of the impact of increased shortwave radiation over the low albedo ablation zone. The observed reduction in cloud cover is strongly correlated with a state shift in the North Atlantic Oscillation promoting anticyclonic conditions in summer and suggests that the enhanced surface mass loss from the GrIS is driven by synoptic-scale changes in Arctic-wide atmospheric circulation.

Improved cloud parameterization for Arctic climate simulations based on satellite data

NASA Astrophysics Data System (ADS)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in a more correct radiative transfer and better energy budget in the atmospheric boundary layer and results also in a more realistic surface energy budget associated with more reasonable turbulent fluxes. All this mitigates the positive temperature, relative humidity and horizontal wind speed biases in the lower model levels.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic cloud data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic cloud patterns. Current investigations underway are listed and the progress made to date is summarized.

A Battlefield Obscuration Model (Smoke & Dust)

DTIC Science & Technology

1979-10-01

ia £ utace of clouds, izsclacioon (incoming radiation) during :he day ts dependent upon solar ali.::ude, which is a fuc nof time of: d&7 and time of...year. ’Irnn clouds exisc, chai~r cover and :b*ickness decrease incoming and ouzgoingS radiation. Z-a this syscea iasola:ion ts estimated b7 solar ...alzictude and =odi44ed -or existing condi:±ons of total cloud cover and cloud ceiling height. kc zig~ic, estimates of oucgoing radiacion are =ade by

Cloud Forecast Simulation Model.

DTIC Science & Technology

1981-10-01

creasing the kurtosis of the distribution, i.e., making it more negative (more platykurtic ). Case (a) might be the distribution of forecast cloud cover be...fore smoothing, and (b) might be the distribution after smoothing. Character- istically, smoothing makes cloud cover distributions less platykurtic ...19, this effect of smoothing can be described in terms of making the smoothed distribu- tion less platykurtic than the unsmoothed distribution

Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

NASA Astrophysics Data System (ADS)

Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

2017-12-01

Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

NASA Technical Reports Server (NTRS)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Aggregation of Sentinel-2 time series classifications as a solution for multitemporal analysis

NASA Astrophysics Data System (ADS)

Lewiński, Stanislaw; Nowakowski, Artur; Malinowski, Radek; Rybicki, Marcin; Kukawska, Ewa; Krupiński, Michał

2017-10-01

The general aim of this work was to elaborate efficient and reliable aggregation method that could be used for creating a land cover map at a global scale from multitemporal satellite imagery. The study described in this paper presents methods for combining results of land cover/land use classifications performed on single-date Sentinel-2 images acquired at different time periods. For that purpose different aggregation methods were proposed and tested on study sites spread on different continents. The initial classifications were performed with Random Forest classifier on individual Sentinel-2 images from a time series. In the following step the resulting land cover maps were aggregated pixel by pixel using three different combinations of information on the number of occurrences of a certain land cover class within a time series and the posterior probability of particular classes resulting from the Random Forest classification. From the proposed methods two are shown superior and in most cases were able to reach or outperform the accuracy of the best individual classifications of single-date images. Moreover, the aggregations results are very stable when used on data with varying cloudiness. They also enable to reduce considerably the number of cloudy pixels in the resulting land cover map what is significant advantage for mapping areas with frequent cloud coverage.

Relevance of long term time - Series of atmospheric parameters at a mountain observatory to models for climate change

NASA Astrophysics Data System (ADS)

Kancírová, M.; Kudela, K.; Erlykin, A. D.; Wolfendale, A. W.

2016-10-01

A detailed analysis has been made based on annual meteorological and cosmic ray data from the Lomnicky stit mountain observatory (LS, 2634 masl; 49.40°N, 20.22°E; vertical cut-off rigidity 3.85 GV), from the standpoint of looking for possible solar cycle (including cosmic ray) manifestations. A comparison of the mountain data with the Global average for the cloud cover in general shows no correlation but there is a possible small correlation for low clouds (LCC in the Global satellite data). However, whereas it cannot be claimed that cloud cover observed at Lomnicky stit (LSCC) can be used directly as a proxy for the Global LCC, its examination has value because it is an independent estimate of cloud cover and one that has a different altitude weighting to that adopted in the satellite-derived LCC. This statement is derived from satellite data (http://isccp.giss.nasa.gov/climanal7.html) which shows the time series for the period 1983-2010 for 9 cloud regimes. There is a significant correlation only between cosmic ray (CR) intensity (and sunspot number (SSN)) and the cloud cover of the types cirrus and stratus. This effect is mainly confined to the CR intensity minimum during the epoch around 1990, when the SSN was at its maximum. This fact, together with the present study of the correlation of LSCC with our measured CR intensity, shows that there is no firm evidence for a significant contribution of CR induced ionization to the local (or, indeed, Global) cloud cover. Pressure effects are the preferred cause of the cloud cover changes. A consequence is that there is no evidence favouring a contribution of CR to the Global Warming problem. Our analysis shows that the LS data are consistent with the Gas Laws for a stable mass of atmosphere.

More Frequent Cloud Free Sky and Less Surface Solar Radiation in China from 1955-2000

NASA Technical Reports Server (NTRS)

Qian, Yun; Kaiser, Dale P.; Leung, L. Ruby; Xu, Ming

2006-01-01

In this study, we used newly available data frorn extended weather stations and time period to reveal that much of China has experienced significant decreases in cloud cover over the last half of the Twentieth century. This conclusion is supported by analysis of the more reliably observed frequency of cloud-free sky and overcast sky. We estimated that the total cloud cover and low cloud cover in China have decreased 0.88% and 0.33% per decade, respectively, and cloud-free days have increased 0.60% and overcast days decreased 0.78% per decade from 1954-2001. Meanwhile, both solar radiation and pan evaporation have decreased in China, with'solar radiation decreasing 3.1 w/square m and pan evaporation decreasing 39 mm per decade. Combining these results with findings of previous studies, we speculated that increased air pollution may have produced a fog-like haze that reflected/absorbed radiation from the sun and resulted in less solar radiation reaching the surface, despite concurrent increasing trends in cloud-free sky over China.

The cloud-radiative processes and its modulation by sea-ice cover and stability as derived from a merged C3M Data product.

NASA Astrophysics Data System (ADS)

Nag, B.

2016-12-01

The polar regions of the world constitute an important sector in the global energy balance. Among other effects responsible for the change in the sea-ice cover like ocean circulation and ice-albedo feedback, the cloud-radiation feedback also plays a vital role in modulation of the Arctic environment. However the annual cycle of the clouds is very poorly represented in current global circulation models. This study aims to take advantage of a merged C3M data (CALIPSO, CloudSat, CERES, and MODIS) product from the NASA's A-Train Series to explore the sea-ice and atmospheric conditions in the Arctic on a spatial coverage spanning 70N to 80N. This study is aimed at the interactions or the feedbacks processes among sea-ice, clouds and the atmosphere. Using a composite approach based on a classification due to surface type, it is found that limitation of the water vapour influx from the surface due to change in phase at the surface featuring open oceans or marginal sea-ice cover to complete sea-ice cover is a major determinant in the modulation of the atmospheric moisture and its impacts. The impact of the cloud-radiative effects in the Arctic is found to vary with sea-ice cover and seasonally. The effect of the marginal sea-ice cover becomes more and more pronounced in the winter. The seasonal variation of the dependence of the atmospheric moisture on the surface and the subsequent feedback effects is controlled by the atmospheric stability measured as a difference between the potential temperature at the surface and the 700hPa level. It is found that a stronger stability cover in the winter is responsible for the longwave cloud radiative feedback in winter which is missing during the summer. A regional analysis of the same suggests that most of the depiction of the variations observed is contributed from the North Atlantic region.

Slicing The 2010 Saturn's Storm: Upper Clouds And Hazes

NASA Astrophysics Data System (ADS)

Perez-Hoyos, Santiago; Sanz-Requena, J. F.; Sanchez-Lavega, A.; Hueso, R.

2012-10-01

At the end of 2010 a small storm erupted in Saturn's northern mid-latitudes. Starting from a localized perturbation, it grew up to be a global-scale disturbance and cover the whole latitude band by February, 2011 (Fletcher et al. 2011, Science 332; Sánchez-Lavega et al. 2011, Nature 475; Fischer et al. 2011, Nature 475). By June, 2011 the storm was facing its end and gradually disappeared (Sánchez-Lavega et al. 2012, Icarus 220). In this work we use the observations acquired by the Cassini ISS instrument during the whole process to investigate the vertical cloud and haze structure above the ammonia condensation level (roughly 1 bar). Cassini ISS observations cover visual wavelengths from the blue to the near-infrared including two methane absorption bands. Such observations have been modeled using a radiative transfer code which reproduces the atmospheric reflectivity as a function of observation/illumination geometry and wavelength together with a retrieval technique to find maximum likelihood atmospheric models. This allows to investigate some atmospheric parameters: cloud-top pressures, aerosol optical thickness and particle absorption, among others. We will focus on two aspects: (1) maximum likelihood models for the undisturbed reference atmosphere in the 15°N to 45°N band before and after the disturbance; (2) models for particular structures during the development of the global-scale phenomenon. Our results show a general increase of particle density and single-scattering albedo inside the storm. However, some discrete features showing anomalous structure and related to the storm peculiar dynamics will also be discussed. Acknowledgments: This work was supported by the Spanish MICIIN project AYA2009-10701 with FEDER funds, by Grupos Gobierno Vasco IT-464-07 and by Universidad País Vasco UPV/EHU through program UFI11/55.

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

MISR RICO Products

Atmospheric Science Data Center

2016-11-25

... microphysics of the transition to a mature rainshaft, organization of trade wind clouds, water budget of trade wind cumulus, and the ... (MISR) mission objectives involve providing accurate information on cloud cover, cloud-track winds, stereo-derived cloud-top ...

Correlation between atmospheric electric fields and cloud cover using a field mill and cloud observation data

NASA Astrophysics Data System (ADS)

Nakamori, Kota; Suzuki, Yasuki; Ohya, Hiroyo; Takano, Toshiaki; Kawamura, Yohei; Nakata, Hiroyuki; Yamashita, Kozo

2017-04-01

It is known that lightning and precipitations of rain droplets generated from thunderclouds are a generator of global atmospheric electric circuit. In the fair weather, the atmospheric electric fields (AEF) are downward (positive), while they are upward (negative) during lightning and precipitations. However, the correlations between the AEF, and the cloud parameters such as cloud cover, weather phenomenon, have been not revealed quantitatively yet. In this study, we investigate the correlations between the AEF and the cloud parameters, weather phenomenon using a field mill, the 95 GHz-FALCON (FMCW Radar for Cloud Observations)-I and all-sky camera observations. In this study, we installed a Boltek field mill on the roof of our building in Chiba University, Japan, (Geographic coordinate: 35.63 degree N, 140.10 degree E, the sea level: 55 m) on the first June, 2016. The sampling time of the AEF is 0.5 s. On the other hand, the FALCON-I has observed the cloud parameters far from about 76 m of the field mill throughout 24 hours every day. The vertical cloud profiles and the Doppler velocity of cloud particles can be derived by the FALCON-I with high distance resolutions (48.8 m) (Takano et al., 2010). In addition, the images of the clouds and precipitations are recorded with 30-s sampling by an all-sky camera using a CCD camera on the same roof during 05:00-22:00 LT every day. The distance between the field mill and the all-sky camera is 3.75 m. During 08:30 UT - 10:30 UT, on 4 July, 2016, we found the variation of the AEF due to the approach of thundercloud. The variation consisted of two patterns. One was slow variation due to the movement of thunderclouds, and the other was rapid variation associated with lightning discharges. As for the movement of thunderclouds, the AEF increased when the anvil was located over the field mill, which was opposite direction of the previous studies. This change might be due to the positive charges in the upper anvil more than 14 km altitude. As for the rapid variations of the AEF, 12 peaks of the AEF coincided with the occurrence of the lightning within 37 km. Moreover, we developed the automatic procedure to estimate the cloud cover from cloud optical images using the RGB color values. We estimated the correlation between the cloud cover and the AEF during June - November, 2016. The AEF decreased with increasing the cloud cover. This trend may be caused by the dielectric polarization due to the insert of the dielectric clouds into the global condenser. The standard deviation of AEF was small when the cloud cover increased. In this session, we will show the variations in the AEF during usual precipitations and snowing.

Cloud and surface textural features in polar regions

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Fewer clouds in the Mediterranean: consistency of observations and climate simulations

PubMed Central

Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

2017-01-01

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Wenyang; Cheung, Yam; Sawant, Amit

2016-05-15

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparsemore » regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.« less

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system.

PubMed

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-05-01

To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications.

A robust real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system

PubMed Central

Liu, Wenyang; Cheung, Yam; Sawant, Amit; Ruan, Dan

2016-01-01

Purpose: To develop a robust and real-time surface reconstruction method on point clouds captured from a 3D surface photogrammetry system. Methods: The authors have developed a robust and fast surface reconstruction method on point clouds acquired by the photogrammetry system, without explicitly solving the partial differential equation required by a typical variational approach. Taking advantage of the overcomplete nature of the acquired point clouds, their method solves and propagates a sparse linear relationship from the point cloud manifold to the surface manifold, assuming both manifolds share similar local geometry. With relatively consistent point cloud acquisitions, the authors propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, assuming that the point correspondences built by the iterative closest point (ICP) is reasonably accurate and have residual errors following a Gaussian distribution. To accommodate changing noise levels and/or presence of inconsistent occlusions during the acquisition, the authors further propose a modified sparse regression (MSR) model to model the potentially large and sparse error built by ICP with a Laplacian prior. The authors evaluated the proposed method on both clinical point clouds acquired under consistent acquisition conditions and on point clouds with inconsistent occlusions. The authors quantitatively evaluated the reconstruction performance with respect to root-mean-squared-error, by comparing its reconstruction results against that from the variational method. Results: On clinical point clouds, both the SR and MSR models have achieved sub-millimeter reconstruction accuracy and reduced the reconstruction time by two orders of magnitude to a subsecond reconstruction time. On point clouds with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent and robust performance despite the introduced occlusions. Conclusions: The authors have developed a fast and robust surface reconstruction method on point clouds captured from a 3D surface photogrammetry system, with demonstrated sub-millimeter reconstruction accuracy and subsecond reconstruction time. It is suitable for real-time motion tracking in radiotherapy, with clear surface structures for better quantifications. PMID:27147347

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of this algorithm. The two visible channels of SEVIRI are used to find the COT and the near infra red channel to estimate the effective radius of droplets. Estimation of COT using a semi analytical scheme, which doesn't involve the conventional look-up table approach, is the aim of this work and henceforth, vertically integrated liquid water (w) or ice water content will be retrieved. The COT estimated and w obtained, will be compared with the values obtained from other approaches and will be validated with in situ measurements. Corresponding author address: Praveen Pandey, VITO - Flemish Institute for Technological Research, Boeretang 200, B 2400, Mol, Belgium. E-mail: praveen.pandey@vito.be

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Xue; Klein, S. A.; Ma, H. -Y.

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE PAGES

Zheng, Xue; Klein, S. A.; Ma, H. -Y.; ...

2016-07-19

To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds

PubMed Central

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-01-01

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol’s thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3–5 W⋅m−2) and a surface cooling (−5 to −8 W⋅m−2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments. PMID:24218569

Mars Global Surveyor: 7 Years in Orbit!

NASA Technical Reports Server (NTRS)

2004-01-01

12 September 2004 Today, 12 September 2004, the Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) team celebrates 7 Earth years orbiting Mars. MGS first reached the red planet and performed its critical orbit insertion burn on 12 September 1997. Over the past 7 years, MOC has returned over 170,000 images; its narrow angle camera has covered about 4.5% of the surface, and its wide angle cameras have viewed 100% of the planet nearly everyday.

At this time, MOC is not acquiring data because Mars is on the other side of the Sun relative to Earth. This period, known as Solar Conjunction, occurs about once every 26 months. During Solar Conjunction, no radio communications from spacecraft that are orbiting or have landed on Mars can be received. MOC was turned off on 7 September and is expected to resume operations on 25 September 2004, when Mars re-emerges from behind the Sun.

The rotating color image of Mars shown here was compiled from MOC red and blue wide angle daily global images acquired exactly 1 Mars year ago on 26 October 2002 (Ls 86.4o). In other words, Mars today (12 September 2004) should look about the same as the view provided here. Presently, Mars is in very late northern spring, and the north polar cap has retreated almost to its summer configuration. Water ice clouds form each afternoon at this time of year over the large volcanoes in the Tharsis and Elysium regions. A discontinuous belt of clouds forms over the martian equator; it is most prominent north of the Valles Marineris trough system. In the southern hemisphere, it is late autumn and the giant Hellas Basin floor is nearly white with seasonal frost cover. The south polar cap is not visible, it is enveloped in seasonal darkness. The northern summer and southern winter seasons will begin on 20 September 2004.

A Model Evaluation Data Set for the Tropical ARM Sites

DOE Data Explorer

Jakob, Christian

2008-01-15

This data set has been derived from various ARM and external data sources with the main aim of providing modelers easy access to quality controlled data for model evaluation. The data set contains highly aggregated (in time) data from a number of sources at the tropical ARM sites at Manus and Nauru. It spans the years of 1999 and 2000. The data set contains information on downward surface radiation; surface meteorology, including precipitation; atmospheric water vapor and cloud liquid water content; hydrometeor cover as a function of height; and cloud cover, cloud optical thickness and cloud top pressure information provided by the International Satellite Cloud Climatology Project (ISCCP).

Accuracy Assessment of Underwater Photogrammetric Three Dimensional Modelling for Coral Reefs

NASA Astrophysics Data System (ADS)

Guo, T.; Capra, A.; Troyer, M.; Gruen, A.; Brooks, A. J.; Hench, J. L.; Schmitt, R. J.; Holbrook, S. J.; Dubbini, M.

2016-06-01

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Trends in Upper-Level Cloud Cover and Surface Divergence Over the Tropical Indo-Pacific Ocean Between 1952 And 1997

NASA Technical Reports Server (NTRS)

Norris, Joel R.

2005-01-01

This study investigated the spatial pattern of linear trends in surface-observed upper-level (combined mid-level and High-level) cloud cover, precipitation, and surface divergence over the tropical Indo-Pacific Ocean during 1952-1957. Cloud values were obtained from the Extended Edited Cloud Report Archive (EECRA), precipitation values were obtained from the Hulme/Climate Research Unit Data Set, and surface divergence was alternatively calculated from wind reported Comprehensive Ocean-Atmosphere Data Set and from Smith and Reynolds Extended Reconstructed sea level pressure data.

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

NASA Astrophysics Data System (ADS)

Tang, Zhiguang; Wang, Jian; Li, Hongyi; Yan, Lili

2013-01-01

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

Cloud Computing E-Communication Services in the University Environment

ERIC Educational Resources Information Center

Babin, Ron; Halilovic, Branka

2017-01-01

The use of cloud computing services has grown dramatically in post-secondary institutions in the last decade. In particular, universities have been attracted to the low-cost and flexibility of acquiring cloud software services from Google, Microsoft and others, to implement e-mail, calendar and document management and other basic office software.…

Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet

PubMed Central

Hofer, Stefan; Tedstone, Andrew J.; Fettweis, Xavier; Bamber, Jonathan L.

2017-01-01

The Greenland Ice Sheet (GrIS) has been losing mass at an accelerating rate since the mid-1990s. This has been due to both increased ice discharge into the ocean and melting at the surface, with the latter being the dominant contribution. This change in state has been attributed to rising temperatures and a decrease in surface albedo. We show, using satellite data and climate model output, that the abrupt reduction in surface mass balance since about 1995 can be attributed largely to a coincident trend of decreasing summer cloud cover enhancing the melt-albedo feedback. Satellite observations show that, from 1995 to 2009, summer cloud cover decreased by 0.9 ± 0.3% per year. Model output indicates that the GrIS summer melt increases by 27 ± 13 gigatons (Gt) per percent reduction in summer cloud cover, principally because of the impact of increased shortwave radiation over the low albedo ablation zone. The observed reduction in cloud cover is strongly correlated with a state shift in the North Atlantic Oscillation promoting anticyclonic conditions in summer and suggests that the enhanced surface mass loss from the GrIS is driven by synoptic-scale changes in Arctic-wide atmospheric circulation. PMID:28782014

The effects of moon illumination, moon angle, cloud cover, and sky glow on night vision goggle flight performance

NASA Astrophysics Data System (ADS)

Loro, Stephen Lee

This study was designed to examine moon illumination, moon angle, cloud cover, sky glow, and Night Vision Goggle (NVG) flight performance to determine possible effects. The research was a causal-comparative design. The sample consisted of 194 Fort Rucker Initial Entry Rotary Wing NVG flight students being observed by 69 NVG Instructor Pilots. The students participated in NVG flight training from September 1992 through January 1993. Data were collected using a questionnaire. Observations were analyzed using a Kruskal-Wallis one-way analysis of variance and a Wilcox matched pairs signed-ranks test for difference. Correlations were analyzed using Pearson's r. The analyses results indicated that performance at high moon illumination levels is superior to zero moon illumination, and in most task maneuvers, superior to >0%--50% moon illumination. No differences were found in performance at moon illumination levels above 50%. Moon angle had no effect on night vision goggle flight performance. Cloud cover and sky glow have selective effects on different maneuvers. For most task maneuvers, cloud cover does not affect performance. Overcast cloud cover had a significant effect on seven of the 14 task maneuvers. Sky glow did not affect eight out of 14 task maneuvers at any level of sky glow.

On the impact of cloudiness on the characteristics of nocturnal downslope flows

NASA Astrophysics Data System (ADS)

Ye, Z. J.; Segal, M.; Garratt, J. R.; Pielke, R. A.

1989-10-01

The effects of cloud cover amount and the height of cloud base on nighttime thermally induced downslope flow were investigated using analytical and numerical model approaches. The conclusions obtained with the analytical and the numerical model evaluations agreed. It was concluded that, (i) as cloud cover increases and/or the height of cloud base decreases, the depth and the intensity of nighttime thermally-induced downslope flows may decrease by a factor reaching one sixth and one tenth, respectively, in the case of overcast low cloud; (ii) when skies suddenly cloud over around midnight, the development of the downslope flow is altered in different ways: a reduction in intensity; or a cessation of further development, depending on the fraction of cloud coverage, and (iii) with a sudden clearing of overcast low cloud around midnight, the depth and the intensity of the downslope flow increases significantly.

Statistics of link blockage due to cloud cover for free-space optical communications using NCDC surface weather observation data

NASA Technical Reports Server (NTRS)

Slobin, S. D.; Piazzolla, S.

2002-01-01

Cloud opacity is one of the main atmospheric physical phenomena that can jeopardize the successful completion of an optical link between a spacecraft and a ground station. Hence, the site location chosen for a telescope used for optical communications must rely on knowledge of weather and cloud cover statistics for the geographical area where the telescope itself is located.

Waves on White: Ice or Clouds?

NASA Technical Reports Server (NTRS)

2005-01-01

As it passed over Antarctica on December 16, 2004, the Multi-angle Imaging SpectroRadiometer (MISR) on NASA's Terra satellite captured this image showing a wavy pattern in a field of white. At most other latitudes, such wavy patterns would likely indicate stratus or stratocumulus clouds. MISR, however, saw something different. By using information from several of its multiple cameras (each of which views the Earth's surface from a different angle), MISR was able to tell that what looked like a wavy cloud pattern was actually a wavy pattern on the ice surface. One of MISR's cloud classification products, the Angular Signature Cloud Mask (ASCM), correctly identified the rippled area as being at the surface.

In this image pair, the view from MISR's most oblique backward-viewing camera is on the left, and the color-coded image on the right shows the results of the ASCM. The colors represent the level of certainty in the classification. Areas that were classed as cloudy with high confidence are white, and areas where the confidence was lower are yellow; dark blue shows confidently clear areas, while light blue indicates clear with lower confidence. The ASCM works particularly well at detecting clouds over snow and ice, but also works well over ocean and land. The rippled area on the surface which could have been mistaken for clouds are actually sastrugi -- long wavelike ridges of snow formed by the wind and found on the polar plains. Usually sastrugi are only several centimeters high and several meters apart, but large portions of East Antarctica are covered by mega-sastrugi ice fields, with dune-like features as high as four meters separated by two to five kilometers. The mega-sastrugi fields are a result of unusual snow accumulation and redistribution processes influenced by the prevailing winds and climate conditions. MISR imagery indicates that these mega sastrugi were stationary features between 2002 and 2004.

Being able to distinguish clouds from snow or ice-covered surfaces is important in order to adequately characterize the radiation balance of the polar regions. However, detecting clouds using spaceborne detectors over snow and ice surfaces is notoriously difficult, because the surface may often be as bright and as cold as the overlying clouds, and because polar atmospheric temperature inversions sometimes mean that clouds are warmer than the underlying snow or ice surface. The Angular Signature Cloud Mask (ASCM) was developed based on the Band-Differenced Angular Signature (BDAS) approach, introduced by Di Girolamo and Davies (1994) and updated for MISR application by Di Girolamo and Wilson (2003). BDAS uses both spectral and angular changes in reflectivity to distinguish clouds from the background, and the ASCM calculates the difference between the 446 and 866 nanometer reflectances at MISR's two most oblique cameras that view forward-scattered light. New land thresholds for the ASCM are planned for delivery later this year.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. This image area covers about 277 kilometers by 421 kilometers in the interior of the East Antarctic ice sheet. These data products were generated from a portion of the imagery acquired during Terra orbit 26584 and utilize data from within blocks 159 to 161 within World Reference System-2 path 63.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Optical and morphological properties of Cirrus clouds determined by the high spectral resolution lidar during FIRE

NASA Technical Reports Server (NTRS)

Grund, Christian John; Eloranta, Edwin W.

1990-01-01

Cirrus clouds reflect incoming solar radiation and trap outgoing terrestrial radiation; therefore, accurate estimation of the global energy balance depends upon knowledge of the optical and physical properties of these clouds. Scattering and absorption by cirrus clouds affect measurements made by many satellite-borne and ground based remote sensors. Scattering of ambient light by the cloud, and thermal emissions from the cloud can increase measurement background noise. Multiple scattering processes can adversely affect the divergence of optical beams propagating through these clouds. Determination of the optical thickness and the vertical and horizontal extent of cirrus clouds is necessary to the evaluation of all of these effects. Lidar can be an effective tool for investigating these properties. During the FIRE cirrus IFO in Oct. to Nov. 1986, the High Spectral Resolution Lidar (HSRL) was operated from a rooftop site on the campus of the University of Wisconsin at Madison, Wisconsin. Approximately 124 hours of fall season data were acquired under a variety of cloud optical thickness conditions. Since the IFO, the HSRL data set was expanded by more than 63.5 hours of additional data acquired during all seasons. Measurements are presented for the range in optical thickness and backscattering phase function of the cirrus clouds, as well as contour maps of extinction corrected backscatter cross sections indicating cloud morphology. Color enhanced images of range-time indicator (RTI) displays a variety of cirrus clouds with approximately 30 sec time resolution are presented. The importance of extinction correction on the interpretation of cloud height and structure from lidar observations of optically thick cirrus are demonstrated.

Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

BrowndeColstoun, Eric

2010-01-01

For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.

Preparatory studies of zero-g cloud drop coalescence experiment

NASA Technical Reports Server (NTRS)

Telford, J. W.; Keck, T. S.

1979-01-01

Experiments to be performed in a weightless environment in order to study collision and coalescence processes of cloud droplets are described. Rain formation in warm clouds, formation of larger cloud drops, ice and water collision processes, and precipitation in supercooled clouds are among the topics covered.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

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

NASA Astrophysics Data System (ADS)

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. However during dry season, the satellite sees high altitude clouds and the camera can not detect these clouds from the ground as it relies on city lights reflected from low level clouds. With this acknowledged disparity, the ground-based camera has the advantage of detecting haze and thin clouds near the ground that are hardly or not detected by the satellites.

MODIS Views Variations in Cloud Types

NASA Technical Reports Server (NTRS)

2002-01-01

This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

Discrimination Between Clouds and Snow in Landsat 8 Imagery: an Assessment of Current Methods and a New Approach

NASA Astrophysics Data System (ADS)

Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.

2015-12-01

Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.

View of Earth from Apollo 10 taken from reproduction of tv transmission

NASA Technical Reports Server (NTRS)

1969-01-01

A cloud-covered earth from about 12,800 nautical miles away is seen in this color reproduction taken from the second TV transmission made by the color television camera onboard the Apollo 10 spacecraft. The United States and Mexico are located at right center. The more cloud-free area is the western and southwestern part of the U.S. and northern Mexico. Clouds cover the eastern half of the U.S.

Cloud cover archiving on a global scale - A discussion of principles

NASA Technical Reports Server (NTRS)

Henderson-Sellers, A.; Hughes, N. A.; Wilson, M.

1981-01-01

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

NASA Astrophysics Data System (ADS)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

Tailoring Earth Observation To Ranchers For Improved Land Management And Profitability: The VegMachine Online Project

NASA Astrophysics Data System (ADS)

Scarth, P.; Trevithick, B.; Beutel, T.

2016-12-01

VegMachine Online is a freely available browser application that allows ranchers across Australia to view and interact with satellite derived ground cover state and change maps on their property and extract this information in a graphical format using interactive tools. It supports the delivery and communication of a massive earth observation data set in an accessible, producer friendly way . Around 250,000 Landsat TM, ETM and OLI images were acquired across Australia, converted to terrain corrected surface reflectance and masked for cloud, cloud shadow, terrain shadow and water. More than 2500 field sites across the Australian rangelands were used to derive endmembers used in a constrained unmixing approach to estimate the per-pixel proportion of bare, green and non-green vegetation for all images. A seasonal metoid compositing method was used to produce national fractional cover virtual mosaics for each three month period since 1988. The time series of green fraction is used to estimate the persistent green due to tree and shrub canopies, and this estimate is used to correct the fractional cover to ground cover for our mixed tree-grass rangeland systems. Finally, deciles are produced for key metrics every season to track a pixels relativity to the entire time series. These data are delivered through time series enabled web mapping services and customised web processing services that enable the full time series over any spatial extent to be interrogated in seconds via a RESTful interface. These services interface with a front end browser application that provides product visualization for any date in the time series, tools to draw or import polygon boundaries, plot time series ground cover comparisons, look at the effect of historical rainfall and tools to run the revised universal soil loss equation in web time to assess the effect of proposed changes in cover retention. VegMachine Online is already being used by ranchers monitoring paddock condition, organisations supporting land management initiatives in Great Barrier Reef catchments, by students developing tools to understand land condition and degradation and the underlying data and APIs are supporting several other land condition mapping tools.

San Marco C-2 (San Marco-4) Post Launch Report No. 1

NASA Technical Reports Server (NTRS)

1974-01-01

The San Marco C-2 spacecraft, now designated San Marco-4, was successfully launched by a Scout vehicle from the San Marco Platform on 18 February 1974 at 6:05 a.m. EDT. The launch occurred 2 hours 50 minutes into the 3-hour window due co low cloud cover at the launch site. All spacecraft subsystems have been checked and are functioning normally. The protective caps for the two U.S. experiments were ejected and the Omegatron experiment activated on 19 February. The neutral mass spectrometer was activated as scheduled on 22 February after sufficient time to allow for spacecraft outgassing and to avoid the possibility of corona occurring. Both instruments are performing properly and worthwhile scientific data is being acquired.

Oregon Wildfire Captured in NASA Satellite Image

NASA Image and Video Library

2017-08-24

In early August 2017, the Cinder Butte fire burned 9 miles (15 kilometers) outside of the town of Riley, Oregon, and consumed more than 82 square miles (53,000 acres) of forest and brushland. The fire threatened tribal archaeological sites with strong significance to the Burns Paiute and Klamath tribes. Firefighters were able to contain the fire before it could damage the historic sites. On the image, the burned area is gray-brown, and cloud shadows are dark gray-to-black. The image was acquired Aug. 23, 2017, covers an area of 20 by 25 miles (31.5 by 39.9 kilometers), and is located at 43.5 degrees north, 119.9 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA21879

The Cloud Detection and UV Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, L.; Loh, E.; Sokolsky, P.; Streitmatter, R.

2004-01-01

We propose a large-area, low-power instrument to perform CLoud detection and Ultraviolet monitoring, CLUE. CLUE will combine the W detection capabilities of the NIGHTGLOW payload, with an array of infrared sensors to perform cloud slicing measurements. Missions such as EUSO and OWL which seek to measure UHE cosmic-rays at 1W20 eV use the atmosphere as a fluorescence detector. CLUE will provide several important correlated measurements for these missions, including: monitoring the atmospheric W emissions &om 330 - 400 nm, determining the ambient cloud cover during those W measurements (with active LIDAR), measuring the optical depth of the clouds (with an array of narrow band-pass IR sensors), and correlating LIDAR and IR cloud cover measurements. This talk will describe the instrument as we envision it.

Desktop Cloud Visualization: the new technology to remote access 3D interactive applications in the Cloud.

PubMed

Torterolo, Livia; Ruffino, Francesco

2012-01-01

In the proposed demonstration we will present DCV (Desktop Cloud Visualization): a unique technology that allows users to remote access 2D and 3D interactive applications over a standard network. This allows geographically dispersed doctors work collaboratively and to acquire anatomical or pathological images and visualize them for further investigations.

Lightweight Electronic Camera for Research on Clouds

NASA Technical Reports Server (NTRS)

Lawson, Paul

2006-01-01

"Micro-CPI" (wherein "CPI" signifies "cloud-particle imager") is the name of a small, lightweight electronic camera that has been proposed for use in research on clouds. It would acquire and digitize high-resolution (3- m-pixel) images of ice particles and water drops at a rate up to 1,000 particles (and/or drops) per second.

A Cut in the Clouds

NASA Image and Video Library

2017-12-08

Like a ship carving its way through the sea, the South Georgia and South Sandwich Islands parted the clouds. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image on February 2, 2017. The ripples in the clouds are known as gravity waves. NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response #nasagoddard

Combining structure-from-motion derived point clouds from satellites and unmanned aircraft systems images with ground-truth data to create high-resolution digital elevation models

NASA Astrophysics Data System (ADS)

Palaseanu, M.; Thatcher, C.; Danielson, J.; Gesch, D. B.; Poppenga, S.; Kottermair, M.; Jalandoni, A.; Carlson, E.

2016-12-01

Coastal topographic and bathymetric (topobathymetric) data with high spatial resolution (1-meter or better) and high vertical accuracy are needed to assess the vulnerability of Pacific Islands to climate change impacts, including sea level rise. According to the Intergovernmental Panel on Climate Change reports, low-lying atolls in the Pacific Ocean are extremely vulnerable to king tide events, storm surge, tsunamis, and sea-level rise. The lack of coastal topobathymetric data has been identified as a critical data gap for climate vulnerability and adaptation efforts in the Republic of the Marshall Islands (RMI). For Majuro Atoll, home to the largest city of RMI, the only elevation dataset currently available is the Shuttle Radar Topography Mission data which has a 30-meter spatial resolution and 16-meter vertical accuracy (expressed as linear error at 90%). To generate high-resolution digital elevation models (DEMs) in the RMI, elevation information and photographic imagery have been collected from field surveys using GNSS/total station and unmanned aerial vehicles for Structure-from-Motion (SfM) point cloud generation. Digital Globe WorldView II imagery was processed to create SfM point clouds to fill in gaps in the point cloud derived from the higher resolution UAS photos. The combined point cloud data is filtered and classified to bare-earth and georeferenced using the GNSS data acquired on roads and along survey transects perpendicular to the coast. A total station was used to collect elevation data under tree canopies where heavy vegetation cover blocked the view of GNSS satellites. A subset of the GPS / total station data was set aside for error assessment of the resulting DEM.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

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-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

An Observational Study of the Relationship between Cloud, Aerosol and Meteorology in Broken Low-Level Cloud Conditions

NASA Technical Reports Server (NTRS)

Loeb, Norman G.; Schuster, Gregory L.

2008-01-01

Global satellite analyses showing strong correlations between aerosol optical depth and 3 cloud cover have stirred much debate recently. While it is tempting to interpret the results as evidence of aerosol enhancement of cloud cover, other factors such as the influence of meteorology on both the aerosol and cloud distributions can also play a role, as both aerosols and clouds depend upon local meteorology. This study uses satellite observations to examine aerosol-cloud relationships for broken low-level cloud regions off the coast of Africa. The analysis approach minimizes the influence of large-scale meteorology by restricting the spatial and temporal domains in which the aerosol and cloud properties are compared. While distributions of several meteorological variables within 5deg 5deg latitude-longitude regions are nearly identical under low and high aerosol optical depth, the corresponding distributions of single-layer low cloud properties and top-of-atmosphere radiative fluxes differ markedly, consistent with earlier studies showing increased cloud cover with aerosol optical depth. Furthermore, fine-mode fraction and Angstrom Exponent are also larger in conditions of higher aerosol optical depth, even though no evidence of systematic latitudinal or longitudinal gradients between the low and high aerosol optical depth populations are observed. When the analysis is repeated for all 5deg 5deg latitude-longitude regions over the global oceans (after removing cases in which significant meteorological differences are found between the low and high aerosol populations), results are qualitatively similar to those off the coast of Africa.

Effective cloud optical depth and enhancement effects for broken liquid water clouds in Valencia (Spain)

NASA Astrophysics Data System (ADS)

Marín, M. J.; Serrano, D.; Utrillas, M. P.; Núñez, M.; Martínez-Lozano, J. A.

2017-10-01

Partly cloudy skies with liquid water clouds have been analysed, founding that it is essential to distinguish data if the Sun is obstructed or not by clouds. Both cases can be separated considering simultaneously the Cloud Modification Factor (CMF) and the clearness index (kt). For partly cloudy skies and the Sun obstructed the effective cloud optical depth (τ) has been obtained by the minimization method for overcast skies. This method was previously developed by the authors but, in this case, taking into account partial cloud cover. This study has been conducted for the years 2011-2015 with the multiple scattering model SBDART and irradiance measurements for the UV Erythemal Radiation (UVER) and the broadband ranges. Afterwards a statistical analysis of τ has shown that the maximum value is much lower than for overcast skies and there is more discrepancy between the two spectral ranges regarding the results for overcast skies. In order to validate these results the effective cloud optical depth has been correlated with several transmission factors, giving similar fit parameters to those obtained for overcast skies except for the clearness index in the UVER range. As our method is not applicable for partly cloudy skies with the visible Sun, the enhancement of radiation caused by clouds when the Sun is visible has been studied. Results show that the average enhancement CMF values are the same for both ranges although enhancement is more frequent for low cloud cover in the UVER and medium-high cloud cover in the broadband range and it does not depend on the solar zenith angle.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

Cloud cover and horizontal plane eye damaging solar UV exposures.

PubMed

Parisi, A V; Downs, N

2004-11-01

The spectral UV and the cloud cover were measured at intervals of 5 min with an integrated cloud and spectral UV measurement system at a sub-tropical Southern Hemisphere site for a 6-month period and solar zenith angle (SZA) range of 4.7 degrees to approximately 80 degrees . The solar UV spectra were recorded between 280 nm and 400 nm in 0.5 nm increments and weighted with the action spectra for photokeratitis and cataracts in order to investigate the effect of cloud cover on the horizontal plane biologically damaging UV irradiances for cataracts (UVBE(cat)) and photokeratitis (UVBE(pker)). Eighty five percent of the recorded spectra produced a measured irradiance to a cloud free irradiance ratio of 0.6 and higher while 76% produced a ratio of 0.8 and higher. Empirical non-linear expressions as a function of SZA have been developed for all sky conditions to allow the evaluation of the biologically damaging UV irradiances for photokeratitis and cataracts from a knowledge of the unweighted UV irradiances.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size showed an overestimation of in situ LST and some improvement in the daytime Terra and nighttime Aqua biases, with the highest accuracy achieved with the 5x5 window. A comparison between MODIS emmisivity from bands 31, 32, and in situ emissivity showed that emissivity errors (Relative error = -.003) were insignificant.

Automated Visibility & Cloud Cover Measurements with a Solid State Imaging System

DTIC Science & Technology

1989-03-01

GL-TR-89-0061 SIO Ref. 89-7 MPL-U-26/89 AUTOMATED VISIBILITY & CLOUD COVER MEASUREMENTS WITH A SOLID-STATE IMAGING SYSTEM C) to N4 R. W. Johnson W. S...include Security Classification) Automated Visibility & Cloud Measurements With A Solid State Imaging System 12. PERSONAL AUTHOR(S) Richard W. Johnson...based imaging systems , their ics and control algorithms, thus they ar.L discussed sepa- initial deployment and the preliminary application of rately

TH-AB-202-08: A Robust Real-Time Surface Reconstruction Method On Point Clouds Captured From a 3D Surface Photogrammetry System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, W; Sawant, A; Ruan, D

2016-06-15

Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity inmore » local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.« less

Remote sensing of smoke, clouds, and fire using AVIRIS data

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yorman J.; Green, Robert O.

1993-01-01

Clouds remain the greatest element of uncertainty in predicting global climate change. During deforestation and biomass burning processes, a variety of atmospheric gases, including CO2 and SO2, and smoke particles are released into the atmosphere. The smoke particles can have important effects on the formation of clouds because of the increased concentration of cloud condensation nuclei. They can also affect cloud albedo through changes in cloud microphysical properties. Recently, great interest has arisen in understanding the interaction between smoke particles and clouds. We describe our studies of smoke, clouds, and fire using the high spatial and spectral resolution data acquired with the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).

Mapping known and potential mineral occurrences and host rocks in the Bonnifield Mining District using minimal cloud- and snow-cover ASTER data: Chapter E in Recent U.S. Geological Survey studies in the Tintina Gold Province, Alaska, United States, and Yukon, Canada--results of a 5-year project

USGS Publications Warehouse

Hubbard, Bernard E.; Dusel-Bacon, Cynthia; Rowan, Lawrence C.; Eppinger, Robert G.; Gough, Larry P.; Day, Warren C.

2007-01-01

On July 8, 2003, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor acquired satellite imagery of a 60-kilometer-wide swath covering a portion of the Bonnifield mining district within the southernmost part of the Tintina Gold Province, Alaska, under unusually favorable conditions of minimal cloud and snow cover. Although rocks from more than eight different lithotectonic terranes are exposed within the extended swath of data, we focus on volcanogenic massive sulfides (VMS) and porphyry deposits within the Yukon-Tanana terrane (YTT), the largest Mesozoic accretionary terrane exposed between the Denali fault system to the south of Fairbanks and the Tintina fault system to the north of Fairbanks. Comparison of thermal-infrared region (TIR) decorrelation stretch data to available geologic maps indicates that rocks from the YTT contain a wide range of rock types ranging in composition from mafic metavolcanic rocks to felsic rock types such as metarhyolites, pelitic schists, and quartzites. The nine-band ASTER visible-near-infrared region--short-wave infrared region (VNIR-SWIR) reflectance data and spectral matched-filter processing were used to map hydrothermal alteration patterns associated with VMS and porphyry deposit types. In particular, smectite, kaolinite, opaline silica, jarosite and (or) other ferric iron minerals defined narrow (less than 250-meter diameter) zonal patterns around Red Mountain and other potential VMS targets. Using ASTER we identified some of the known mineral deposits in the region, as well as mineralogically similar targets that may represent potential undiscovered deposits. Some known deposits were not identified and may have been obscured by vegetation or snow cover or were too small to be resolved.

Classification by Using Multispectral Point Cloud Data

NASA Astrophysics Data System (ADS)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

NASA Astrophysics Data System (ADS)

Tamiminia, H.; Homayouni, S.; Safari, A.

2015-12-01

Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

Students as Ground Observers for Satellite Cloud Retrieval Validation

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Integrated approach using multi-platform sensors for enhanced high-resolution daily ice cover product

NASA Astrophysics Data System (ADS)

Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean

2016-09-01

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

An energy balance model exploration of the impacts of interactions between surface albedo, cloud cover and water vapor on polar amplification

NASA Astrophysics Data System (ADS)

Södergren, A. Helena; McDonald, Adrian J.; Bodeker, Gregory E.

2017-11-01

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes.

Comparison between MODIS-derived day and night cloud cover and surface observations over the North China Plain

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Tan, Saichun; Shi, Guangyu

2018-02-01

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover (TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and 7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16% higher than the Synop data, and this value was higher at nighttime (15.58%-16.64%) than daytime (12.74%-14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter (29.53%-31.07%) and smallest in summer (4.46%-6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.

Trends in Total Cloud Amount Over China (1951 - 1994)

DOE Data Explorer

Kaiser, Dale P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States).

1999-01-01

These total cloud amount time series for China are derived from the work of Kaiser (1998). The cloud data were extracted from a database of 6-hourly weather observations provided by the National Climate Center of the China Meteorological Administration (CMA) to the U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) through a bilateral research agreement. Surface-observed (visual) six-hourly observations [0200, 0800, 1400, and 2000 Beijing Time (BT)] of cloud amount (0-10 tenths of sky cover) were available from 196 Chinese stations covering the period 1954-94. Data from 1951-1953 were also available; however, they only included 0800, 1400, and 2000 BT observations.

Stereo Cloud Height and Wind Determination Using Measurements from a Single Focal Plane

NASA Astrophysics Data System (ADS)

Demajistre, R.; Kelly, M. A.

2014-12-01

We present here a method for extracting cloud heights and winds from an aircraft or orbital platform using measurements from a single focal plane, exploiting the motion of the platform to provide multiple views of the cloud tops. To illustrate this method we use data acquired during aircraft flight tests of a set of simple stereo imagers that are well suited to this purpose. Each of these imagers has three linear arrays on the focal plane, one looking forward, one looking aft, and one looking down. Push-broom images from each of these arrays are constructed, and then a spatial correlation analysis is used to deduce the delays and displacements required for wind and cloud height determination. We will present the algorithms necessary for the retrievals, as well as the methods used to determine the uncertainties of the derived cloud heights and winds. We will apply the retrievals and uncertainty determination to a number of image sets acquired by the airborne sensors. We then generalize these results to potential space based observations made by similar types of sensors.

Real object-based 360-degree integral-floating display using multiple depth camera

NASA Astrophysics Data System (ADS)

Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam

2015-03-01

A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.

Normalized-Difference Snow Index (NDSI)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.

2010-01-01

The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

HCMM/soil moisture experiment. [relationship between surface minus air temperature differential and available water according to crop type in Canada

NASA Technical Reports Server (NTRS)

Cihlar, J. (Principal Investigator)

1980-01-01

Progress in the compilation and analysis of airborne and ground data to determine the relationship between the maximum surface minus maximum air temperature differential (delta Tsa) and available water (PAW) is reported. Also, results of an analysis of HCMM images to determine the effect of cloud cover on the availability of HCMM-type data are presented. An inverse relationship between delta Tsa and PAW is indicated along with stable delta Tsa vs. PAW distributions for fully developed canopies. Large variations, both geographical and diurnal, in the cloud cover images are reported. The average monthly daytime cloud cover fluctuated between 40 and 60 percent.

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

Filling of Cloud-Induced Gaps for Land Use and Land Cover Classifications Around Refugee Camps

NASA Astrophysics Data System (ADS)

Braun, Andreas; Hagensieker, Ron; Hochschild, Volker

2016-08-01

Clouds cover is one of the main constraints in the field of optical remote sensing. Especially the use of multispectral imagery is affected by either fully obscured data or parts of the image which remain unusable. This study compares four algorithms for the filling of cloud induced gaps in classified land cover products based on Markov Random Fields (MRF), Random Forest (RF), Closest Spectral Fit (CSF) operators. They are tested on a classified image of Sentinel-2 where artificial clouds are filled by information derived from a scene of Sentinel-1. The approaches rely on different mathematical principles and therefore produced results varying in both pattern and quality. Overall accuracies for the filled areas range from 57 to 64 %. Best results are achieved by CSF, however some classes (e.g. sands and grassland) remain critical through all approaches.

Providing Diurnal Sky Cover Data at ARM Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klebe, Dimitri I.

2015-03-06

The Solmirus Corporation was awarded two-year funding to perform a comprehensive data analysis of observations made during Solmirus’ 2009 field campaign (conducted from May 21 to July 27, 2009 at the ARM SGP site) using their All Sky Infrared Visible Analyzer (ASIVA) instrument. The objective was to develop a suite of cloud property data products for the ASIVA instrument that could be implemented in real time and tailored for cloud modelers. This final report describes Solmirus’ research and findings enabled by this grant. The primary objective of this award was to develop a diurnal sky cover (SC) data product utilizingmore » the ASIVA’s infrared (IR) radiometrically-calibrated data and is described in detail. Other data products discussed in this report include the sky cover derived from ASIVA’s visible channel and precipitable water vapor, cloud temperature (both brightness and color), and cloud height inferred from ASIVA’s IR channels.« less

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

NASA Astrophysics Data System (ADS)

Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

2017-09-01

The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm

NASA Astrophysics Data System (ADS)

Frouin, Robert; Deschamps, Pierre-Yves; Ramon, Didier; Steinmetz, François

2012-10-01

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

NASA Technical Reports Server (NTRS)

Savastano, K. J.; Leming, T. D.

1975-01-01

An investigation was conducted to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. The data from the test area was jointly acquired by NASA, the Navy, the Air Force and NOAA/NMFS elements and private and professional fishermen in the northeastern Gulf of Mexico. The data collected has made it possible to identify fisheries significant environmental parameters for white marlin. Prediction models, based on catch data and surface truth information, were developed and demonstrated a potential for significantly reducing search by identifying areas that have a high probability of productivity. Three of the parameters utilized by the models, chlorophyll-a, sea surface temperature, and turbidity were inferred from aircraft sensor data and were tested. Effective use of Skylab data was inhibited by cloud cover and delayed delivery. Initial efforts toward establishing the feasibility of utilizing remotely sensed data to assess and monitor the distribution of oceanic gamefish has successfully identified fisheries significant oceanographic parameters and demonstrated the capability of remotely measuring most of the parameters.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

The Oort cloud

NASA Technical Reports Server (NTRS)

Marochnik, Leonid S.; Mukhin, Lev M.; Sagdeev, Roald Z.

1991-01-01

Views of the large-scale structure of the solar system, consisting of the Sun, the nine planets and their satellites, changed when Oort demonstrated that a gigantic cloud of comets (the Oort cloud) is located on the periphery of the solar system. The following subject areas are covered: (1) the Oort cloud's mass; (2) Hill's cloud mass; (3) angular momentum distribution in the solar system; and (4) the cometary cloud around other stars.

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2006-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze Atmospheric InfraRed Sounder/Advanced Microwave Sounding Unit/Humidity Sounder Brazil (AIRS/AMSU/HSB) data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small and the RMS accuracy of lower tropospheric temperature retrieved with 80 percent cloud cover is about 0.5 K poorer than for clear cases. HSB failed in February 2003, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC (Distributed Active Archive Center) in April 2003 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Shallow cumulus rooted in photosynthesis

NASA Astrophysics Data System (ADS)

Vila-Guerau Arellano, J.; Ouwersloot, H.; Horn, G.; Sikma, M.; Jacobs, C. M.; Baldocchi, D.

2014-12-01

We investigate the interaction between plant evapotranspiration, controlled by photosynthesis (for a low vegetation cover by C3 and C4 grasses), and the moist thermals that are responsible for the formation and development of shallow cumulus clouds (SCu). We perform systematic numerical experiments at fine spatial scales using large-eddy simulations explicitly coupled to a plant-physiology model. To break down the complexity of the vegetation-atmospheric system at the diurnal scales, we design the following experiments with increasing complexity: (a) clouds that are transparent to radiation, (b) clouds that shade the surface from the incoming shortwave radiation and (c) plant stomata whose apertures react with an adjustment in time to cloud perturbations. The shading by SCu leads to a strong spatial variability in photosynthesis and the surface energy balance. As a result, experiment (b) simulates SCu that are characterized by less extreme and less skewed values of the liquid water path and cloud-base height. These findings are corroborated by the calculation of characteristics lengths scales of the thermals and clouds using autocorrelation and spectral analysis methods. We find that experiments (a) and (b) are characterized by similar cloud cover evolution, but different cloud population characteristics. Experiment (b), including cloud shading, is characterized by smaller clouds, but closer to each other. By performing a sensitivity analysis on the exchange of water vapor and carbon dioxide at the canopy level, we show that the larger water-use efficiency of C4 grass leads to two opposing effects that directly influence boundary-layer clouds: the thermals below the clouds are more vigorous and deeper driven by a larger buoyancy surface flux (positive effect), but are characterized by less moisture content (negative effect). We conclude that under the investigated mid-latitude atmospheric and well-watered soil conditions, SCu over C4 grass fields is characterized by larger cloud cover and an enhanced liquid water path compared to C3 grass fields.

Assessment of Photogrammetry Structure-from-Motion Compared to Terrestrial LiDAR Scanning for Generating Digital Elevation Models. Application to the Austre Lovéenbreen Polar Glacier Basin, Spitsbergen 79°N

NASA Astrophysics Data System (ADS)

Tolle, F.; Friedt, J. M.; Bernard, É.; Prokop, A.; Griselin, M.

2014-12-01

Digital Elevation Model (DEM) is a key tool for analyzing spatially dependent processes including snow accumulation on slopes or glacier mass balance. Acquiring DEM within short time intervals provides new opportunities to evaluate such phenomena at the daily to seasonal rates.DEMs are usually generated from satellite imagery, aerial photography, airborne and ground-based LiDAR, and GPS surveys. In addition to these classical methods, we consider another alternative for periodic DEM acquisition with lower logistics requirements: digital processing of ground based, oblique view digital photography. Such a dataset, acquired using commercial off the shelf cameras, provides the source for generating elevation models using Structure from Motion (SfM) algorithms. Sets of pictures of a same structure but taken from various points of view are acquired. Selected features are identified on the images and allow for the reconstruction of the three-dimensional (3D) point cloud after computing the camera positions and optical properties. This cloud point, generated in an arbitrary coordinate system, is converted to an absolute coordinate system either by adding constraints of Ground Control Points (GCP), or including the (GPS) position of the cameras in the processing chain. We selected the opensource digital signal processing library provided by the French Geographic Institute (IGN) called Micmac for its fine processing granularity and the ability to assess the quality of each processing step.Although operating in snow covered environments appears challenging due to the lack of relevant features, we observed that enough reference points could be identified for 3D reconstruction. Despite poor climatic environment of the Arctic region considered (Ny Alesund area, 79oN) is not a problem for SfM, the low lying spring sun and the cast shadows appear as a limitation because of the lack of color dynamics in the digital cameras we used. A detailed understanding of the processing steps is mandatory during the image acquisition phase: compliance with acquisition rules reducing digital processing errors helps minimizing the uncertainty on the point cloud absolute position in its coordinate system. 3D models from SfM are compared with terrestrial LiDAR acquisitions for resolution assesment.

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

NASA Technical Reports Server (NTRS)

Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

2016-01-01

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

Indonesia's Active Mount Agung Volcano Imaged by NASA Spacecraft

NASA Image and Video Library

2017-12-10

After a new small eruption sent an ash cloud 1.24 miles (2 kilometers) into the sky on Dec. 7, 2017, Indonesia's Mount Agung volcano quieted down. This image was acquired Dec. 8 after the latest activity by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument on NASA's Terra satellite. The image shows vegetation in red colors. The summit crater has a hot spot (yellow) as detected by ASTER's thermal infrared channels. More than 65,00 residents continue to be evacuated from the volcano's danger zone in case of a major eruption. The image covers an area of 11 by 12.3 miles (17.8 by 19.8 kilometers), and is located at 8.3 degrees south, 115.5 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA22121

SPIDER: Probing the dawn of time from above the clouds

NASA Astrophysics Data System (ADS)

Moncelsi, Lorenzo; Spider Collaboration

2017-11-01

SPIDER is a balloon-borne microwave polarimeter designed to measure cosmological B-modes on degree angular scales in the presence of Galactic foregrounds. With six independent telescopes housing a total of 2000 detectors in the 90 GHz and 150 GHz frequency bands, SPIDER is the most instantaneously-sensitive CMB polarimeter deployed on the sky to date. SPIDER was successfully launched from McMurdo Station, Antarctica in January 2015 and acquired science data for 16 days. We cover the in-flight performance and present highlights from the ongoing data-analysis. After a successful recovery, the SPIDER team is planning the next flight, featuring one foreground-optimized channel at 280GHz, which will allow us constrain the primordial tensor-mode amplitude at the level of r < 0.03 (99% CL), in the presence of foregrounds.

Concepts for on board satellite image registration. Volume 4: Impact of data set selection on satellite on board signal processing

NASA Technical Reports Server (NTRS)

Ruedger, W. H.; Aanstoos, J. V.; Snyder, W. E.

1982-01-01

The NASA NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. This volume addresses the impact of data set selection on data formatting required for efficient telemetering of the acquired satellite sensor data. More specifically, the FILE algorithm developed by Martin-Marietta provides a means for the determination of those pixels from the data stream effects an improvement in the achievable system throughput. It will be seen that based on the lack of statistical stationarity in cloud cover, spatial distribution periods exist where data acquisition rates exceed the throughput capability. The study therefore addresses various approaches to data compression and truncation as applicable to this sensor mission.

Synergy of Optical and SAR Data for Mapping and Monitoring Mangroves

NASA Astrophysics Data System (ADS)

Monzon, A. K.; Reyes, S. R.; Veridiano, R. K.; Tumaneng, R.; De Alban, J. D.

2016-06-01

Quantitative information on mangrove cover extents is essential in producing relevant resource management plans and conservation strategies. In the Philippines, mangrove rehabilitation was made a priority in relation to disaster risk response and mitigation following the calamities in the coastal communities during typhoon Haiyan/Yolanda; hence, baseline information on the extent of remaining mangrove cover was essential for effective site interventions. Although mangrove cover maps for the country already exists, analysis of mangrove cover changes were limited to the application of fixed annual deforestation rates due to the challenge of acquiring consistent temporal cloud-free optical satellite data over large landscapes. This study presents an initial analysis of SAR and optical imagery combined with field-based observations for detecting mangrove cover extent and changes through a straightforward graphical approach. The analysis is part of a larger study evaluating the synergistic use of time-series L-band SAR and optical data for mapping and monitoring of mangroves. Image segmentation was implemented on the 25-meter ALOS/PALSAR image mosaics, in which the generated objects were subjected to statistical analysis using the software R. In combination with selected Landsat bands, the class statistics from the image bands were used to generate decision trees and thresholds for the hierarchical image classification. The results were compared with global mangrove cover dataset and validated using collected ground truth data. This study developed an integrated replicable approach for analyzing future radar and optical datasets, essential in national level mangrove cover change monitoring and assessment for long-term conservation targets and strategies.

Clouds on Neptune: Motions, Evolution, and Structure

NASA Technical Reports Server (NTRS)

Sromovsky, Larry A.; Morgan, Thomas (Technical Monitor)

2001-01-01

The aims of our original proposal were these: (1) improving measurements of Neptune's circulation, (2) understanding the spatial distribution of cloud features, (3) discovery of new cloud features and understanding their evolutionary process, (4) understanding the vertical structure of zonal cloud patterns, (5) defining the structure of discrete cloud features, and (6) defining the near IR albedo and light curve of Triton. Towards these aims we proposed analysis of existing 1996 groundbased NSFCAM/IRTF observations and nearly simultaneous WFPC2 observations from the Hubble Space Telescope. We also proposed to acquire new observations from both HST and the IRTF.

Classification of Global Urban Centers Using ASTER Data: Preliminary Results From the Urban Environmental Monitoring Program

NASA Astrophysics Data System (ADS)

Stefanov, W. L.; Stefanov, W. L.; Christensen, P. R.

2001-05-01

Land cover and land use changes associated with urbanization are important drivers of global ecologic and climatic change. Quantification and monitoring of these changes are part of the primary mission of the ASTER instrument, and comprise the fundamental research objective of the Urban Environmental Monitoring (UEM) Program. The UEM program will acquire day/night, visible through thermal infrared ASTER data twice per year for 100 global urban centers over the duration of the mission (6 years). Data are currently available for a number of these urban centers and allow for initial comparison of global city structure using spatial variance texture analysis of the 15 m/pixel visible to near infrared ASTER bands. Variance texture analysis highlights changes in pixel edge density as recorded by sharp transitions from bright to dark pixels. In human-dominated landscapes these brightness variations correlate well with urbanized vs. natural land cover and are useful for characterizing the geographic extent and internal structure of cities. Variance texture analysis was performed on twelve urban centers (Albuquerque, Baghdad, Baltimore, Chongqing, Istanbul, Johannesburg, Lisbon, Madrid, Phoenix, Puebla, Riyadh, Vancouver) for which cloud-free daytime ASTER data are available. Image transects through each urban center produce texture profiles that correspond to urban density. These profiles can be used to classify cities into centralized (ex. Baltimore), decentralized (ex. Phoenix), or intermediate (ex. Madrid) structural types. Image texture is one of the primary data inputs (with vegetation indices and visible to thermal infrared image spectra) to a knowledge-based land cover classifier currently under development for application to ASTER UEM data as it is acquired. Collaboration with local investigators is sought to both verify the accuracy of the knowledge-based system and to develop more sophisticated classification models.

Potential reciprocal effect between land use / land cover change and climate change

NASA Astrophysics Data System (ADS)

Daham, Afrah; Han, Dawei; Rico-Ramirez, Miguel

2016-04-01

Land use/land cover (LULC) activity influences climate change and one way to explore climate change is to analyse the change in LULC patterns. Modelling the Spatio-temporal pattern of LULC change requires the use of satellite remote sensing data and aerial photographs with different pre-processing steps. The aim of this research is to analyse the reciprocal effects of LUCC (Land Use and Cover Change) and the climate change on each other in the study area which covers part of Bristol, South Gloucestershire, Bath and Somerset in England for the period (1975-2015). LUCC is assessed using remote sensing data. Three sets of remotely sensed data, LanSAT-1 Multispectral Scanner (MSS) data obtained in (1975 and 1976), LanSAT-5 Thematic Mapper (TM) data obtained in (1984 and 1997), and LandSAT-7 Enhanced Thematic Mapper Plus (ETM+) acquired in (2003 and 2015), with a time span of forty years were used in the study. One of the most common problems in the satellite images is the presence of cloud covers. In this study, the cloud cover problem is handled using a novel algorithm, which is capable of reducing the cloud coverage in the classified images significantly. This study also examines a suite of possible photogrammetry techniques applicable to detect the change in LULC. At the moment photogrammertic techniques are used to derive the ground truth for supervised classification from the high resolution aerial photos which were provided by Ordnance Survey (contract number: 240215) and global mapper for the years in (2001 and 2014). After obtaining the classified images almost free of clouds, accuracy assessment is implemented with the derived classified images using confusion matrix at some ground truth points. Eight classes (Improved grassland, Built up areas and gardens, Arable and horticulture, Broad-leaved / mixed woodland, Coniferous woodland, Oceanic seas, Standing open water and reservoir, and Mountain; heath; bog) have been classified in the chosen study area. Also, CORINE Land Cover (CLC) maps are used to study the environmental changes and to validate the obtained maps from remote sensing and photogrammetry data. On climate change, different sources of climate data were used in this research. Three rainfall datasets from the Global Precipitation Climatology Centre (GPCC), the Climate Research Unit (CRU) and Gridded Estimates of daily Areal Rainfall (CEH-GEAR) in the study area were compared at a resolution of 0.5 degrees. The dataset were available for the operational period 1975-2015. The historically observed rainfall datasets for the study area were obtained from the Met Office Integrated Data Archive System (MIDAS) Land and Marine downloaded through the British Atmospheric Data Centre (BADC) website, which includes the rainfall and the temperature, are collected from all the weather stations in the UK in the last 40 years. Only four gauging stations were available to represent the spatial variability of rainfall within and around the study area. The monthly rainfall time series were evaluated against a dataset based on four rain gauges. These data are processed and analysed statistically to find the changes in climate of the study area in the last 40 years. The potential reciprocal effect between the LULC change and the climate change is done by finding the correlation between LUCC and the variables Rainfall and Temperature. In addition, The Soil and Water Assessment Tool (SWAT) model is used to study the impact of LULC change on the water system and climate.

Sloped terrain segmentation for autonomous drive using sparse 3D point cloud.

PubMed

Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Jeong, Young-Sik; Um, Kyhyun; Sim, Sungdae

2014-01-01

A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, O. B.; Stevens, D. E.

2003-01-01

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

CloudSat Takes a 3D Slice of Hurricane Matthew

NASA Image and Video Library

2016-10-07

NASA's CloudSat flew east of Hurricane Matthew's center on Oct. 6 at 11:30 a.m. PDT (2:30 p.m. EDT), intersecting parts of Matthew's outer rain bands and revealing Matthew's anvil clouds (thick cirrus cloud cover), with cumulus and cumulonimbus clouds beneath (lower image). Reds/pinks are larger water/ice droplets. http://photojournal.jpl.nasa.gov/catalog/PIA21095

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Jiming; Lv, Qiaoyi; Jian, Bida; Zhang, Min; Zhao, Chuanfeng; Fu, Qiang; Kawamoto, Kazuaki; Zhang, Hua

2018-05-01

Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007-2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.

Macrophysical and optical properties of midlatitude high-altitude clouds from 4 ground-based lidars and collocated CALIOP observations

NASA Astrophysics Data System (ADS)

Dupont, J. C.; Haeffelin, M.; Morille, Y.; Noel, V.; Keckhut, P.; Comstock, J.; Winker, D.; Chervet, P.; Roblin, A.

2009-04-01

Cirrus clouds not only play a major role in the energy budget of the Earth-Atmosphere system, but are also important in the hydrological cycle [Stephens et al., 1990; Webster, 1994]. According to satellite passive remote sensing, high-altitude clouds cover as much as 40% of the earth's surface on average (Liou 1986; Stubenrauch et al., 2006) and can reach 70% of cloud cover over the Tropics (Wang et al., 1996; Nazaryan et al., 2008). Hence, given their very large cloud cover, they have a major role in the climate system (Lynch et al. 2001). Cirrus clouds can be classified into three distinct families according to their optical thickness, namely subvisible clouds (OD<0.03), semi-transparent clouds (0.03

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

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 of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

Integration of MODIS Snow, Cloud and Land Area Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

NASA Astrophysics Data System (ADS)

Qualls, R. J.; Woodruff, C.

2017-12-01

The behavior of inter-annual trends in mountain snow cover would represent extremely useful information for drought and climate change assessment; however, individual data sources exhibit specific limitations for characterizing this behavior. For example, SNOTEL data provide time series point values of Snow Water Equivalent (SWE), but lack spatial content apart from that contained in a sparse network of point values. Satellite observations in the visible spectrum can provide snow covered area, but not SWE at present, and are limited by cloud cover which often obscures visibility of the ground, especially during the winter and spring in mountainous areas. Cloud cover, therefore, often limits both temporal and spatial coverage of satellite remote sensing of snow. Among the platforms providing the best combination of temporal and spatial coverage to overcome the cloud obscuration problem by providing frequent overflights, the Aqua and Terra satellites carrying the MODIS instrument package provide 500 m, daily resolution observations of snow cover. These were only launched in 1999 and the early 2000's, thus limiting the historical period over which these data are available. A hybrid method incorporating SNOTEL and MODIS data has been developed which accomplishes cloud removal, and enables determination of the time series of watershed spatial snow cover when either SNOTEL or MODIS data are available. This allows one to generate spatial snow cover information for watersheds with SNOTEL stations for periods both before and after the launch of the Aqua and Terra satellites, extending the spatial information about snow cover over the period of record of the SNOTEL stations present in a watershed. This method is used to quantify the spatial time series of snow over the 9000 km2 Upper Snake River watershed and to evaluate inter-annual trends in the timing, rate, and duration of melt over the nearly 40 year period from the early 1980's to the present, and shows promise for generating snow cover depletion maps for drought and climate change scenarios.

Rocky Mountain Snow

NASA Image and Video Library

2017-12-08

NASA image acquired December 19, 2012 In time for the 2012 winter solstice, a storm dropped snow over most of the Rocky Mountains in the United States. On December 20, the National Weather Service reported snow depths exceeding 100 centimeters (39 inches) in some places—the result of the recent snowfall plus accumulation from earlier storms. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured this natural-color image on December 19, 2012. Clouds had mostly cleared from the region, though some cloud cover lingered over parts of the Pacific Northwest and Colorado. Showing more distinct contours than the clouds, the snow cover stretched across the Rocky Mountains and the surrounding region, from Idaho to Arizona and from California to Colorado. Snowfall did not stop in Colorado, as the storm continued moving eastward across the Midwest. By December 20, 2012, a combination of heavy snow and strong winds had closed schools, iced roads, and delayed flights, complicating plans for holiday travelers. Though troublesome for travel, the snow brought much-needed moisture; multiple cities had set new records for consecutive days without measurable snow, CBS news reported. As of December 18, the U.S. Drought Monitor stated that a substantial portion of the continental United States continued to suffer from drought, and “exceptional” drought conditions extended from South Dakota to southern Texas. NASA image courtesy Jeff Schmaltz, LANCE MODIS Rapid Response. Caption by Michon Scott. Instrument: Aqua - MODIS To read more go to: earthobservatory.nasa.gov/IOTD/view.php?id=80035 Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Seasonal and Non-Seasonal Variations of Jupiter's Atmosphere from Observations of Thermal Emission, 1994-2011

NASA Technical Reports Server (NTRS)

Orton, G.; Fletcher, L.; Yanamandra-Fisher, P.; Greathouse, T.; Fisher, B.; Greco, J.; Wakefield, L.; Snead, E.; Boydstun, K.; Simon-Miller, A.;

Mean winds at the cloud top of Venus obtained from two-wavelength UV imaging by Akatsuki

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Kouyama, Toru; Lee, Yeon Joo; Murakami, Shin-ya; Ogohara, Kazunori; Takagi, Masahiro; Imamura, Takeshi; Nakajima, Kensuke; Peralta, Javier; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2018-01-01

Venus is covered with thick clouds. Ultraviolet (UV) images at 0.3-0.4 microns show detailed cloud features at the cloud-top level at about 70 km, which are created by an unknown UV-absorbing substance. Images acquired in this wavelength range have traditionally been used to measure winds at the cloud top. In this study, we report low-latitude winds obtained from the images taken by the UV imager, UVI, onboard the Akatsuki orbiter from December 2015 to March 2017. UVI provides images with two filters centered at 365 and 283 nm. While the 365-nm images enable continuation of traditional Venus observations, the 283-nm images visualize cloud features at an SO2 absorption band, which is novel. We used a sophisticated automated cloud-tracking method and thorough quality control to estimate winds with high precision. Horizontal winds obtained from the 283-nm images are generally similar to those from the 365-nm images, but in many cases, westward winds from the former are faster than the latter by a few m/s. From previous studies, one can argue that the 283-nm images likely reflect cloud features at higher altitude than the 365-nm images. If this is the case, the superrotation of the Venusian atmosphere generally increases with height at the cloud-top level, where it has been thought to roughly peak. The mean winds obtained from the 365-nm images exhibit local time dependence consistent with known tidal features. Mean zonal winds exhibit asymmetry with respect to the equator in the latter half of the analysis period, significantly at 365 nm and weakly at 283 nm. This contrast indicates that the relative altitude may vary with time and latitude, and so are the observed altitudes. In contrast, mean meridional winds do not exhibit much long-term variability. A previous study suggested that the geographic distribution of temporal mean zonal winds obtained from UV images from the Venus Express orbiter during 2006-2012 can be interpreted as forced by topographically induced stationary gravity waves. However, the geographic distribution of temporal mean zonal winds we obtained is not consistent with that distribution, which suggests that the distribution may not be persistent. [Figure not available: see fulltext.

Mapping with Small UAS: A Point Cloud Accuracy Assessment

NASA Astrophysics Data System (ADS)

Toth, Charles; Jozkow, Grzegorz; Grejner-Brzezinska, Dorota

2015-12-01

Interest in using inexpensive Unmanned Aerial System (UAS) technology for topographic mapping has recently significantly increased. Small UAS platforms equipped with consumer grade cameras can easily acquire high-resolution aerial imagery allowing for dense point cloud generation, followed by surface model creation and orthophoto production. In contrast to conventional airborne mapping systems, UAS has limited ground coverage due to low flying height and limited flying time, yet it offers an attractive alternative to high performance airborne systems, as the cost of the sensors and platform, and the flight logistics, is relatively low. In addition, UAS is better suited for small area data acquisitions and to acquire data in difficult to access areas, such as urban canyons or densely built-up environments. The main question with respect to the use of UAS is whether the inexpensive consumer sensors installed in UAS platforms can provide the geospatial data quality comparable to that provided by conventional systems. This study aims at the performance evaluation of the current practice of UAS-based topographic mapping by reviewing the practical aspects of sensor configuration, georeferencing and point cloud generation, including comparisons between sensor types and processing tools. The main objective is to provide accuracy characterization and practical information for selecting and using UAS solutions in general mapping applications. The analysis is based on statistical evaluation as well as visual examination of experimental data acquired by a Bergen octocopter with three different image sensor configurations, including a GoPro HERO3+ Black Edition, a Nikon D800 DSLR and a Velodyne HDL-32. In addition, georeferencing data of varying quality were acquired and evaluated. The optical imagery was processed by using three commercial point cloud generation tools. Comparing point clouds created by active and passive sensors by using different quality sensors, and finally, by different commercial software tools, provides essential information for the performance validation of UAS technology.

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

NASA Astrophysics Data System (ADS)

Klein, A. G.; Thapa, S.

2017-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS. While it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage quantitative comparisons between their snow products are currently limited. Therefore this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI Snow Cover product at a snow cover fraction of 30% generated binary snow maps most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. Agreement was highest during the winter but lower during late fall and spring. Comparability was lowest over forest. MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicates that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67%, and cloud 65.02% and 59.91%, respectively. Visual comparisons depict good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products. While VIIRS and MODIS have similar capacity to map snow cover, VIIRS has the potential to more accurately map snow cover area for the successive development of climate data records.

Stormy Day at Jupiter

NASA Image and Video Library

2017-05-25

Small bright clouds dot Jupiter's entire south tropical zone in this image acquired by JunoCam on NASA's Juno spacecraft on May 19, 2017, at an altitude of 7,990 miles (12,858 kilometers). Although the bright clouds appear tiny in this vast Jovian cloudscape, they actually are cloud towers roughly 30 miles (50 kilometers) wide and 30 miles (50 kilometers) high that cast shadows on the clouds below. On Jupiter, clouds this high are almost certainly composed of water and/or ammonia ice, and they may be sources of lightning. This is the first time so many cloud towers have been visible, possibly because the late-afternoon lighting is particularly good at this geometry. https://photojournal.jpl.nasa.gov/catalog/PIA21647

Study of the transport parameters of cloud lightning plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Z. S.; Yuan, P.; Zhao, N.

2010-11-15

Three spectra of cloud lightning have been acquired in Tibet (China) using a slitless grating spectrograph. The electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity of the cloud lightning, for the first time, are calculated by applying the transport theory of air plasma. In addition, we investigate the change behaviors of parameters (the temperature, the electron density, the electrical conductivity, the electron thermal conductivity, and the electron thermal diffusivity) in one of the cloud lightning channels. The result shows that these parameters decrease slightly along developing direction of the cloud lightning channel. Moreover, they represent similar suddenmore » change behavior in tortuous positions and the branch of the cloud lightning channel.« less

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models.

PubMed

Medeiros, Brian; Nuijens, Louise

2016-05-31

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection.

Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models

PubMed Central

Nuijens, Louise

2016-01-01

Trade wind regions cover most of the tropical oceans, and the prevailing cloud type is shallow cumulus. These small clouds are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these clouds in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that clouds in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados Cloud Observatory are relevant to clouds across the tropics. The same methods are applied to climate models to evaluate the simulated clouds. The models generally capture the cloud radiative effect, but underestimate cloud cover and show an array of cloud vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of cloud and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to cloud feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. PMID:27185925

Monitoring a boreal wildfire using multi-temporal Radarsat-1 intensity and coherence images

USGS Publications Warehouse

Rykhus, Russell P.; Lu, Zhong

2011-01-01

Twenty-five C-band Radarsat-1 synthetic aperture radar (SAR) images acquired from the summer of 2002 to the summer of 2005 are used to map a 2003 boreal wildfire (B346) in the Yukon Flats National Wildlife Refuge, Alaska under conditions of near-persistent cloud cover. Our analysis is primarily based on the 15 SAR scenes acquired during arctic growing seasons. The Radarsat-1 intensity data are used to map the onset and progression of the fire, and interferometric coherence images are used to qualify burn severity and monitor post-fire recovery. We base our analysis of the fire on three test sites, two from within the fire and one unburned site. The B346 fire increased backscattered intensity values for the two burn study sites by approximately 5–6 dB and substantially reduced coherence from background levels of approximately 0.8 in unburned background forested areas to approximately 0.2 in the burned area. Using ancillary vegetation information from the National Land Cover Database (NLCD) and information on burn severity from Normalized Burn Ratio (NBR) data, we conclude that burn site 2 was more severely burned than burn site 1 and that C-band interferometric coherence data are useful for mapping landscape changes due to fire. Differences in burn severity and topography are determined to be the likely reasons for the observed differences in post-fire intensity and coherence trends between burn sites.

Progressive Mid-latitude Afforestation: Local and Remote Climate Impacts in the Framework of Two Coupled Earth System Models

NASA Astrophysics Data System (ADS)

Lague, Marysa

Vegetation influences the atmosphere in complex and non-linear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, we systematically evaluate the response of climate to linearly increasing the area of forest cover over the northern mid-latitudes. We show that the magnitude of afforestation of the northern mid-latitudes determines the climate response in a non-linear fashion, and identify a threshold in vegetation-induced cloud feedbacks - a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. We identify how vegetation-induced changes in cloud cover further feedback on changes in the global energy balance. We also show how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased (a relationship which has not previously been demonstrated). This work demonstrates that while some climate effects (such as energy transport) of large scale mid-latitude afforestation scale roughly linearly across a wide range of afforestation areas, others (such as the local partitioning of the surface energy budget) are non-linear, and sensitive to the particular magnitude of mid-latitude forcing. Our results highlight the importance of considering both local and remote climate responses to large-scale vegetation change, and explore the scaling relationship between changes in vegetation cover and the resulting climate impacts.

Physics Parameterization for Seasonal Prediction

DTIC Science & Technology

2012-09-30

comparison Project, a joint effort between the Year of Tropical Convection (YOTC) Program and the Global Energy and Water Cycle Experiment (GEWEX) Cloud...unified” representation of the water cycle in the model. One such area is the correspondence between diagnosed cloud cover and prognostic cloud

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2005-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Low cost digital photogrammetry: From the extraction of point clouds by SFM technique to 3D mathematical modeling

NASA Astrophysics Data System (ADS)

Michele, Mangiameli; Giuseppe, Mussumeci; Salvatore, Zito

2017-07-01

The Structure From Motion (SFM) is a technique applied to a series of photographs of an object that returns a 3D reconstruction made up by points in the space (point clouds). This research aims at comparing the results of the SFM approach with the results of a 3D laser scanning in terms of density and accuracy of the model. The experience was conducted by detecting several architectural elements (walls and portals of historical buildings) both with a 3D laser scanner of the latest generation and an amateur photographic camera. The point clouds acquired by laser scanner and those acquired by the photo camera have been systematically compared. In particular we present the experience carried out on the "Don Diego Pappalardo Palace" site in Pedara (Catania, Sicily).

New Perspectives of Point Clouds Color Management - the Development of Tool in Matlab for Applications in Cultural Heritage

NASA Astrophysics Data System (ADS)

Pepe, M.; Ackermann, S.; Fregonese, L.; Achille, C.

2017-02-01

The paper describes a method for Point Clouds Color management and Integration obtained from Terrestrial Laser Scanner (TLS) and Image Based (IB) survey techniques. Especially in the Cultural Heritage (CH) environment, methods and techniques to improve the color quality of Point Clouds have a key role because a homogenous texture brings to a more accurate reconstruction of the investigated object and to a more pleasant perception of the color object as well. A color management method for point clouds can be useful in case of single data set acquired by TLS or IB technique as well as in case of chromatic heterogeneity resulting by merging different datasets. The latter condition can occur when the scans are acquired in different moments of the same day or when scans of the same object are performed in a period of weeks or months, and consequently with a different environment/lighting condition. In this paper, a procedure to balance the point cloud color in order to uniform the different data sets, to improve the chromatic quality and to highlight further details will be presented and discussed.

Spectral Cloud-Filtering of AIRS Data: Non-Polar Ocean

NASA Technical Reports Server (NTRS)

Aumann, Hartmut H.; Gregorich, David; Barron, Diana

2004-01-01

The Atmospheric Infrared Sounder (AIRS) is a grating array spectrometer which covers the thermal infrared spectral range between 640 and 1700/cm. In order to retain the maximum radiometric accuracy of the AIRS data, the effects of cloud contamination have to be minimized. We discuss cloud filtering which uses the high spectral resolution of AIRS to identify about 100,000 of 500,000 non-polar ocean spectra per day as relatively "cloud-free". Based on the comparison of surface channels with the NCEP provided global real time sst (rtg.sst), AIRS surface sensitive channels have a cold bias ranging from O.5K during the day to 0.8K during the night. Day and night spatial coherence tests show that the cold bias is due to cloud contamination. During the day the cloud contamination is due to a 2-3% broken cloud cover at the 1-2 km altitude, characteristic of low stratus clouds. The cloud-contamination effects surface sensitive channels only. Cloud contamination can be reduced to 0.2K by combining the spectral filter with a spatial coherence threshold, but the yield drops to 16,000 spectra per day. AIRS was launched in May 2002 on the Earth Observing System (EOS) Aqua satellite. Since September 2002 it has returned 4 million spectra of the globe each day.

The GFS Atmospheric Model description

Science.gov Websites

model has only one type of cloud cover represented by C. In the tropics the cloudiness is primarily due mainly through grid-scale condensation. The fractional cloud cover C is available at all model levels , 1996: Parameterizations for the absorption of solar radiation by water vapor and ozone. J. Atmos. Sci

Sources of variation in Landsat autocorrelation

NASA Technical Reports Server (NTRS)

Craig, R. G.; Labovitz, M. L.

1980-01-01

Analysis of sixty-four scan lines representing diverse conditions across satellites, channels, scanners, locations and cloud cover confirms that Landsat data are autocorrelated and consistently follow an Arima (1,0,1) pattern. The AR parameter varies significantly with location and the MA coefficient with cloud cover. Maximum likelihood classification functions are considerably in error unless this autocorrelation is compensated for in sampling.

Earth Observations taken by the Expedition 14 crew

NASA Image and Video Library

2006-11-28

ISS014-E-08744 (28 Nov. 2006) --- Mumbai Harbor, India is featured in this image photographed by an Expedition 14 crewmember on the International Space Station. This view is one of three (frames 8741, 8742 and 8744) acquired within ten seconds of each other as the station passed over India. Mumbai (formerly known as Bombay) is a so-called mega city, with over 21 million people living in the greater Mumbai metropolitan region. Mega cities like Tokyo, New York, Sao Paulo, and Mumbai are also known as conurbations -- large contiguous areas of urban land cover formed from the growth and merging together of previously separate and distinct urban centers. The Mumbai conurbation includes several municipal entities including Bhiwandi, Kalyan, Thane, and Ulhasnagar. Located along the coast of western India on Salsette Island, Mumbai is generally considered to be the most modern of India's cities and is a major economic, transportation, and cultural center. Almost cloud-free conditions reveal the continuous urban land cover of the mega city extending north to south across Salsette Island -- a distance of nearly 50 kilometers.

Four years of global cirrus cloud statistics using HIRS

NASA Technical Reports Server (NTRS)

Wylie, Donald P.; Menzel, W. Paul; Woolf, Harold M.; Strabala, Kathleen I.

1994-01-01

Trends in global upper-tropospheric transmissive cirrus cloud cover are beginning to emerge from a four-year cloud climatology using NOAA polar-orbiting High-Resolution Infrared Radiation Sounder (HIRS) multispectral data. Cloud occurrence, height, and effective emissivity are determined with the CO2 slicing technique on the four years of data (June 1989-May 1993). There is a global preponderance of transmissive high clouds, 42% on the average; about three-fourths of these are above 500 hPa and presumed to be cirrus. In the Inter-tropical Convergence Zone (ITCZ), a high frequency of cirrus (greater than 50%) is found at all times; a modest seasonal movement tracks the sun. Large seasonal changes in cloud cover occur over the oceans in the storm belts at midlatitudes; the concentrations of these clouds migrate north and south with the seasons following the progressions of the subtropical highs (anticyclones). More cirrus is found in the summer than in the winter in each hemisphere. A significant change in cirrus cloud cover occurs in 1991, the third year of the study. Cirrus observations increase from 35% to 43% of the data, a change of eight percentage points. Other cloud forms, opaque to terrestrial radiation, decerase by nearly the same amount. Most of the increase is thinner cirrus with infrared optical depths below 0.7. The increase in cirrus happens at the same time as the 1991-92 El Nino/Southern Oscillation (ENSO) and the eruption of Mt. Pinatubo. The cirrus changes occur at the start of the ENSO and persist into 1993 in contrast to other climatic indicators that return to near pre-ENSO and volcanic levels in 1993.

Preliminary verification for application of a support vector machine-based cloud detection method to GOSAT-2 CAI-2

NASA Astrophysics Data System (ADS)

Oishi, Yu; Ishida, Haruma; Nakajima, Takashi Y.; Nakamura, Ryosuke; Matsunaga, Tsuneo

2018-05-01

The Greenhouse Gases Observing Satellite (GOSAT) was launched in 2009 to measure global atmospheric CO2 and CH4 concentrations. GOSAT is equipped with two sensors: the Thermal And Near infrared Sensor for carbon Observations (TANSO)-Fourier transform spectrometer (FTS) and TANSO-Cloud and Aerosol Imager (CAI). The presence of clouds in the instantaneous field of view of the FTS leads to incorrect estimates of the concentrations. Thus, the FTS data suspected to have cloud contamination must be identified by a CAI cloud discrimination algorithm and rejected. Conversely, overestimating clouds reduces the amount of FTS data that can be used to estimate greenhouse gas concentrations. This is a serious problem in tropical rainforest regions, such as the Amazon, where the amount of useable FTS data is small because of cloud cover. Preparations are continuing for the launch of the GOSAT-2 in fiscal year 2018. To improve the accuracy of the estimates of greenhouse gases concentrations, we need to refine the existing CAI cloud discrimination algorithm: Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA1). A new cloud discrimination algorithm using a support vector machine (CLAUDIA3) was developed and presented in another paper. Although the use of visual inspection of clouds as a standard for judging is not practical for screening a full satellite data set, it has the advantage of allowing for locally optimized thresholds, while CLAUDIA1 and -3 use common global thresholds. Thus, the accuracy of visual inspection is better than that of these algorithms in most regions, with the exception of snow- and ice-covered surfaces, where there is not enough spectral contrast to identify cloud. In other words, visual inspection results can be used as truth data for accuracy evaluation of CLAUDIA1 and -3. For this reason visual inspection can be used for the truth metric for the cloud discrimination verification exercise. In this study, we compared CLAUDIA1-CAI and CLAUDIA3-CAI for various land cover types, and evaluated the accuracy of CLAUDIA3-CAI by comparing both CLAUDIA1-CAI and CLAUDIA3-CAI with visual inspection (400 × 400 pixels) of the same CAI images in tropical rainforests. Comparative results between CLAUDIA1-CAI and CLAUDIA3-CAI for various land cover types indicated that CLAUDIA3-CAI had a tendency to identify bright surface and optically thin clouds. However, CLAUDIA3-CAI had a tendency to misjudge the edges of clouds compared with CLAUDIA1-CAI. The accuracy of CLAUDIA3-CAI was approximately 89.5 % in tropical rainforests, which is greater than that of CLAUDIA1-CAI (85.9 %) for the test cases presented here.

Measuring the Internal Structure and Physical Conditions in Star and Planet Forming Clouds Core: Toward a Quantitative Description of Cloud Evolution

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2005-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular cloud cores and investigate the physical conditions which give rise to star and planet formation. The goals of this program are to acquire, reduce and analyze deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds in order to internal structure of starless cloud cores and to quantitatively investigate the evolution of such structure through the star and planet formation process. During the second year of this grant, progress toward these goals is discussed.

Measuring the Internal Structure and Physical Conditions in Star and Planet Forming Clouds Cores: Towards a Quantitative Description of Cloud Evolution

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2004-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular cloud cores and investigate the physical conditions which give rise to star and planet formation. The goals of this program are to acquire, reduce and analyze deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds in order to determine the detailed initial conditions for star formation from quantitative measurements of the internal structure of starless cloud cores and to quantitatively investigate the evolution of such structure through the star and planet formation process.

Liquid water content variation with altitude in clouds over Europe

NASA Astrophysics Data System (ADS)

Andreea, Boscornea; Sabina, Stefan

2013-04-01

Cloud water content is one of the most fundamental measurements in cloud physics. Knowledge of the vertical variability of cloud microphysical characteristics is important for a variety of reasons. The profile of liquid water content (LWC) partially governs the radiative transfer for cloudy atmospheres, LWC profiles improves our understanding of processes acting to form and maintain cloud systems and may lead to improvements in the representation of clouds in numerical models. Presently, in situ airborne measurements provide the most accurate information about cloud microphysical characteristics. This information can be used for verification of both numerical models and cloud remote sensing techniques. The aim of this paper was to analyze the liquid water content (LWC) measurements in clouds, in time of the aircraft flights. The aircraft and its platform ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research is property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania. The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - Cloud, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 m). The processed and analyzed measurements are acquired during 4 flights from Romania (Bucharest, 44°25'57″N 26°06'14″E) to Germany (Berlin 52°30'2″N 13°23'56″E) above the same region of Europe. The flight path was starting from Bucharest to the western part of Romania above Hungary, Austria at a cruse altitude between 6000-8500 m, and after 5 hours reaching Berlin. In total we acquired data during approximately 20 flight hours and we presented the vertical and horizontal LWC variations for different cloud types. The LWC values are similar for each type of cloud to values from literature. The vertical LWC profiles in the atmosphere measured during takeoff and landing of the aircraft have shown their dependence of the meteorological parameters.

Apollo 7 Mission,Clouds

NASA Image and Video Library

1968-10-11

Apollo 7,Cumulus,alto-cumulus,cirrus clouds. Very high oblique. Cloud Cover 50%. Original film magazine was labeled S. Camera Data: Hasselblad 500-C; Lens: Zeiss Planar,F/2.8,80mm; Film Type: Kodak SO-121,Aerial Ektachrome; Filter: Wratten 2A. Flight Date: October 11-12. 1968.

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

NASA Technical Reports Server (NTRS)

Peterson, Thomas C.; Barnett, Tim P.; Roeckner, Erich; Vonder Haar, Thomas H.

1992-01-01

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Lidar Observations of the Optical Properties and 3-Dimensional Structure of Cirrus Clouds

NASA Technical Reports Server (NTRS)

Eloranta, E. W.

1996-01-01

The scientific research conducted under this grant have been reported in a series of journal articles, dissertations, and conference proceedings. This report consists of a compilation of these publications in the following areas: development and operation of a High Spectral Resolution Lidar, cloud physics and cloud formation, mesoscale observations of cloud phenomena, ground-based and satellite cloud cover observations, impact of volcanic aerosols on cloud formation, visible and infrared radiative relationships as measured by satellites and lidar, and scattering cross sections.

On-Board Cryospheric Change Detection By The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Greeley, R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Baker, V.; Dohm, J.; Ip, F.

2004-12-01

The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible/near-IR spectrometer. ASE science activities include autonomous monitoring of cryopsheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. This would have application to the study of cryospheres on Earth, Mars and the icy moons of the outer solar system. A cryosphere classification algorithm, in combination with a previously developed cloud algorithm [1] has been tested on-board ten times from March through August 2004. The cloud algorithm correctly screened out three scenes with total cloud cover, while the cryosphere algorithm detected alpine snow cover in the Rocky Mountains, lake thaw near Madison, Wisconsin, and the presence and subsequent break-up of sea ice in the Barrow Strait of the Canadian Arctic. Hyperion has 220 bands ranging from 400 to 2400 nm, with a spatial resolution of 30 m/pixel and a spectral resolution of 10 nm. Limited on-board memory and processing speed imposed the constraint that only partially processed Level 0.5 data with dark image subtraction and gain factors applied, but not full radiometric calibration. In addition, a maximum of 12 bands could be used for any stacked sequence of algorithms run for a scene on-board. The cryosphere algorithm was developed to classify snow, water, ice and land, using six Hyperion bands at 427, 559, 661, 864, 1245 and 1649 nm. Of these, only 427 nm does overlap with the cloud algorithm. The cloud algorithm was developed with Level 1 data, which introduces complications because of the incomplete calibration of SWIR in Level 0.5 data, including a high level of noise in the 1377 nm band used by the cloud algorithm. Development of a more robust cryosphere classifier, including cloud classification specifically adapted to Level 0.5, is in progress for deployment on EO-1 as part of continued ASE operations. [1] Griffin, M.K. et al., Cloud Cover Detection Algorithm For EO-1 Hyperion Imagery, SPIE 17, 2003.

Relationships between lower tropospheric stability, low cloud cover, and water vapor isotopic composition in the subtropical Pacific

NASA Astrophysics Data System (ADS)

Galewsky, J.

2017-12-01

Understanding the processes that govern the relationships between lower tropospheric stability and low-cloud cover is crucial for improved constraints on low-cloud feedbacks and for improving the parameterizations of low-cloud cover used in climate models. The stable isotopic composition of atmospheric water vapor is a sensitive recorder of the balance of moistening and drying processes that set the humidity of the lower troposphere and may thus provide a useful framework for improving our understanding low-cloud processes. In-situ measurements of water vapor isotopic composition collected at the NOAA Mauna Loa Observatory in Hawaii, along with twice-daily soundings from Hilo and remote sensing of cloud cover, show a clear inverse relationship between the estimated inversion strength (EIS) and the mixing ratios and water vapor δ -values, and a positive relationship between EIS, deuterium excess, and Δ δ D, defined as the difference between an observation and a reference Rayleigh distillation curve. These relationships are consistent with reduced moistening and an enhanced upper-tropospheric contribution above the trade inversion under high EIS conditions and stronger moistening under weaker EIS conditions. The cloud fraction, cloud liquid water path, and cloud-top pressure were all found to be higher under low EIS conditions. Inverse modeling of the isotopic data for the highest and lowest terciles of EIS conditions provide quantitative constraints on the cold-point temperatures and mixing fractions that govern the humidity above the trade inversion. The modeling shows the moistening fraction between moist boundary layer air and dry middle tropospheric air 24±1.5% under low EIS conditions is and 6±1.5% under high EIS conditions. A cold-point (last-saturation) temperature of -30C can match the observations for both low and high EIS conditions. The isotopic composition of the moistening source as derived from the inversion (-114±10‰ ) requires moderate fractionation from a pure marine source, indicating a link between inversion strength and moistening of the lower troposphere from the outflow of shallow convection. This approach can be applied in other settings and the results can be used to test parameterizations in climate models.

E4 True and False Color Hot Spot Mosaic

NASA Image and Video Library

1998-03-06

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial "hotspot" on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter. North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. http://photojournal.jpl.nasa.gov/catalog/PIA00602

Atlantic Multidecadal Oscillation footprint on global high cloud cover

NASA Astrophysics Data System (ADS)

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.

Can Clouds replace Grids? Will Clouds replace Grids?

NASA Astrophysics Data System (ADS)

Shiers, J. D.

2010-04-01

The world's largest scientific machine - comprising dual 27km circular proton accelerators cooled to 1.9oK and located some 100m underground - currently relies on major production Grid infrastructures for the offline computing needs of the 4 main experiments that will take data at this facility. After many years of sometimes difficult preparation the computing service has been declared "open" and ready to meet the challenges that will come shortly when the machine restarts in 2009. But the service is not without its problems: reliability - as seen by the experiments, as opposed to that measured by the official tools - still needs to be significantly improved. Prolonged downtimes or degradations of major services or even complete sites are still too common and the operational and coordination effort to keep the overall service running is probably not sustainable at this level. Recently "Cloud Computing" - in terms of pay-per-use fabric provisioning - has emerged as a potentially viable alternative but with rather different strengths and no doubt weaknesses too. Based on the concrete needs of the LHC experiments - where the total data volume that will be acquired over the full lifetime of the project, including the additional data copies that are required by the Computing Models of the experiments, approaches 1 Exabyte - we analyze the pros and cons of Grids versus Clouds. This analysis covers not only technical issues - such as those related to demanding database and data management needs - but also sociological aspects, which cannot be ignored, neither in terms of funding nor in the wider context of the essential but often overlooked role of science in society, education and economy.

Aerosol-Cloud-Precipitation Interactions over Indo-Gangetic Basin

NASA Technical Reports Server (NTRS)

Tsay, S.-C.; Lau, K. .; Holben, B. N.; Hsu, N. C.; Bhartia, P. K.

2005-01-01

About 60% of world population reside in Asia, in term of which sheer population density presents a major environmental stress. Economic expansion in this region is, in fact, accompanied by increases in bio-fuel burning, industrial pollution, and land cover and land use changes. With a growth rate of approx. 8%/yr for Indian economy, more than 600 million people from Lahore, Pakistan to Calcutta, India over the Indo-Gangetic Basin have particularly witnessed increased frequencies of floods and droughts as well as a dramatic increase in atmospheric loading of aerosols (i.e., anthropogenic and natural aerosol) in recent decades. This regional change (e.g., aerosol, cloud, precipitation, etc.) will constitute a vital part of the global change in the 21st century. Better understanding of the impacts of aerosols in affecting monsoon climate and water cycles is crucial in providing the physical basis to improve monsoon climate prediction and for disaster mitigation. Based on climate model simulations, absorbing aerosols (dust and black carbon) play a critical role in affecting interannual and intraseasonal variability of the Indian monsoon. An initiative on the integrated (aerosols, clouds, and precipitation) measurements approach over the Indo-Gangetic Basin will be discussed. An array of ground-based (e.g., AERONET, MPLNET, SMART-COMMIT, etc.) and satellite (e.g., Terra, A-Train, etc.) sensors will be utilized to acquire aerosol characteristics, sources/sinks, and transport processes during the pre-monsoon (April-May, aerosol forcing) season, and to obtain cloud and precipitation properties during the monsoon (May-June, water cycle response) season. Close collaboration with other international programs, such as ABC, CLIVAR, GEWEX, and CEOP in the region is anticipated.

Fires in the Australian Capital Territory

NASA Technical Reports Server (NTRS)

2003-01-01

The height and extent of billowing smoke plumes from bushfires near Canberra, the Australian capital, are illustrated by these views from the Multi-angle Imaging SpectroRadiometer (MISR). The images were acquired on January 18, 2003. Never before had fires of this magnitude come so close to Australia's capital. Four people lost their lives and over 500 homes were destroyed, mostly in the southwestern suburbs. Australia's famous Mount Stromlo Observatory, located immediately west of the city, was also incinerated by the fires.

The top panel portrays a natural-color view from MISR's nadir camera, in which the eastern portion of the Australian Capital Territory is located south of a pale, ephemeral lake in the upper left-hand corner (Lake George). Several smoke plumes originate within the eastern part of the Australian Capital Territory, while the major plumes originate to the west of the image area. The Australian Capital Territory and much of New South Wales are completely obscured by the smoke, which is driven by fierce westerly winds and extends eastward to the coast and over the Pacific Ocean.

The lower panel provides a stereoscopically retrieved height field of the clouds and smoke plumes. The greenish areas indicate where smoke plumes extend several kilometers above a bank of patchy stratus clouds below. A few high clouds appear near the bottom of the image. Wind retrievals were excluded from this image in order to generate a smooth and continuous field. Although relative height variations are well-represented here, the inclusion of wind retrievals for this scene reduces the actual cloud height results by 1 to 2 kilometers. Areas where heights could not be retrieved are shown as dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuouslyand every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. This data product was generated from a portion of the imagery acquired during Terra orbit 16421. The panels cover an area of 380 kilometers x 253 kilometers, and utilize data from blocks 118 to 120 within World Reference System-2 path 89.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Airborne Sea of Dust over China

NASA Technical Reports Server (NTRS)

2002-01-01

TDust covered northern China in the last week of March during some of the worst dust storms to hit the region in a decade. The dust obscuring China's Inner Mongolian and Shanxi Provinces on March 24, 2002, is compared with a relatively clear day (October 31, 2001) in these images from the Multi-angle Imaging SpectroRadiometer's vertical-viewing (nadir) camera aboard NASA's Terra satellite. Each image represents an area of about 380 by 630 kilometers (236 by 391 miles). In the image from late March, shown on the right, wave patterns in the yellowish cloud liken the storm to an airborne ocean of dust. The veil of particulates obscures features on the surface north of the Yellow River (visible in the lower left). The area shown lies near the edge of the Gobi desert, a few hundred kilometers, or miles, west of Beijing. Dust originates from the desert and travels east across northern China toward the Pacific Ocean. For especially severe storms, fine particles can travel as far as North America. The Multi-angle Imaging SpectroRadiometer, built and managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., is one of five Earth-observing instruments aboard the Terra satellite, launched in December 1999. The instrument acquires images of Earth at nine angles simultaneously, using nine separate cameras pointed forward, downward and backward along its flight path. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles, cloud forms and land surface covers. Image courtesy NASA/GSFC/LaRC/JPL, MISR Team

Multi-Spectral Image Analysis for Improved Space Object Characterization

NASA Astrophysics Data System (ADS)

Duggin, M.; Riker, J.; Glass, W.; Bush, K.; Briscoe, D.; Klein, M.; Pugh, M.; Engberg, B.

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

A Hazy Day in Mexico City

NASA Technical Reports Server (NTRS)

2002-01-01

Mexico City has one of the world's most serious air pollution problems. The city is located atop a high plain at an altitude of 2200 meters, and is surrounded on three sides by mountains and snow-capped volcanoes. Since incident solar radiation does not vary significantly with season at tropical latitudes, photochemical smog is produced much of the year. In winter, air quality can worsen significantly when thermal inversions keep polluted air masses close to the surface.

Atmospheric particulates (aerosols) are readily visible at oblique view angles, and differences in aerosol amount on two days are indicated by these images of central Mexico from the Multi-angle Imaging SpectroRadiometer (MISR). The images at left and center are natural color views acquired by MISR's 70-degree forward-viewing camera on April 9 and December 5, 2001, respectively. Mexico City can be identified in the center panel by the large area of haze accumulation above image center. Two small brighter patches within the hazy area indicate low fog. In the left-hand panel, the city basin appears significantly clearer, but some haze remains apparent across the Sierra Madre mountains in the lower portion of the images. On the right is an elevation field corresponding to the December 5 view. Automated MISR stereoscopic retrievals reveal the clouds at lower right to be at very high altitudes, in contrast to the low-lying haze and fog near Mexico City. When the stereo retrieval determines that a location is not covered by clouds, digital terrain elevation data are displayed instead. High clouds appear as the orange and red areas, and mountainous areas appear light blue and green. The position of the clouds within the 70-degree image are slightly southward of their location in the elevation map as a consequence of geometric parallax.

Major sources of air pollutants within the basin enclosing the Mexico City urban area include exhaust from 3.5 million vehicles, thousands of industries, and mineral dust. The ancient lakebed valley in which Mexico City is situated became a major source of dust when it was drained in the 16th century. The city basin stretches approximately 70 kilometers wide; it is reported that the local air quality causes the surrounding mountains to be rarely visible from the urban center.

The Multi-angle Imaging SpectroRadiometer views almost the entire Earth every 9 days. These images were acquired during Terra orbits 6966 and 10461 and cover an area of 330 kilometers x 464 kilometers. They utilize data from blocks 75 to 77 within World Reference System-2 path 26.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Clouds and Climate Change. Understanding Global Change: Earth Science and Human Impacts. Global Change Instruction Program.

ERIC Educational Resources Information Center

Shaw, Glenn E.

The Global Change Instruction Program was designed by college professors to fill a need for interdisciplinary materials on the emerging science of global change. This instructional module introduces the basic features and classifications of clouds and cloud cover, and explains how clouds form, what they are made of, what roles they play in…

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Maslanik, J. A.; Key, J. R.

1987-01-01

A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Proactive replica checking to assure reliability of data in cloud storage with minimum replication

NASA Astrophysics Data System (ADS)

Murarka, Damini; Maheswari, G. Uma

2017-11-01

The two major issues for cloud storage systems are data reliability and storage costs. For data reliability protection, multi-replica replication strategy which is used mostly in current clouds acquires huge storage consumption, leading to a large storage cost for applications within the loud specifically. This paper presents a cost-efficient data reliability mechanism named PRCR to cut back the cloud storage consumption. PRCR ensures data reliability of large cloud information with the replication that might conjointly function as a price effective benchmark for replication. The duplication shows that when resembled to the standard three-replica approach, PRCR will scale back to consume only a simple fraction of the cloud storage from one-third of the storage, thence considerably minimizing the cloud storage price.

Upper tropospheric cloud systems determined from IR Sounders and their influence on the atmosphere

NASA Astrophysics Data System (ADS)

Stubenrauch, Claudia; Protopapadaki, Sofia; Feofilov, Artem; Velasco, Carola Barrientos

2017-02-01

Covering about 30% of the Earth, upper tropospheric clouds play a key role in the climate system by modulating the Earth's energy budget and heat transport. Infrared Sounders reliably identify cirrus down to an IR optical depth of 0.1. Recently LMD has built global cloud climate data records from AIRS and IASI observations, covering the periods from 2003-2015 and 2008-2015, respectively. Upper tropospheric clouds often form mesoscale systems. Their organization and properties are being studied by (1) distinguishing cloud regimes within 2° × 2° regions and (2) applying a spatial composite technique on adjacent cloud pressures, which estimates the horizontal extent of the mesoscale cloud systems. Convective core, cirrus anvil and thin cirrus of these systems are then distinguished by their emissivity. Compared to other studies of tropical mesoscale convective systems our data include also the thinner anvil parts, which make out about 30% of the area of tropical mesoscale convective systems. Once the horizontal and vertical structure of these upper tropospheric cloud systems is known, we can estimate their radiative effects in terms of top of atmosphere and surface radiative fluxes and by computing their heating rates.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Automated Detection of Geomorphic Features in LiDAR Point Clouds of Various Spatial Density

NASA Astrophysics Data System (ADS)

Dorninger, Peter; Székely, Balázs; Zámolyi, András.; Nothegger, Clemens

2010-05-01

LiDAR, also referred to as laser scanning, has proved to be an important tool for topographic data acquisition. Terrestrial laser scanning allows for accurate (several millimeter) and high resolution (several centimeter) data acquisition at distances of up to some hundred meters. By contrast, airborne laser scanning allows for acquiring homogeneous data for large areas, albeit with lower accuracy (decimeter) and resolution (some ten points per square meter) compared to terrestrial laser scanning. Hence, terrestrial laser scanning is preferably used for precise data acquisition of limited areas such as landslides or steep structures, while airborne laser scanning is well suited for the acquisition of topographic data of huge areas or even country wide. Laser scanners acquire more or less homogeneously distributed point clouds. These points represent natural objects like terrain and vegetation and artificial objects like buildings, streets or power lines. Typical products derived from such data are geometric models such as digital surface models representing all natural and artificial objects and digital terrain models representing the geomorphic topography only. As the LiDAR technology evolves, the amount of data produced increases almost exponentially even in smaller projects. This means a considerable challenge for the end user of the data: the experimenter has to have enough knowledge, experience and computer capacity in order to manage the acquired dataset and to derive geomorphologically relevant information from the raw or intermediate data products. Additionally, all this information might need to be integrated with other data like orthophotos. In all theses cases, in general, interactive interpretation is necessary to determine geomorphic structures from such models to achieve effective data reduction. There is little support for the automatic determination of characteristic features and their statistical evaluation. From the lessons learnt from automated extraction and modeling of buildings (Dorninger & Pfeifer, 2008) we expected that similar generalizations for geomorphic features can be achieved. Our aim is to recognize as many features as possible from the point cloud in the same processing loop, if they can be geometrically described with appropriate accuracy (e.g., as a plane). For this, we propose to apply a segmentation process allowing determining connected, planar structures within a surface represented by a point cloud. It is based on a robust determination of local tangential planes for all points acquired (Nothegger & Dorninger, 2009). It assumes that for points, belonging to a distinct planar structure, similar tangential planes can be determined. In passing, points acquired at continuous such as vegetation can be identified and eliminated. The plane parameters are used to define a four-dimensional feature space which is used to determine seed-clusters globally for the whole are of interest. Starting from these seeds, all points defining a connected, planar region are assigned to a segment. Due to the design of the algorithm, millions of input points can be processed with acceptable processing time on standard computer systems. This allows for processing geomorphically representative areas at once. For each segment, numerous parameter are derived which can be used for further exploitation. These are, for example, location, area, aspect, slope, and roughness. To prove the applicability of our method for automated geomorphic terrain analysis, we used terrestrial and airborne laser scanning data, acquired at two locations. The data of the Doren landslide located in Vorarlberg, Austria, was acquired by a terrestrial Riegl LS-321 laser scanner in 2008, by a terrestrial Riegl LMS-Z420i laser scanner in 2009, and additionally by three airborne LiDAR measurement campaigns, organized by the Landesvermessungsamt Vorarlberg, Feldkirch, in 2003, 2006, and 2007. The measurement distance of the terrestrial measurements was considerably varying considerably because of the various base points that were needed to cover the whole landslide. The resulting point spacing is approximately 20 cm. The achievable accuracy was about 10 cm. The airborne data was acquired with mean point densities of 2 points per square-meter. The accuracy of this dataset was about 15 cm. The second testing site is an area of the Leithagebirge in Burgenland, Austria. The data was acquired by an airborne Riegl LMS-Q560 laser scanner mounted on a helicopter. The mean point density was 6-8 points per square with an accuracy better than 10 cm. We applied our processing chain on the datasets individually. First, they were transformed to local reference frames and fine adjustments of the individual scans respectively flight strips were applied. Subsequently, the local regression planes were determined for each point of the point clouds and planar features were extracted by means of the proposed approach. It turned out that even small displacements can be detected if the number of points used for the fit is enough to define a parallel but somewhat displaced plane. Smaller cracks and erosional incisions do not disturb the plane fitting, because mostly they are filtered out as outliers. A comparison of the different campaigns of the Doren site showed exciting matches of the detected geomorphic structures. Although the geomorphic structure of the Leithagebirge differs from the Doren landslide, and the scales of the two studies were also different, reliable results were achieved in both cases. Additionally, the approach turned out to be highly robust against points which were not located on the terrain. Hence, no false positives were determined within the dense vegetation above the terrain, while it was possible to cover the investigated areas completely with reliable planes. In some cases, however, some structures in the tree crowns were also recognized, but these small patches could be very well sorted out from the geomorphically relevant results. Consequently, it could be verified that a topographic surface can be properly represented by a set of distinct planar structures. Therefore, the subsequent interpretation of those planes with respect to geomorphic characteristics is acceptable. The additional in situ geological measurements verified some of our findings in the sense that similar primary directions could be found that were derived from the LiDAR data set and (Zámolyi et al., 2010, this volume). References: P. Dorninger, N. Pfeifer: "A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds"; Sensors, 8 (2008), 11; 7323 - 7343. C. Nothegger, P. Dorninger: "3D Filtering of High-Resolution Terrestrial Laser Scanner Point Clouds for Cultural Heritage Documentation"; Photogrammetrie, Fernerkundung, Geoinformation, 1 (2009), 53 - 63. A. Zámolyi, B. Székely, G. Molnár, A. Roncat, P. Dorninger, A. Pocsai, M. Wyszyski, P. Drexel: "Comparison of LiDAR derived directional topographic features with geologic field evidence: a case study of Doren landslide (Vorarlberg, Austria)"; EGU General Assembly 2010, Vienna, Austria

Cloud Height Estimation with a Single Digital Camera and Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Carretas, Filipe; Janeiro, Fernando M.

2014-05-01

Clouds influence the local weather, the global climate and are an important parameter in the weather prediction models. Clouds are also an essential component of airplane safety when visual flight rules (VFR) are enforced, such as in most small aerodromes where it is not economically viable to install instruments for assisted flying. Therefore it is important to develop low cost and robust systems that can be easily deployed in the field, enabling large scale acquisition of cloud parameters. Recently, the authors developed a low-cost system for the measurement of cloud base height using stereo-vision and digital photography. However, due to the stereo nature of the system, some challenges were presented. In particular, the relative camera orientation requires calibration and the two cameras need to be synchronized so that the photos from both cameras are acquired simultaneously. In this work we present a new system that estimates the cloud height between 1000 and 5000 meters. This prototype is composed by one digital camera controlled by a Raspberry Pi and is installed at Centro de Geofísica de Évora (CGE) in Évora, Portugal. The camera is periodically triggered to acquire images of the overhead sky and the photos are downloaded to the Raspberry Pi which forwards them to a central computer that processes the images and estimates the cloud height in real time. To estimate the cloud height using just one image requires a computer model that is able to learn from previous experiences and execute pattern recognition. The model proposed in this work is an Artificial Neural Network (ANN) that was previously trained with cloud features at different heights. The chosen Artificial Neural Network is a three-layer network, with six parameters in the input layer, 12 neurons in the hidden intermediate layer, and an output layer with only one output. The six input parameters are the average intensity values and the intensity standard deviation of each RGB channel. The output parameter in the output layer is the cloud height estimated by the ANN. The training procedure was performed, using the back-propagation method, in a set of 260 different clouds with heights in the range [1000, 5000] m. The training of the ANN has resulted in a correlation ratio of 0.74. This trained ANN can therefore be used to estimate the cloud height. The previously described system can also measure the wind speed and direction at cloud height by measuring the displacement, in pixels, of a cloud feature between consecutively acquired photos. Also, the geographical north direction can be estimated using this setup through sequential night images with high exposure times. A further advantage of this single camera system is that no camera calibration or synchronization is needed. This significantly reduces the cost and complexity of field deployment of cloud height measurement systems based on digital photography.

Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

NASA Astrophysics Data System (ADS)

Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

2010-05-01

Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the MODIS optical satellite sensor can be used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a MODIS pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete satellite images database was extracted from the U.S. MODIS/NASA website (http://modis.gsfc.nasa.gov/) for MOD09_B1 Reflectance images, and from the MODIS/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (Aqua Platform). The MOD9 Image reflectance and MOD10_A2 products were respectively analyzed to retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

A Cloudy Day on Mars

NASA Technical Reports Server (NTRS)

2002-01-01

(Released 23 April 2002) The Science This image, centered near 49.7 N and 43.0 W (317.0 E), displays splotchy water ice clouds that obscure the surface. Most of Mars was in a relatively clear period when this image was acquired, which is why many of the other THEMIS images acquired during the same period do not have obvious signs of atmospheric dust or water ice clouds. This image is far enough north to catch the edge of the north polar hood that develops during the northern winter. This is a cap of water ice and CO₂ ice clouds that form over the Martian north pole. Mars has a number of interesting atmospheric phenomena which THEMIS will be able to view in addition to water ice clouds, including dust devils, dust storms, and tracking atmospheric temperatures with the infrared camera. The Story Anyone who's been on an airplane in a storm knows how clouds on Earth can block the view below. The thin water ice clouds on Mars might make things slightly blurry, but at least we can still see the surface. While the surface features may not be as clear in this image, it's actually kind of fascinating to see clouds at work, because we can get a sense of how the north pole on Mars influences the weather and the climate. In this image, the north pole is responsible for the presence of the clouds. Made of water ice and carbon dioxide, these clouds 'mist out' in a atmospheric 'hood' that caps the surface during the northern Martian winter, hiding it from full view of eager observers here on Earth.

Tracking Hurricane Wilma Across the Caribbean

NASA Technical Reports Server (NTRS)

2005-01-01

Information on cloud top heights at different stages in the life cycle of the rapidly intensifying Hurricane Wilma may prove useful for evaluating the ability of numerical weather models to predict the intensity changes of hurricanes. NASA's Multi-angle Imaging SpectroRadiometer (MISR) acquired this sequence of images and cloud-top height observations for Hurricane Wilma as it progressed across the Caribbean in October 2005. Each pair in the sequence has a photo-like view of the storm on the left and a matching color-coded image of cloud-top height on the right. Cloud-top heights range from 0 (purple) to 18 (red) kilometers altitude. Areas where cloud heights could not be determined are shown in dark gray.

The pair on the left show Wilma on Tuesday, October 18, when Hurricane watches were posted for Cuba and Mexico. The central pair shows the eye of Hurricane Wilma just hours before the storm began to cross the Yucatan Peninsula on Friday, October 21. At that time, Wilma was a powerful Category 4 Hurricane on the Saffir-Simpson scale, and had a minimum recorded central pressure of 930 millibars. Hurricane Wilma surged from tropical storm to Category 5 hurricane status in record time, but the storm slowed and weakened considerably after battering Mexico's Yucatan Peninsula and the Caribbean. The right-hand image pair displays the eastern edges of a weakened Wilma, when Wilma had been reduced to Category 2 status and was just starting to reach southern Florida on the morning of Sunday, October 23. Wilma gathered speed and strengthened on Sunday night, crossing Florida as a Category 3 storm on Monday, October 24.

On the 18th, Wilma looked a bit ragged. Its eye is located at the center of the left edge, and its outer bands of clouds appear to be dominated by a rather loose collection of thunderstorms. In the photo-like images, these look like areas of 'boiling clouds,' and in the cloud-height image, these appear as orange blobs, sometimes topped with pinkish-red. On October 21 (center), when Wilma was a Category 4 storm, cloud-top height on the eastern side of the storm near the eye reached 18 kilometers in altitude, with lower heights on the western side. The image from the 23rd shows the eastern edge of Wilma as it approached Florida (upper right) and Cuba (center right).

MISR has nine different cameras which view the Earth from a variety of angles. Shifts in the clouds' apparent position from one camera's perspective to another's allows MISR to measure the height of the cloud-tops. MISR scientists have programmed computers to compare the different views, identify features that appear to shift from view to view, and use that information to calculate cloud height automatically. The height fields pictured have not been corrected for the effects of cloud motion. Wind-corrected heights (which have higher accuracy but sparser spatial coverage) are within about 1 kilometer of the heights shown here.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the entire globe between 82o north and 82o south latitude every nine days. Each image covers an area of about 380 kilometers by 1830 kilometers. The data products were generated from a portion of the imagery acquired during Terra orbits 31037, 31081 and 31110, and utilize data from within blocks 68-83 within World Reference System-2 paths 13, 16 and 18, respectively.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission Directorate, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is managed for NASA by the California Institute of Technology.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Discharge forecasts in mountain basins based on satellite snow cover mapping. [Dinwoody Creek Basin, Wyoming and the Dischma Basin, Switzerland

NASA Technical Reports Server (NTRS)

Martinec, J.; Rango, A. (Principal Investigator)

1980-01-01

The author has identified the following significant results. A snow runoff model developed for European mountain basins was used with LANDSAT imagery and air temperature data to simulate runoff in the Rocky Mountains under conditions of large elevation range and moderate cloud cover (cloud cover of 40% or less during LANDSAT passes 70% of the time during a snowmelt season). Favorable results were obtained for basins with area not exceeding serval hundred square kilometers and with a significant component of subsurface runoff.

Use of satellite data in runoff forecasting in the heavily forested, cloud-covered Pacific Northwest. [Upper Snake, Boise, Dworshak, Libby and Hungry Horse River Basins

NASA Technical Reports Server (NTRS)

Dillard, J. P.; Orwig, C. F. (Principal Investigator)

1980-01-01

The author has identified the following significant results. Satellite-derived snow cover data improves forecasts of stream flow but not at a statistically significant amount and should not be used exclusively because of persistent cloud cover. Based upon reconstruction runs, satellite data can be used to augment snow-flight data in the Upper Snake, Boise, Dworshak, and Hungry Horse basins. Satellite data does not compare well with aerial snow-flight data in the Libby basin.

Local effects of partly cloudy skies on solar and emitted radiations

NASA Technical Reports Server (NTRS)

Whitney, D. A.; Venable, D. D.

1981-01-01

Solar radiation measurements are made on a routine basis. Global solar, atmospheric emitted, downwelled diffuse solar, and direct solar radiation measurement systems are fully operational with the first two in continuous operation. Fractional cloud cover measurements are made from GOES imagery or from ground based whole sky photographs. Normalized global solar irradiance values for partly cloudy skies were correlated to fractional cloud cover.

Two Methods for Retrieving UV Index for All Cloud Conditions from Sky Imager Products or Total SW Radiation Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badosa, Jordi; Calbo, J.; McKenzie, R. L.

2014-07-01

In the present study, we assess the cloud effects on UV Index (UVI) and total solar radiation (TR) as a function of cloud cover estimations and sunny conditions (from sky imaging products) as well as of solar zenith angle (SZA). These analyses are undertaken for a southern-hemisphere mid-latitude site where a 10-years dataset is available. It is confirmed that clouds reduce TR more than UV, in particular for obscured Sun conditions, low cloud fraction (< 60%) and large SZA (> 60º). Similarly, clouds enhance TR more than UV, mainly for visible Sun conditions, large cloud fraction and large SZA. Twomore » methods to estimate UVI are developed: 1) from sky imaging cloud cover and sunny conditions, and 2) from TR measurements. Both methods may be used in practical operational applications, although Method 2 shows overall the best performance, since TR allows accounting for cloud optical properties. The mean absolute differences of Method 2 estimations with respect to measured values are 0.17 UVI units (for 1-minute data) and 0.79 Standard Erythemal Dose (SED) units (for daily integrations). Method 1 shows less accurate results but it is still suitable to estimate UVI: mean absolute differences are 0.37 UVI units and 1.6 SED.« less

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE PAGES

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.; ...

2017-04-26

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

Monitoring the Seasonal Evolution of the North and South Polar Vortex on Titan during 10 Years with Cassini/Vims

NASA Astrophysics Data System (ADS)

Le Mouelic, S.; Rousseau, B.; Rodriguez, S.; Cornet, T.; Sotin, C.; Barnes, J. W.; Brown, R. H.; Buratti, B. J.; Baines, K. H.; Clark, R. N.; Nicholson, P. D.

2014-12-01

Cassini entered in Saturn's orbit in July 2004. In ten years, more than 100 targeted flybys of Titan have been performed. We focus our study on the comprehensive analysis of the Visual and Infrared Mapping Spectrometer data set acquired between 2004 and 2014, with a particular emphasis on the atmospheric polar features. First evidences for a vast ethane cloud covering the North Pole have been detected as soon as the second targeted flyby in December 2005 [1]. The first detailed imaging of this north polar feature with VIMS was obtained in December 2006, thanks to a change in inclination of the spacecraft orbit [2]. At this time, the northern lakes and seas of Titan were totally masked to the optical instruments by the haze and clouds, whereas the southern pole was well illuminated and mostly clear of haze and vast clouds. Subsequent flybys revealed that the vast north polar feature was progressively vanishing around the equinox in 2009 [2,3,4], in agreement with the predictions of Global Circulation Models [5]. It revealed progressively the underlying lakes to the ISS and VIMS instruments. First evidences of an atmospheric vortex growing over the South Pole occurred in May 2012, with a high altitude feature detected at each flybys since then. In this study, we have computed individual global maps of the north and south poles for each of the 100 targeted flybys, using VIMS wavelengths sensitive both to clouds and surface features. This allows a more complete monitoring of the evolution of the north polar cloud than was previously done before using a selection of individual flybys only. It also provides a detailed investigation of what is currently acting over the South Pole. [1] Griffith et al., Science, 2006. [2] Le Mouélic et al., PSS, 2012. [3] Rodriguez et al., Nature, 2009. [4] Rodriguez et al., Icarus 2011. [5] Rannou et al., Science 2005

Analysis and modeling of summertime convective cloud and precipitation structure over the Southeastern United States

NASA Technical Reports Server (NTRS)

Knupp, Kevin R.

1991-01-01

A summary of an investigation of deep convective cloud systems that typify the summertime subtropical environment of northern Alabama is presented. The major portion of the research effort included analysis of data acquired during the 1986 Cooperative Huntsville Meteorological Experiment (COHMEX), which consisted of the joint programs Satellite Precipitation and Cloud Experiment (SPACE) under NASA direction, the Microburst and Service Thunderstorm (MIST) Program under NSF sponsorship, and the FAA-Lincoln Laboratory Weather Study (FLOWS). This work relates closely to the SPACE component of COHMEX, one of the general goals of which was to further the understanding of kinematic and precipitation structure of convective cloud systems. The special observational plateforms that were available under the SPACE/COHMEX Program are shown. The original objectives included studies of both isolated deep convection and of (small) mesoscale convection systems that are observed in the Southeast environment. In addition, it was proposed to include both observational and comparative numerical modeling studies of these characteristic cloud systems. Changes in scope were made during the course of this investigation to better accommodate both the manpower available and the data that was acquired. A greater emphasis was placed on determination of the internal structure of small mesoscale convective systems, and the relationship of internal dynamical and microphysical processes to the observed cloud top behavior as inferred from GOES IR (30 min) data. The major accomplishments of this investigation are presented.

Skylab

NASA Image and Video Library

1973-09-01

This Earth Resource Experiment Package (EREP) photograph of the Uncompahgre area of Colorado was electronically acquired in September of 1973 by the Multi-spectral Scarner, Skylab Experiment S192. EREP images were used to analyze the vegetation conditions and landscape characteristic of this area. Skylab's Earth sensors played the dual roles of gathering information about the planet and perfecting instruments and techniques for future satellites and manned stations. An array of six fixed cameras, another for high resolution, and the astronauts' handheld cameras photographed surface features. Other instruments, recording on magnetic tape, measured the reflectivity of plants, soils, and water. Radar measured the altitude of land and water surfaces. The sensors' objectives were to survey croplands and forests, identify soils and rock types, map natural features and urban developments, detect sediments and the spread of pollutants, study clouds and the sea, and determine the extent of snow and ice cover.

Geologic interpretation of space shuttle radar images of Indonesia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sabing, F.F.

1983-11-01

The National Aeronautics and Space Administration (NASA) space shuttle mission in November 1981 acquired images of parts of the earth with a synthetic aperture radar system at a wavelength of 23.5 cm (9.3 in.) and spatial resolution of 38 m (125 ft). This report describes the geologic interpretation of 1:250,000-scale images of Irian Jaya and eastern Kalimantan, Indonesia, where the all-weather capability of radar penetrates the persistent cloud cover. The inclined look direction of radar enhances subtle topographic features that may be the expression of geologic structures. On the Indonesian images, the following terrain categories are recognizable for geologic mapping:more » carbonate, clastic, volcanic, alluvial and coastal, melange, and metamorphic, as well as undifferentiated bedrock. Regional and local geologic structures are well expressed on the images.« less

Evapotranspiration over spatially extensive plant communities in the Big Cypress National Preserve, southern Florida, 2007-2010

USGS Publications Warehouse

Shoemaker, W. Barclay; Lopez, Christian D.; Duever, Michael J.

2011-01-01

Net radiation and available energy explained most of the variability in ET observed at all five sites. Mean annual and monthly net radiation varied among the sites in response to cloud cover and the albedo of the land surface and plant community. Net radiation was greatest at the Cypress Swamp site, averaging about 130 W/m2 (watts per square meter) during the 3-year study. Net radiation was generally less at the Dwarf Cypress site, averaging about 115 W/m2 over 3 years. The Dwarf Cypress site apparently has the largest albedo, which likely is due to the sparse canopy and a highly reflective, calcareous, periphyton-covered land surface. Furthermore, mean annual net radiation was least in the first year of the study, which likely was due to greater cloud cover during a relatively wet year. In contrast, net radiation was greatest in the second year of the study, which likely was due to less cloud cover during a relatively dry year.

Twenty-four year record of Northern Hemisphere snow cover derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm is enhanced. Trends in annual averages are similar, decreasing at rates of approximately 2% per decade. The only region where the passive microwave data consistently indicate snow and the visible data do not is over the Tibetan Plateau and surrounding mountain areas. In the effort to determine the accuracy of the microwave algorithm over this region we are acquiring surface snow observations through a collaborative study with CAREERI/Lanzhou. In order to provide an optimal snow cover product in the future, we are developing a procedure that blends snow extent maps derived from MODIS data with snow water equivalent maps derived from both SSM/I and AMSR.

Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud

PubMed Central

Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Sim, Sungdae

2014-01-01

A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame. PMID:25093204

Atmospheric Soundings from AIRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert

2004-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correlation coefficients and the prediction of location and intensity of cyclones.

Current results from AlRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert; Barnet, Christopher; Blaisdell, Jon; Iredell, Lena; Bri, Genia; Jusem, Juan Carlos; Keita, Fricky; Kouvaris, Louis; Molnar, Gyula

2004-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correction coefficients and the prediction of location and intensity of cyclones.

Cloud Cover

ERIC Educational Resources Information Center

Schaffhauser, Dian

2012-01-01

This article features a major statewide initiative in North Carolina that is showing how a consortium model can minimize risks for districts and help them exploit the advantages of cloud computing. Edgecombe County Public Schools in Tarboro, North Carolina, intends to exploit a major cloud initiative being refined in the state and involving every…

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2012 CFR

2012-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2014 CFR

2014-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

15 CFR 908.8 - Maintenance of records.

Code of Federal Regulations, 2013 CFR

2013-01-01

... activity during each operational period (e.g., cumulus clouds between 10,000 and 30,000 feet m.s.l.; ground... weather modification activity during each operational period (e.g., cumulus clouds between 10,000 and 30... operation; for example: Percent of cloud cover, temperature, humidity, the presence of lightning, hail...

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

DTIC Science & Technology

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Kloster, S.; Roeckner, E.; Zhang, J.

2007-07-01

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.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

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

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

Smoke over Hudson Bay

NASA Image and Video Library

2017-12-08

A vigorous summer fire season continued through July, 2013 as many large wildfires continued to burn in the forests of northern Canada. The high fire activity not only laid waste to thousands of hectares of boreal forest, but sent thick smoke billowing high into the atmosphere, where it was carried far across the Atlantic Ocean. On July 30, the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this true-color image of a river of smoke spreading south across the Hudson Bay. The blue background is formed by the waters of Hudson Bay. In the southeast the green, forest-covered land of Quebec province peeks from under a large cloud bank. Another large bank of white cloud covers the water in the southwest, and a smaller cloud bank covers the territory of Nunavut in the northwest. A bit of Baffin Island can be seen near the top center of the image. Looking closely at the image, it appears that the gray smoke mixes with whiter cloud in the south, suggesting they may be at the same level in the atmosphere. In the northeast corner of the image, a ribbon of smoke appears to blow over a bank of popcorn clouds as well as over a few lower-lying clouds, causing some of the clouds to appear gray beneath the smoky veil. Where cloud meets smoke in the northeast, however, the line of the cloud bank remains sharp, while the smoke appears to continue traveling under the edge. Although these interpretations are somewhat subjective in this true-color image, the false-color image of the same scene (not shown here) lends strength to the interpretation. Data from other NASA instruments, designed to measure cloud height and characteristics, agree that clouds vary in height, and that smoke mingles with cloud in the south. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Human amplification of drought-driven fire in tropical regions

NASA Astrophysics Data System (ADS)

Tosca, Michael

2015-04-01

The change in globally-measured radiative forcing from the pre-industrial to the present due to interactions between aerosol particles and cloud cover has the largest uncertainty of all anthropogenic factors. Uncertainties are largest in the tropics, where total cloud amount and incoming solar radiation are highest, and where 50% of all aerosol emissions originate from anthropogenic fire. It is well understood that interactions between smoke particles and cloud droplets modify cloud cover , which in turn affects climate, however, few studies have observed the temporal nature of aerosol-cloud interactions without the use of a model. Here we apply a novel approach to measure the effect of fire aerosols on convective clouds in tropical regions (Brazil, Africa and Indonesia) through a combination of remote sensing and meteorological data. We attribute a reduction in cloud fraction during periods of high aerosol optical depths to a smoke-driven inhibition of convection. We find that higher smoke burdens limit vertical updrafts, increase surface pressure, and increase low- level divergence-meteorological indicators of convective suppression. These results are corroborated by climate model simulations that show a smoke-driven increase in regionally averaged shortwave tropospheric heating and boundary layer stratification, and a decrease in vertical velocity and precipitation during the fire season (December-February). We then quantify the human response to decreased cloud cover using a combination of socioeconomic and climate data Our results suggest that, in tropical regions, anthropogenic fire initiates a positive feedback loop where increased aerosol emissions limit convection, dry the surface and enable increased fire activity via human ignition. This result has far-reaching implications for fire management and climate policy in emerging countries along the equator that utilize fire.

Aerosols and their influence on radiation partitioning and savanna productivity in northern Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanniah, K. D.; Beringer, J.; Tapper, N. J.

2010-05-01

We investigated the effect of aerosols and clouds on the Net Ecosystem Productivity (NEP) of savannas in northern Australia using aerosol optical depth, clouds and radiation data from the Atmospheric Radiation Measurement (ARM) site in Darwin and carbon flux data measured from eddy covariance techniques from a site at Howard Springs, 35km southeast of Darwin. Generally we found that the concentration of aerosols in this region was relatively low than observed at other sites, therefore the proportion of diffuse radiation reaching the earths surface was only ~ 30%. As a result, we observed only a modest change in carbon uptakemore » under aerosol laden skies and there was no significant difference for dry season Radiation Use Efficiency (RUE) between clear sky, aerosols or thin clouds. On the other hand thick clouds in the wet season produce much more diffuse radiation than aerosols or thin clouds and therefore the initial canopy quantum efficiency was seen to increase 45 and 2.5 times more than under thin clouds and aerosols respectively. The normalized carbon uptake under thick clouds is 57% and 50% higher than under aerosols and thin clouds respectively even though the total irradiance received under thick clouds was reduced 59% and 50% than under aerosols and thin clouds respectively. However, reduction in total irradiance decreases the mean absolute carbon uptake as much as 22% under heavy cloud cover compared to thin clouds or aerosols. Thus, any increase in aerosol concentration or cloud cover that can enhance the diffuse component may have large impacts on productivity in this region.« less

Evaluation of ERA-interim and MERRA Cloudiness in the Southern Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.

2014-01-01

The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.

Effects of Cloud Properties on PM2.5 Levels in the Southeastern United States

NASA Astrophysics Data System (ADS)

Yu, C.; Zhang, X.; Liu, Y.

2012-12-01

The spatial and temporal characteristics of fine particulate matter (PM2.5) are increasingly being derived from satellite aerosol remote sensing data. A major concern of satellite-derived PM2.5 information is cloud cover, i.e., PM2.5 mass concentrations cannot be estimated from satellite observations under cloudy conditions. There has been little research on the effects of cloud properties on PM2.5 levels. In this study, we performed a statistical analysis of relationships between various cloud parameters and PM2.5 concentrations. We used 2005-2010 PM2.5 observations from 8 sites in the Southeastern Aerosol Research and Characterization (SEARCH) Network, and cloud parameters from MODIS cloud product retrievals from Terra and Aqua satellites. We find that cloud fraction (CF) is generally negatively correlated with the mean value of PM2.5 mass concentration. However, the largest mean value occurs when the cloud fraction is between 10% and 30% instead of lower cloud cover (CF < 10%). The mean value of PM2.5 decreased from 14.3μg/m3 during 10%~30% cloud fraction to 9.3μg/m3 in cloudy days (CF=100%), and the negative correlation is more significant during the summer and fall than spring and winter. In addition, Cloud top pressure (CTP) and cloud optical thickness (COT) also influence PM2.5 mass concentration, with CTP being positively correlated with PM2.5 while COT being negatively correlated. These results suggest that cloud parameters may be used as predictor variables in satellite models of PM2.5.

Absorption of solar energy heats up our planet's surface and the atmosphere and makes life for us po

NASA Technical Reports Server (NTRS)

2002-01-01

Credit: Image courtesy Barbara Summey, NASA Goddard Visualization Analysis Lab, based upon data processed by Takmeng Wong, CERES Science Team, NASA Langley Research Center Satellite: Terra Sensor: CERES Image Date: 09-30-2001 VE Record ID: 11546 Description: Absorption of solar energy heats up our planet's surface and the atmosphere and makes life for us possible. But the energy cannot stay bound up in the Earth's environment forever. If it did then the Earth would be as hot as the Sun. Instead, as the surface and the atmosphere warm, they emit thermal longwave radiation, some of which escapes into space and allows the Earth to cool. This false-color image of the Earth was produced on September 30, 2001, by the Clouds and the Earth's Radiant Energy System (CERES) instrument flying aboard NASA's Terra spacecraft. The image shows where more or less heat, in the form of longwave radiation, is emanating from the top of Earth's atmosphere. As one can see in the image, the thermal radiation leaving the oceans is fairly uniform. The blue swaths across the central Pacific represent thick clouds, the tops of which are so high they are among the coldest places on Earth. In the American Southwest, which can be seen in the upper righthand corner of the globe, there is often little cloud cover to block outgoing radiation and relatively little water to absorb solar energy. Consequently, the amount of outgoing radiation in the American Southwest exceeds that of the oceans. Also, that region was experiencing an extreme heatwave when these data were acquired. Recently, NASA researchers discovered that incoming solar radiation and outgoing thermal radiation increased in the tropics from the 1980s to the 1990s. (Click to read the press release .) They believe that the reason for the unexpected increase has to do with an apparent change in circulation patterns around the globe, which effectively reduced the amount of water vapor and cloud cover in the upper reaches of the atmosphere. Without the clouds, more sunlight was allowed to enter the tropical zones and more thermal energy was allowed to leave. The findings may have big implications for climate change and future global warming. 'This suggests that the tropical heat engine increased its speed,' observes Dr. Bruce Wielicki, of NASA Langley Research Center. 'It's as if the heat engine in the tropics has become less efficient, using more fuel in the 1990s than in the 1980s.'

Temperature Calculations in the Coastal Modeling System

DTIC Science & Technology

2017-04-01

tide) and river discharge at model boundaries, wave radiation stress, and wind forcing over a model computational domain. Physical processes calculated...calculated in the CMS using the following meteorological parameters: solar radiation, cloud cover, air temperature, wind speed, and surface water temperature...during a clear (i.e., cloudless) sky (Wm-2); CLDC is the cloud cover fraction (0-1.0); SWR is the surface reflection coefficient; and SHDf is the

Origin and causes of the mammoth steppe: a story of cloud cover, woolly mammal tooth pits, buckles, and inside-out Beringia

NASA Astrophysics Data System (ADS)

Dale Guthrie, R.

2001-01-01

To account for the vastness of the northern arid steppes during Glacial episodes, I propose the proximate key variable was simply frequent clear skies. This hitherto under-emphasized point is the hub which best explains many questions. Low maritime cloud cover best accounts for today's tundra, and in a related way, the cloudy Polar Front accounts for the whole of the taiga. Even during Glacial maxima, the proximity of the sea to the Bering isthmus created intermittent maritime cloud cover. This regional cloud cover produced an ecological interruption, or buckle, of the arid steppe belt. While this Beringian mesic buckle did not serve as an intercontinental ecological barrier to most steppe-adapted species, it does seem to have limited the distributions of woolly rhinos, camels, American kiangs, short-faced bears, badgers, and some others. At the beginning of the Holocene, this narrow refugium seems to have been a source of some mesic-adapted species which colonized westward into the now tundra vegetation of northern Asia and eastward into northern North America. This Holocene expansion from a limited and regional Pleistocene refugium created our present misconceptions about Beringia. The mid-strait mesic ecological conditions were the exception to the more extensive, arid-adapted, communities of the Mammoth Steppe.

Cloud Occurrence Measurements Over Sea during the 2nd 7 Southeast Asian Studies (7SEAS) Field Campaign in Palawan Archipelago

NASA Astrophysics Data System (ADS)

Antioquia, C. T.; Uy, S. N.; Caballa, K.; Lagrosas, N.

2014-12-01

Ground based sky imaging cameras have been used to measure cloud cover over an area to aid in radiation budget models. During daytime, certain clouds tend to help decrease atmospheric temperature by obstructing sunrays in the atmosphere. Thus, the detection of clouds plays an important role in the formulation of radiation budget in the atmosphere. In this study, a wide angled sky imager (GoPro Hero 2) was brought on board M/Y Vasco to detect and quantity cloud occurrence over sea during the 2nd 7SEAS field campaign. The camera is just a part of a number of scientific instruments used to measure weather, aerosol chemistry and solar radiation among others. The data collection started during the departure from Manila Bay on 05 September 2012 and went on until the end of the cruise (29 September 2012). The camera was placed in a weather-proof box that is then affixed on a steel mast where other instruments are also attached during the cruise. The data has a temporal resolution of 1 minute, and each image is 500x666 pixels in size. Fig. 1a shows the track of the ship during the cruise. The red, blue, hue, saturation, and value of the pixels are analysed for cloud occurrence. A pixel is considered to "contain" thick cloud if it passes all four threshold parameters (R-B, R/B, R-B/R+B, HSV; R is the red pixel color value, blue is the blue pixel color value, and HSV is the hue saturation value of the pixel) and considered thin cloud if it passes two or three parameters. Fig. 1b shows the daily analysis of cloud occurrence. Cloud occurrence here is quantified as the ratio of the pixels with cloud to the total number of pixels in the data image. The average cloud cover for the days included in this dataset is 87%. These measurements show a big contrast when compared to cloud cover over land (Manila Observatory) which is usually around 67%. During the duration of the cruise, only one day (September 6) has an average cloud occurrence below 50%; the rest of the days have averages of 66% or higher - 98% being the highest. This result would then give a general trend of how cloud occurrences over land and over sea differ in the South East Asian region. In this study, these cloud occurrences come from local convection and clouds brought about by Southwest Monsoon winds.

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II; Cloud Fraction and Radiative Forcing

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Minnis, Patrick

2006-01-01

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.

Geologic Mapping and Mineral Resource Assessment of the Healy and Talkeetna Mountains Quadrangles, Alaska Using Minimal Cloud- and Snow-Cover ASTER Data

USGS Publications Warehouse

Hubbard, Bernard E.; Rowan1, Lawrence C.; Dusel-Bacon, Cynthia; Eppinger, Robert G.

2007-01-01

On July 8, 2003, ASTER acquired satellite imagery of a 60 km-wide swath of parts of two 1:250,000 Alaska quadrangles, under favorable conditions of minimal cloud- and snow-cover. Rocks from eight different lithotectonic terranes are exposed within the swath of data, several of which define permissive tracts for various mineral deposit types such as: volcanic-hosted massive sulfides (VMS) and porphyry copper and molybdenum. Representative rock samples collected from 13 different lithologic units from the Bonnifield mining district within the Yukon-Tanana terrane (YTT), plus hydrothermally altered VMS material from the Red Mountain prospect, were analyzed to produce a spectral library spanning the VNIR-SWIR (0.4 - 2.5 ?m) through the TIR (8.1 - 11.7 ?m). Comparison of the five-band ASTER TIR emissivity and decorrelation stretch data to available geologic maps indicates that rocks from the YTT display the greatest range and diversity of silica composition of the mapped terranes, ranging from mafic rocks to silicic quartzites. The nine-band ASTER VNIR-SWIR reflectance data and spectral matched-filter processing were used to map several lithologic sequences characterized by distinct suites of minerals that exhibit diagnostic spectral features (e.g. chlorite, epidote, amphibole and other ferrous-iron bearing minerals); other sequences were distinguished by their weathering characteristics and associated hydroxyl- and ferric-iron minerals, such as illite, smectite, and hematite. Smectite, kaolinite, opaline silica, jarosite and/or other ferric iron minerals defined narrow (< 250 m diameter) zonal patterns around Red Mountain and other potential VMS targets. Using ASTER we identified some of the known mineral deposits in the region, as well as mineralogically similar targets that may represent potential undiscovered deposits. Some known deposits were not identified and may have been obscured by vegetation- or snow-cover, or were too small to be resolved.

Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery

NASA Astrophysics Data System (ADS)

Nascimento, Wilson R.; Souza-Filho, Pedro Walfir M.; Proisy, Christophe; Lucas, Richard M.; Rosenqvist, Ake

2013-01-01

Mapping and monitoring mangrove ecosystems is a crucial objective for tropical countries, particularly where human disturbance occurs and because of uncertainties associated with sea level and climatic fluctuation. In many tropical regions, such efforts have focused largely on the use of optical data despite low capture rates because of persistent cloud cover. Recognizing the ability of Synthetic Aperture Radar (SAR) for providing cloud-free observations, this study investigated the use of JERS-1 SAR and ALOS PALSAR data, acquired in 1996 and 2008 respectively, for mapping the extent of mangroves along the Brazilian coastline, from east of the Amazon River mouth, Pará State, to the Bay of São José in Maranhão. For each year, an object-orientated classification of major land covers (mangrove, secondary vegetation, gallery and swamp forest, open water, intermittent lakes and bare areas) was performed with the resulting maps then compared to quantify change. Comparison with available ground truth data indicated a general accuracy in the 2008 image classification of all land covers of 96% (kappa = 90.6%, tau = 92.6%). Over the 12 year period, the area of mangrove increased by 718.6 km2 from 6705 m2 to 7423.60 km2, with 1931.0 km² of expansion and 1213 km² of erosion noted; 5493 km² remained unchanged in extent. The general accuracy relating to changes in mangroves was 83.3% (Kappa 66.1%; tau 66.7%). The study confirmed that these mangroves constituted the largest continuous belt globally and were experiencing significant change because of the dynamic coastal environment and the influence of sedimentation from the Amazon River along the shoreline. The study recommends continued observations using combinations of SAR and optical data to establish trends in mangrove distributions and implications for provision of ecosystem services (e.g., fish/invertebrate nurseries, carbon storage and coastal protection).

Automatic registration of terrestrial point clouds based on panoramic reflectance images and efficient BaySAC

NASA Astrophysics Data System (ADS)

Kang, Zhizhong

2013-10-01

This paper presents a new approach to automatic registration of terrestrial laser scanning (TLS) point clouds utilizing a novel robust estimation method by an efficient BaySAC (BAYes SAmpling Consensus). The proposed method directly generates reflectance images from 3D point clouds, and then using SIFT algorithm extracts keypoints to identify corresponding image points. The 3D corresponding points, from which transformation parameters between point clouds are computed, are acquired by mapping the 2D ones onto the point cloud. To remove false accepted correspondences, we implement a conditional sampling method to select the n data points with the highest inlier probabilities as a hypothesis set and update the inlier probabilities of each data point using simplified Bayes' rule for the purpose of improving the computation efficiency. The prior probability is estimated by the verification of the distance invariance between correspondences. The proposed approach is tested on four data sets acquired by three different scanners. The results show that, comparing with the performance of RANSAC, BaySAC leads to less iterations and cheaper computation cost when the hypothesis set is contaminated with more outliers. The registration results also indicate that, the proposed algorithm can achieve high registration accuracy on all experimental datasets.

Comparison of the different approaches to generate holograms from data acquired with a Kinect sensor

NASA Astrophysics Data System (ADS)

Kang, Ji-Hoon; Leportier, Thibault; Ju, Byeong-Kwon; Song, Jin Dong; Lee, Kwang-Hoon; Park, Min-Chul

2017-05-01

Data of real scenes acquired in real-time with a Kinect sensor can be processed with different approaches to generate a hologram. 3D models can be generated from a point cloud or a mesh representation. The advantage of the point cloud approach is that computation process is well established since it involves only diffraction and propagation of point sources between parallel planes. On the other hand, the mesh representation enables to reduce the number of elements necessary to represent the object. Then, even though the computation time for the contribution of a single element increases compared to a simple point, the total computation time can be reduced significantly. However, the algorithm is more complex since propagation of elemental polygons between non-parallel planes should be implemented. Finally, since a depth map of the scene is acquired at the same time than the intensity image, a depth layer approach can also be adopted. This technique is appropriate for a fast computation since propagation of an optical wavefront from one plane to another can be handled efficiently with the fast Fourier transform. Fast computation with depth layer approach is convenient for real time applications, but point cloud method is more appropriate when high resolution is needed. In this study, since Kinect can be used to obtain both point cloud and depth map, we examine the different approaches that can be adopted for hologram computation and compare their performance.

Infrared Extinction and the Initial Conditions For Star and Planet Formation

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2003-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular clouds and investigate the physical conditions which give rise to star and planet formation. The goals of the this program are to: 1) acquire deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds, 2) reduce and analyze the data obtained in order to produce detailed extinction maps of the clouds, 3) prepare results, where appropriate, for publication.

Infrared Extinction and the Initial Conditions for Star and Planet Formation

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2002-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular clouds and investigate the physical conditions which give rise to star and planet formation. The goals of the this program are to: (1) acquire deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds; (2) reduce and analyze the data obtained in order to produce detailed extinction maps of the clouds; and (3) prepare results, where appropriate, for publication.

Cloud Statistics for NASA Climate Change Studies

NASA Technical Reports Server (NTRS)

Wylie, Donald P.

1999-01-01

The Principal Investigator participated in two field experiments and developed a global data set on cirrus cloud frequency and optical depth to aid the development of numerical models of climate. Four papers were published under this grant. The accomplishments are summarized: (1) In SUCCESS (SUbsonic aircraft: Contrail & Cloud Effects Special Study) the Principal Investigator aided weather forecasters in the start of the field program. A paper also was published on the clouds studied in SUCCESS and the use of the satellite stereographic technique to distinguish cloud forms and heights of clouds. (2) In SHEBA (Surface Heat Budget in the Arctic) FIRE/ACE (Arctic Cloud Experiment) the Principal Investigator provided daily weather and cloud forecasts for four research aircraft crews, NASA's ER-2, UCAR's C-130, University of Washington's Convert 580, and the Canadian Atmospheric Environment Service's Convert 580. Approximately 105 forecasts were written. The Principal Investigator also made daily weather summaries with calculations of air trajectories for 54 flight days in the experiment. The trajectories show where the air sampled during the flights came from and will be used in future publications to discuss the origin and history of the air and clouds sampled by the aircraft. A paper discussing how well the FIRE/ACE data represent normal climatic conditions in the arctic is being prepared. (3) The Principal Investigator's web page became the source of information for weather forecasting by the scientists on the SHEBA ship. (4) Global Cirrus frequency and optical depth is a continuing analysis of global cloud cover and frequency distribution are being made from the NOAA polar orbiting weather satellites. This analysis is sensitive to cirrus clouds because of the radiative channels used. During this grant three papers were published which describe cloud frequencies, their optical properties and compare the Wisconsin FM Cloud Analysis to other global cloud data such as the International Satellite Cloud Climatology Program (ISCCP) and the Stratospheric Aerosol and Gas Experiment (SAGE). A summary of eight years of HIRS data will be published in late 1998. Important information from this study are: 1) cirrus clouds cover most of the earth, 2) they are found about 40% of the time globally, 3) in the tropics cirrus cloud frequencies are even higher, from 80-100%, 4) there is slight evidence that cirnis cloud cover is increasing in the northern hemisphere at about 0.5% per year, and 5) cirrus clouds have an average infrared transmittance of about 40% of the terrestrial radiation. (5) Global Cloud Frequency Statistics published on the Principal Investigator's web page have been used in the planning of the future CRYSTAL experiment and have been used for refinements of a global numerical model operated at the Colorado State University.

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

CO observations of dark clouds in Lupus

NASA Technical Reports Server (NTRS)

Murphy, D. C.; Cohen, R.; May, J.

1986-01-01

C-12O observations covering 170 square degrees toward the southern T Association Lupus have revealed the presence of an extended physically related complex of dark clouds which have recently formed low mass stars. The estimated mass of the clouds (about 30,000 solar masses) is comparable to that of the nearby Ophiuchus dust clouds. The Lupus clouds are projected onto a gap between two subgroups of the Scorpio-Centaurus OB association suggesting that this long accepted subgrouping may require reinterpretation.

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

DOE Data Explorer

Shupe, Matthew

2013-05-22

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

Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

USGS Publications Warehouse

Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, A. Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

2016-01-01

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

Quantitative Measures of Immersion in Cloud and the Biogeography of Cloud Forests

NASA Technical Reports Server (NTRS)

Lawton, R. O.; Nair, U. S.; Ray, D.; Regmi, A.; Pounds, J. A.; Welch, R. M.

2010-01-01

Sites described as tropical montane cloud forests differ greatly, in part because observers tend to differ in their opinion as to what constitutes frequent and prolonged immersion in cloud. This definitional difficulty interferes with hydrologic analyses, assessments of environmental impacts on ecosystems, and biogeographical analyses of cloud forest communities and species. Quantitative measurements of cloud immersion can be obtained on site, but the observations are necessarily spatially limited, although well-placed observers can examine 10 50 km of a mountain range under rainless conditions. Regional analyses, however, require observations at a broader scale. This chapter discusses remote sensing and modeling approaches that can provide quantitative measures of the spatiotemporal patterns of cloud cover and cloud immersion in tropical mountain ranges. These approaches integrate remote sensing tools of various spatial resolutions and frequencies of observation, digital elevation models, regional atmospheric models, and ground-based observations to provide measures of cloud cover, cloud base height, and the intersection of cloud and terrain. This combined approach was applied to the Monteverde region of northern Costa Rica to illustrate how the proportion of time the forest is immersed in cloud may vary spatially and temporally. The observed spatial variation was largely due to patterns of airflow over the mountains. The temporal variation reflected the diurnal rise and fall of the orographic cloud base, which was influenced in turn by synoptic weather conditions, the seasonal movement of the Intertropical Convergence Zone and the north-easterly trade winds. Knowledge of the proportion of the time that sites are immersed in clouds should facilitate ecological comparisons and biogeographical analyses, as well as land use planning and hydrologic assessments in areas where intensive on-site work is not feasible.

Power availability at terrestrial receptor sites for laser-power transmission from the satellite power system

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1982-01-01

A statistical model was developed for relating the temporal transmission parameters of a laser beam from a solar power satellite to observable meteorological data to determine the influence of weather on power reception at the earth-based receiver. Sites within 100 miles of existing high voltage transmission lines were examined and the model was developed for clear-sky and clouded conditions. The cases of total transmission through clouds at certain wavelengths, no transmission, and partial transmission were calculated for the cloud portion of the model. The study covered cirriform, stratiform, cumiliform, and mixed type clouds and the possibility of boring holes through the clouds with the beam. Utilization of weapons-quality beams for hole boring, was found to yield power availability increases of 9-33%, although no beneficial effects could be predicted in regions of persistent cloud cover. An efficiency of 80% was determined as possible if several receptor sites were available within 200-300 miles of each other, thereby allowing changes of reception point in cases of unacceptable meteorological conditions.

Titan's atmosphere (clouds and composition): new results

NASA Astrophysics Data System (ADS)

Griffith, C. A.

Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200 % on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9 % of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering ≤1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection might govern their evolution. Their short lives point to the presence of rain.

Near-Field Deformation Associated with the South Napa Earthquake (M 6.0) Using Differential Airborne LiDAR

NASA Astrophysics Data System (ADS)

Hudnut, K. W.; Glennie, C. L.; Brooks, B. A.; Hauser, D. L.; Ericksen, T.; Boatwright, J.; Rosinski, A.; Dawson, T. E.; Mccrink, T. P.; Mardock, D. K.; Hoirup, D. F., Jr.; Bray, J.

2014-12-01

Pre-earthquake airborne LiDAR coverage exists for the area impacted by the M 6.0 South Napa earthquake. The Napa watershed data set was acquired in 2003, and data sets were acquired in other portions of the impacted area in 2007, 2010 and 2014. The pre-earthquake data are being assessed and are of variable quality and point density. Following the earthquake, a coalition was formed to enable rapid acquisition of post-earthquake LiDAR. Coordination of this coalition took place through the California Earthquake Clearinghouse; consequently, a commercial contract was organized by Department of Water Resources that allowed for the main fault rupture and damaged Browns Valley area to be covered 16 days after the earthquake at a density of 20 points per square meter over a 20 square kilometer area. Along with the airborne LiDAR, aerial imagery was acquired and will be processed to form an orthomosaic using the LiDAR-derived DEM. The 'Phase I' airborne data were acquired using an Optech Orion M300 scanner, an Applanix 200 GPS-IMU, and a DiMac ultralight medium format camera by Towill. These new data, once delivered, will be differenced against the pre-earthquake data sets using a newly developed algorithm for point cloud matching, which is improved over prior methods by accounting for scan geometry error sources. Proposed additional 'Phase II' coverage would allow repeat-pass, post-earthquake coverage of the same area of interest as in Phase I, as well as an addition of up to 4,150 square kilometers that would potentially allow for differential LiDAR assessment of levee and bridge impacts at a greater distance from the earthquake source. Levee damage was reported up to 30 km away from the epicenter, and proposed LiDAR coverage would extend up to 50 km away and cover important critical lifeline infrastructure in the western Sacramento River delta, as well as providing full post-earthquake repeat-pass coverage of the Napa watershed to study transient deformation.

Earth Limb taken by the Expedition 17 Crew

NASA Image and Video Library

2008-07-22

ISS017-E-011603 (22 July 2008) --- Layers of Earth's atmosphere, brightly colored as the sun rises over central Asia, and Polar Mesospheric Clouds (also known as noctilucent clouds) are featured in this image photographed by an Expedition 17 crewmember on the International Space Station. The image was acquired in support of International Polar Year research.

Forty-year (1971-2010) semiquantitative observations of visibility-cloud-precipitation in Korea and its implication for aerosol effects on regional climate.

PubMed

Lee, Hyo-Jung; Kang, Jeong-Eon; Kim, Cheol-Hee

2015-07-01

Forty-year (1971-2010) observations of cloud cover and types have been analyzed, and implications on the effects of aerosol-cloud feedback were explored. Cloud cover and types have been observed over Korea on the basis of visible (human-eye) attributes without any change in official observing instructions. Visibility has been used as an ongoing proxy measure of aerosol concentrations, and observed meteorological variables such as sunshine duration and precipitation have been employed to analyze aerosol causes and implications for urban and regional climate. The analysis revealed persistent decade-long patterns in Korea: steadily reduced visibility (-0.37 km/yr), consistently decreasing sunshine duration (-0.06 %/hr), and declining occurrence of light precipitation. Spatial distributions of sunshine duration and visibility exhibited more localized variations in the early period (1971-1990), and tended to be more uniform throughout Korea over more recent years (1991-2010), implying the recent regional-scale impact of cloud change over northeast Asia. Cloud analysis results showed that the five most common types were stratocumulus (Sc), cirrus (Ci), altostratus (As), stratus (St), and nimbostratus (Ns), with occurrences of 33%, 17%, 17%, 9%, and 8%, respectively. Occurrence of rarely precipitating or nonprecipitating low-level Sc clouds showed an increasing (+0.34%/yr), but no (or only minor) effects of aerosols on heavy precipitation such as cumulus cloud types were found. Cloud cover in the range of 6/10 to 8/10 units has increased by 31.5±6.5%, and occurrences of both cloud-free (~2/10 units) and overcast (~8/10 units) conditions have decreased. Aerosol-cloud-precipitations interaction is highly nonlinear due to feedback mechanisms. One reason for our poor understanding of the aerosol-cloud feedback study is the variety of cloud types with their complicated responses to variations of the aerosol. Our study on the response of precipitation-cloud to long-term anthropogenic aerosols over 40 years (1971-2010) in South Korea demonstrated that recent changes tend to be at a regional scale, and change in stratocumulus clouds is the most significant. In addition, the changes in cloud-relevant meteorological variables such as sunshine duration and light precipitation were not consistent with expected local anthropogenic aerosol after 1990, implying the importance of long range transboundary influence on a regional or larger than urban scale over the recent years in the northeast Asian region.

Casting Light and Shadows on a Saharan Dust Storm

NASA Technical Reports Server (NTRS)

2003-01-01

On March 2, 2003, near-surface winds carried a large amount of Saharan dust aloft and transported the material westward over the Atlantic Ocean. These observations from the Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite depict an area near the Cape Verde Islands (situated about 700 kilometers off of Africa's western coast) and provide images of the dust plume along with measurements of its height and motion. Tracking the three-dimensional extent and motion of air masses containing dust or other types of aerosols provides data that can be used to verify and improve computer simulations of particulate transport over large distances, with application to enhancing our understanding of the effects of such particles on meteorology, ocean biological productivity, and human health.

MISR images the Earth by measuring the spatial patterns of reflected sunlight. In the upper panel of the still image pair, the observations are displayed as a natural-color snapshot from MISR's vertical-viewing (nadir) camera. High-altitude cirrus clouds cast shadows on the underlying ocean and dust layer, which are visible in shades of blue and tan, respectively. In the lower panel, heights derived from automated stereoscopic processing of MISR's multi-angle imagery show the cirrus clouds (yellow areas) to be situated about 12 kilometers above sea level. The distinctive spatial patterns of these clouds provide the necessary contrast to enable automated feature matching between images acquired at different view angles. For most of the dust layer, which is spatially much more homogeneous, the stereoscopic approach was unable to retrieve elevation data. However, the edges of shadows cast by the cirrus clouds onto the dust (indicated by blue and cyan pixels) provide sufficient spatial contrast for a retrieval of the dust layer's height, and indicate that the top of layer is only about 2.5 kilometers above sea level.

Motion of the dust and clouds is directly observable with the assistance of the multi-angle 'fly-over' animation (Below). The frames of the animation consist of data acquired by the 70-degree, 60-degree, 46-degree and 26-degree forward-viewing cameras in sequence, followed by the images from the nadir camera and each of the four backward-viewing cameras, ending with 70-degree backward image. Much of the south-to-north shift in the position of the clouds is due to geometric parallax between the nine view angles (rather than true motion), whereas the west-to-east motion is due to actual motion of the clouds over the seven minutes during which all nine cameras observed the scene. MISR's automated data processing retrieved a primarily westerly (eastward) motion of these clouds with speeds of 30-40 meters per second. Note that there is much less geometric parallax for the cloud shadows owing to the relatively low altitude of the dust layer upon which the shadows are cast (the amount of parallax is proportional to elevation and a feature at the surface would have no geometric parallax at all); however, the westerly motion of the shadows matches the actual motion of the clouds. The automated processing was not able to resolve a velocity for the dust plume, but by manually tracking dust features within the plume images that comprise the animation sequence we can derive an easterly (westward) speed of about 16 meters per second. These analyses and visualizations of the MISR data demonstrate that not only are the cirrus clouds and dust separated significantly in elevation, but they exist in completely different wind regimes, with the clouds moving toward the east and the dust moving toward the west.

[figure removed for brevity, see original site]

(Click on image above for high resolution version)

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17040. The panels cover an area of about 312 kilometers x 242 kilometers, and use data from blocks 74 to 77 within World Reference System-2 path 207.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Air Modeling - Observational Meteorological Data

EPA Pesticide Factsheets

Observed meteorological data for use in air quality modeling consist of physical parameters that are measured directly by instrumentation, and include temperature, dew point, wind direction, wind speed, cloud cover, cloud layer(s), ceiling height,

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter subsetting, reformatting, and re-projection of the data.

Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

NASA Astrophysics Data System (ADS)

Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

2017-12-01

The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

NASA Technical Reports Server (NTRS)

Susskind, Joel; Rosenberg, Robert I.; Iredell, Lena

2015-01-01

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

Cloud removing method for daily snow mapping over Central Asia and Xinjiang, China

NASA Astrophysics Data System (ADS)

Yu, Xiaoqi; Qiu, Yubao; Guo, Huadong; Chen, Lijuan

2017-02-01

Central Asia and Xinjiang, China are conjunct areas, located in the hinterland of the Eurasian continent, where the snowfall is an important water resource supplement form. The induced seasonal snow cover is vita factors to the regional energy and water balance, remote sensing plays a key role in the snow mapping filed, while the daily remote sensing products are normally contaminated by the occurrence of cloud, that obviously obstacles the utility of snow cover parameters. In this paper, based on the daily snow product from Moderate Resolution Imaging Spectroradiometer (MODIS A1), a cloud removing method was developed by considering the regional snow distribution characteristics with latitude and altitude dependence respectively. In the end, the daily cloud free products was compared with the same period of eight days MODIS standard product, revealing that the cloud free snow products are reasonable, while could provide higher temporal resolution, and more details over Center Asia and Xinjiang Province.

Hayman Fire, Colorado

NASA Technical Reports Server (NTRS)

2002-01-01

The Hayman forest fire, started on June 8, is continuing to burn in the Pike National Forest, 57 km (35 miles) south-southwest of Denver. According to the U.S. Forest Service, the fire has consumed more than 90,000 acres and has become Colorado's worst fire ever. In this ASTER image, acquired Sunday, June 16, 2002 at 10:30 am MST, the dark blue area is burned vegetation and the green areas are healthy vegetation. Red areas are active fires, and the blue cloud at the top center is smoke. Meteorological clouds are white. The image covers an area of 32.2 x 35.2 km (20.0 x 21.8 miles), and displays ASTER bands 8-3-2 in red, green and blue.

This image was acquired on June 16, 2002 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet.

ASTER is one of five Earth-observing instruments launched December 18,1999, on NASA's Terra satellite. The instrument was built by Japan's Ministry of Economy, Trade and Industry. A joint U.S./Japan science team is responsible for validation and calibration of the instrument and the data products. Dr. Anne Kahle at NASA's Jet Propulsion Laboratory, Pasadena, California, is the U.S. Science team leader; Bjorn Eng of JPL is the project manager. The Terra mission is part of NASA's Earth Science Enterprise, a long-term research and technology program designed to examine Earth's land, oceans, atmosphere, ice and life as a total integrated system.

The broad spectral coverage and high spectral resolution of ASTER will provide scientists in numerous disciplines with critical information for surface mapping, and monitoring dynamic conditions and temporal change. Example applications are: monitoring glacial advances and retreats; monitoring potentially active volcanoes; identifying crop stress; determining cloud morphology and physical properties; wetlands evaluation; thermal pollution monitoring; coral reef degradation; surface temperature mapping of soils and geology; and measuring surface heat balance.

Size: 32.2 x 35.2 km (20.0 x 21.8 miles) Location: 39.2 deg. North lat., 105.3 deg. West long. Orientation: North at top Image Data: ASTER bands 8, 3, and 2. Original Data Resolution: 15 m Date Acquired: June 16, 2002

ASTER Images the Island of Hawaii

NASA Technical Reports Server (NTRS)

2000-01-01

These images of the Island of Hawaii were acquired on March 19, 2000 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet. Data are shown from the short wavelength and thermal infrared spectral regions, illustrating how different and complementary information is contained in different parts of the spectrum.

Left image: This false-color image covers an area 60 kilometers (37 miles) wide and 120 kilometers (75 miles) long in three bands of the short wavelength infrared region. While, much of the island was covered in clouds, the dominant central Mauna Loa volcano, rising to an altitude of 4115 meters (13,500 feet), is cloud-free. Lava flows can be seen radiating from the central crater in green and black tones. As they reach lower elevations, the flows become covered with vegetation, and their image color changes to yellow and orange. Mauna Kea volcano to the north of Mauna Loa has a thin cloud-cover, producing a bluish tone on the image. The ocean in the lower right appears brown due to the color processing.

Right image: This image is a false-color composite of three thermal infrared bands. The brightness of the colors is proportional to the temperature, and the hues display differences in rock composition. Clouds are black, because they are the coldest objects in the scene. The ocean and thick vegetation appear dark green because they are colder than bare rock surfaces, and have no thermal spectral features. Lava flows are shades of magenta, green, pink and yellow, reflecting chemical changes due to weathering and relative age differences.

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of five Earth-observing instruments launched December 18, 1999, on NASA's Terra satellite. The instrument was built by Japan's Ministry of International Trade and Industry. A joint U.S./Japan science team is responsible for validation and calibration of the instrument and the data products. Dr. Anne Kahle at NASA's Jet Propulsion Laboratory, Pasadena, California, is the U.S. Science team leader; Moshe Pniel of JPL is the project manager. ASTER is the only high resolution imaging sensor on Terra. The primary goal of the ASTER mission is to obtain high-resolution image data in 14 channels over the entire land surface, as well as black and white stereo images. With revisit time of between 4 and 16 days, ASTER will provide the capability for repeat coverage of changing areas on Earth's surface.

The broad spectral coverage and high spectral resolution of ASTER will provide scientists in numerous disciplines with critical information for surface mapping, and monitoring dynamic conditions and temporal change. Example applications are: monitoring glacial advances and retreats; monitoring potentially active volcanoes; identifying crop stress; determining cloud morphology and physical properties; wetlands evaluation; thermal pollution monitoring; coral reef degradation; surface temperature mapping of soils and geology; and measuring surface heat balance.

Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hughes, Michael J.; Hayes, Daniel J

2014-01-01

Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less

Space Radar Image of Bebedauro, Brazil, Seasonal

NASA Image and Video Library

1999-05-01

This is an X-band image showing seasonal changes at the hydrological test site of Bebedouro in Brazil. The image is centered at 9 degrees south latitude and 40.2 degrees west longitude. This image was acquired by the Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour on April 10, 1994, during the first flight of the radar system, and on October 1, 1994, during the second mission. The swath width is approximately 16.5 kilometers (10.5 miles) wide. The image channels have the following color assignments: red represents data acquired on April 10; green represents data acquired on October 1; blue corresponds to the ratio of the two data sets. Agriculture plays an important economic and social role in Brazil. One of the major problems related to Brazilian agriculture is estimating the size of planting areas and their productivity. Due to cloud cover and the rainy season, which occurs from November through April, optical and infrared Earth observations are seldom used to survey the region. An additional goal of monitoring this region is to watch the floodplains of rivers like Rio Sao Francisco in order to determine suitable locations for additional agricultural fields. This area belongs to the semi-arid northeastern region of Brazil, where estimates have suggested that about 10 times more land could be used for agriculture, including some locations which could be used for irrigation projects. Monitoring of soil moisture during the important summer crop season is of high priority for the future development and productivity of this region. In April the area was covered with vegetation because of the moisture of the soil and only small differences could be seen in X-band data. In October the run-off channels of this hilly region stand out quite clearly because the greenish areas indicated much less soil moisture and water content in plants. http://photojournal.jpl.nasa.gov/catalog/PIA01733

THE INFLUENCE OF NONUNIFORM CLOUD COVER ON TRANSIT TRANSMISSION SPECTRA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Line, Michael R.; Parmentier, Vivien, E-mail: mrline@ucsc.edu

2016-03-20

We model the impact of nonuniform cloud cover on transit transmission spectra. Patchy clouds exist in nearly every solar system atmosphere, brown dwarfs, and transiting exoplanets. Our major findings suggest that fractional cloud coverage can exactly mimic high mean molecular weight atmospheres and vice versa over certain wavelength regions, in particular, over the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) bandpass (1.1–1.7 μm). We also find that patchy cloud coverage exhibits a signature that is different from uniform global clouds. Furthermore, we explain analytically why the “patchy cloud-high mean molecular weight” degeneracy exists. We also explore the degeneracy ofmore » nonuniform cloud coverage in atmospheric retrievals on both synthetic and real planets. We find from retrievals on a synthetic solar composition hot Jupiter with patchy clouds and a cloud-free high mean molecular weight warm Neptune that both cloud-free high mean molecular weight atmospheres and partially cloudy atmospheres can explain the data equally well. Another key finding is that the HST WFC3 transit transmission spectra of two well-observed objects, the hot Jupiter HD 189733b and the warm Neptune HAT-P-11b, can be explained well by solar composition atmospheres with patchy clouds without the need to invoke high mean molecular weight or global clouds. The degeneracy between high molecular weight and solar composition partially cloudy atmospheres can be broken by observing the molecular Rayleigh scattering differences between the two. Furthermore, the signature of partially cloudy limbs also appears as a ∼100 ppm residual in the ingress and egress of the transit light curves, provided that the transit timing is known to seconds.« less

Bigdata Driven Cloud Security: A Survey

NASA Astrophysics Data System (ADS)

Raja, K.; Hanifa, Sabibullah Mohamed

2017-08-01

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

NASA Astrophysics Data System (ADS)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

Microsecond-scale electric field pulses in cloud lightning discharges

NASA Technical Reports Server (NTRS)

Villanueva, Y.; Rakov, V. A.; Uman, M. A.; Brook, M.

1994-01-01

From wideband electric field records acquired using a 12-bit digitizing system with a 500-ns sampling interval, microsecond-scale pulses in different stages of cloud flashes in Florida and New Mexico are analyzed. Pulse occurrence statistics and waveshape characteristics are presented. The larger pulses tend to occur early in the flash, confirming the results of Bils et al. (1988) and in contrast with the three-stage representation of cloud-discharge electric fields suggested by Kitagawa and Brook (1960). Possible explanations for the discrepancy are discussed. The tendency for the larger pulses to occur early in the cloud flash suggests that they are related to the initial in-cloud channel formation processes and contradicts the common view found in the atmospheric radio-noise literature that the main sources of VLF/LF electromagnetic radiation in cloud flashes are the K processes which occur in the final, or J type, part of the cloud discharge.

Integrating Cloud-Computing-Specific Model into Aircraft Design

NASA Astrophysics Data System (ADS)

Zhimin, Tian; Qi, Lin; Guangwen, Yang

Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

Fast calculation method of computer-generated hologram using a depth camera with point cloud gridding

NASA Astrophysics Data System (ADS)

Zhao, Yu; Shi, Chen-Xiao; Kwon, Ki-Chul; Piao, Yan-Ling; Piao, Mei-Lan; Kim, Nam

2018-03-01

We propose a fast calculation method for a computer-generated hologram (CGH) of real objects that uses a point cloud gridding method. The depth information of the scene is acquired using a depth camera and the point cloud model is reconstructed virtually. Because each point of the point cloud is distributed precisely to the exact coordinates of each layer, each point of the point cloud can be classified into grids according to its depth. A diffraction calculation is performed on the grids using a fast Fourier transform (FFT) to obtain a CGH. The computational complexity is reduced dramatically in comparison with conventional methods. The feasibility of the proposed method was confirmed by numerical and optical experiments.

Deep Clouds

NASA Image and Video Library

2008-05-27

Bright puffs and ribbons of cloud drift lazily through Saturn's murky skies. In contrast to the bold red, orange and white clouds of Jupiter, Saturn's clouds are overlain by a thick layer of haze. The visible cloud tops on Saturn are deeper in its atmosphere due to the planet's cooler temperatures. This view looks toward the unilluminated side of the rings from about 18 degrees above the ringplane. Images taken using red, green and blue spectral filters were combined to create this natural color view. The images were acquired with the Cassini spacecraft wide-angle camera on April 15, 2008 at a distance of approximately 1.5 million kilometers (906,000 miles) from Saturn. Image scale is 84 kilometers (52 miles) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA09910

Impact of Arctic sea-ice retreat on the recent change in cloud-base height during autumn

NASA Astrophysics Data System (ADS)

Sato, K.; Inoue, J.; Kodama, Y.; Overland, J. E.

2012-12-01

Cloud-base observations over the ice-free Chukchi and Beaufort Seas in autumn were conducted using a shipboard ceilometer and radiosondes during the 1999-2010 cruises of the Japanese R/V Mirai. To understand the recent change in cloud base height over the Arctic Ocean, these cloud-base height data were compared with the observation data under ice-covered situation during SHEBA (the Surface Heat Budget of the Arctic Ocean project in 1998). Our ice-free results showed a 30 % decrease (increase) in the frequency of low clouds with a ceiling below (above) 500 m. Temperature profiles revealed that the boundary layer was well developed over the ice-free ocean in the 2000s, whereas a stable layer dominated during the ice-covered period in 1998. The change in surface boundary conditions likely resulted in the difference in cloud-base height, although it had little impact on air temperatures in the mid- and upper troposphere. Data from the 2010 R/V Mirai cruise were investigated in detail in terms of air-sea temperature difference. This suggests that stratus cloud over the sea ice has been replaced as stratocumulus clouds with low cloud fraction due to the decrease in static stability induced by the sea-ice retreat. The relationship between cloud-base height and air-sea temperature difference (SST-Ts) was analyzed in detail using special section data during 2010 cruise data. Stratus clouds near the sea surface were predominant under a warm advection situation, whereas stratocumulus clouds with a cloud-free layer were significant under a cold advection situation. The threshold temperature difference between sea surface and air temperatures for distinguishing the dominant cloud types was 3 K. Anomalous upward turbulent heat fluxes associated with the sea-ice retreat have likely contributed to warming of the lower troposphere. Frequency distribution of the cloud-base height (km) detected by a ceilometer/lidar (black bars) and radiosondes (gray bars), and profiles of potential temperature (K) for (a) ice-free cases (R/V Mirai during September) and (b) ice-covered case (SHEBA during September 1998). (c) Vertical profiles of air temperature from 1000 hPa to 150 hPa (solid lines: observations north of 75°N, and dashed lines: the ERA-Interim reanalysis over 75-82.5°N, 150-170°W). Green, blue, and red lines denote profiles derived from observations by NP stations (the 1980s), SHEBA (1998), and the R/V Mirai (the 2000s), respectively. (d) Temperature trend calculated by the ERA-Interim reanalysis over the area.

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

NASA Technical Reports Server (NTRS)

Seze, G.; Rossow, W.

1987-01-01

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Snapshots of Titan North Polar Cloud

NASA Image and Video Library

2012-02-23

This series of false-color images obtained by NASA Cassini spacecraft shows the dissolving cloud cover over the north pole of Saturn moon Titan, allowing scientists to see the underlying northern lakes and seas, including Kraken Mare.

ASTER cloud coverage reassessment using MODIS cloud mask products

NASA Astrophysics Data System (ADS)

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.

Study of cloud properties using airborne and satellite measurements

NASA Astrophysics Data System (ADS)

Boscornea, Andreea; Stefan, Sabina; Vajaiac, Sorin Nicolae

2014-08-01

The present study investigates cloud microphysics properties using aircraft and satellite measurements. Cloud properties were drawn from data acquired both from in situ measurements with state of the art airborne instrumentation and from satellite products of the MODIS06 System. The used aircraft was ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research, property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania, which is specially equipped for this kind of research. The main tool of the airborne laboratory is a Cloud, Aerosol and Precipitation Spectrometer - CAPS (30 bins, 0.51- 50 μm). The data was recorded during two flights during the winter 2013-2014, over a flat region in the south-eastern part of Romania (between Bucharest and Constanta). The analysis of cloud particle size variations and cloud liquid water content provided by CAPS can explain cloud processes, and can also indicate the extent of aerosols effects on clouds. The results, such as cloud coverage and/or cloud types, microphysical parameters of aerosols on the one side and the cloud microphysics parameters obtained from aircraft flights on the other side, was used to illustrate the importance of microphysics cloud properties for including the radiative effects of clouds in the regional climate models.

Comparisons of cloud cover evaluated from LANDSAT imagery and meteorological stations across the British Isles

NASA Technical Reports Server (NTRS)

Barrett, E. C. (Principal Investigator); Grant, C. K.

1976-01-01

The author has identified the following significant results. This stage of the study has confirmed the initial supposition that LANDSAT data could be analyzed to provide useful data on cloud amount, and that useful light would be thrown thereby on the performance of the ground observer of this aspect of the state of the sky. This study, in comparison with previous studies of a similar nature using data from meteorological satellites, has benefited greatly from the much higher resolution data provided by LANDSAT. This has permitted consideration of not only the overall performance of the surface observer in estimating total cloud cover, but also his performance under different sky conditions.

E4 True and false color hot spot mosaic

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of Jupiter from NASA's Galileo spacecraft show an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers (about 21,100 by 6,800 miles). The top mosaic combines the violet and near infrared continuum filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaic covers latitudes 1 to 10 degrees and is centered at longitude 336 degrees west. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers (about 930,000 miles) by the Solid State Imaging camera system aboard Galileo. The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at: http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at: http:/ /www.jpl.nasa.gov/galileo/sepo.

Preliminary Examination of Pulse Shapes From GLAS Ocean Returns

NASA Astrophysics Data System (ADS)

Swift, T. P.; Minster, B.

2003-12-01

We have examined GLAS data collected over the Pacific ocean during the commission phase of the ICESat mission, in an area where sea state is well documented. The data used for this preliminary analysis were acquired during two passes along track 95, on March 18 and 26 of 2003, along the stretch offshore southern California. These dates were chosen for their lack of cloud cover; large (4.0 m) and small (0.7 m) significant wave heights, respectively; and the presence of waves emanating from single distant Pacific storms. Cloud cover may be investigated using MODIS images (http://acdisx.gsfc.nasa.gov/data/dataset/MODIS/), while models of significant wave heights and wave vectors for offshore California are archived by the Coastal Data Information Program (http://cdip.ucsd.edu/cdip_htmls/models.shtml). We find that the shape of deep-ocean GLAS pulse returns is diagnostic of the state of the ocean surface. A calm surface produces near-Gaussian, single-peaked shot returns. In contrast, a rough surface produces blurred shot returns which often feature multiple peaks; these peaks are typically separated by total path lengths on the order of one meter. Gaussian curves fit to rough-water returns are therefore less reliable and lead to greater measurement error; outliers in the ocean surface elevation product are mostly the result of poorly fit low-energy shot returns. Additionally, beat patterns and aliasing artifacts may arise from the sampling of deep-ocean wave trains by GLAS footprints separated by 140m. The apparent wavelength of such patterns depends not only on the wave frequency, but also on the angle between the ICESat ground track and the azimuth of the wave crests. We present a preliminary analysis of such patterns which appears to be consistent with a simple geometrical model.

Multi-spectral image analysis for improved space object characterization

NASA Astrophysics Data System (ADS)

Glass, William; Duggin, Michael J.; Motes, Raymond A.; Bush, Keith A.; Klein, Meiling

2009-08-01

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground-based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). This information can be used to improve our catalog of space objects and will be helpful in the resolution of satellite anomalies. At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space-Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Space Radar Image of Patagonian Ice Fields

NASA Image and Video Library

1999-04-15

This pair of images illustrates the ability of multi-parameter radar imaging sensors such as the Spaceborne Imaging Radar-C/X-band Synthetic Aperture radar to detect climate-related changes on the Patagonian ice fields in the Andes Mountains of Chile and Argentina. The images show nearly the same area of the south Patagonian ice field as it was imaged during two space shuttle flights in 1994 that were conducted five-and-a-half months apart. The images, centered at 49.0 degrees south latitude and 73.5degrees west longitude, include several large outlet glaciers. The images were acquired by SIR-C/X-SAR on board the space shuttle Endeavour during April and October 1994. The top image was acquired on April 14, 1994, at 10:46 p.m. local time, while the bottom image was acquired on October 5,1994, at 10:57 p.m. local time. Both were acquired during the 77th orbit of the space shuttle. The area shown is approximately 100 kilometers by 58 kilometers (62 miles by 36 miles) with north toward the upper right. The colors in the images were obtained using the following radar channels: red represents the C-band (horizontally transmitted and received); green represents the L-band (horizontally transmitted and received); blue represents the L-band (horizontally transmitted and vertically received). The overall dark tone of the colors in the central portion of the April image indicates that the interior of the ice field is covered with thick wet snow. The outlet glaciers, consisting of rough bare ice, are the brightly colored yellow and purple lobes which terminate at calving fronts into the dark waters of lakes and fiords. During the second mission the temperatures were colder and the corresponding change in snow and ice conditions is readily apparent by comparing the images. The interior of the ice field is brighter because of increased radar return from the dryer snow. The distinct green/orange boundary on the ice field indicates an abrupt change in the structure of the snowcap, a direct indication of the steep meteorological gradients known to exist in this region. The bluer color of the outlet glaciers is probably due to a thin snow cover. A portion of the terminus of the outlet glacier at the top left center of the images has advanced approximately 600 meters (1,970 feet) in the five-and-a-half months between the two missions. Because of the persistent cloud cover this observation was only possible by using the orbiting, remote imaging radar system. http://photojournal.jpl.nasa.gov/catalog/PIA01778

Improving volcanic sulfur dioxide cloud dispersal forecasts by progressive assimilation of satellite observations

NASA Astrophysics Data System (ADS)

Boichu, Marie; Clarisse, Lieven; Khvorostyanov, Dmitry; Clerbaux, Cathy

2014-04-01

Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts.

Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, David R.; McCubbin, Ian; Gao, Bo Cai

Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA’s “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARMmore » Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. Finally, the coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.« less

Florida Everglades and Keys, USA

NASA Technical Reports Server (NTRS)

1991-01-01

Though much of southern Florida is covered by clouds, the Florida Everglades and Keys (25.0N, 82.0W) remain relatively clear in this nearly vertical view. The view covers the Gulf of Mexico port city of Ft. Myers, and Lake Okeechobee, at the top of the scene, in the north, The Everglades, in the center and the entire Florida Key Chain at the bottom. Even with the many popcorn clouds, ground detail and the city of Miami is easily discerned.

Study of the application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J. (Principal Investigator); Russell, O. R.; Amato, R. V.

1972-01-01

The author has identified the following significant results. Various data compilation and analysis activities in support of ERTS-1 imagery interpretation are in progress or are completed. These include the compilation of mine accident data, areas of mine roof instability and the analysis of high altitude color infrared photography and low altitude color and color infrared photography which was acquired by NASA in support of the project. The photography reveals that many fracture lineaments are detectable through a varied thickness of glacial till. These data will be compiled on a series of 1:250,000 scale base maps and evaluated for a correlation between fracture zones and mine accidents and rooffalls. Due to high occurrence of cloud cover in the project area and to the delay in imagery shipments, little progress has been made in the analysis of ERTS-1 imagery.

Study of 3D bathymetry modelling using LAPAN Surveillance Unmanned Aerial Vehicle 02 (LSU-02) photo data with stereo photogrammetry technique, Wawaran Beach, Pacitan, East Java, Indonesia

NASA Astrophysics Data System (ADS)

Sari, N. M.; Nugroho, J. T.; Chulafak, G. A.; Kushardono, D.

2018-05-01

Coastal is an ecosystem that has unique object and phenomenon. The potential of the aerial photo data with very high spatial resolution covering coastal area is extensive. One of the aerial photo data can be used is LAPAN Surveillance UAV 02 (LSU-02) photo data which is acquired in 2016 with a spatial resolution reaching 10cm. This research aims to create an initial bathymetry model with stereo photogrammetry technique using LSU-02 data. In this research the bathymetry model was made by constructing 3D model with stereo photogrammetry technique that utilizes the dense point cloud created from overlapping of those photos. The result shows that the 3D bathymetry model can be built with stereo photogrammetry technique. It can be seen from the surface and bathymetry transect profile.

Height and Motion of the Chikurachki Eruption Plume

NASA Technical Reports Server (NTRS)

2003-01-01

The height and motion of the ash and gas plume from the April 22, 2003, eruption of the Chikurachki volcano is portrayed in these views from the Multi-angle Imaging SpectroRadiometer (MISR). Situated within the northern portion of the volcanically active Kuril Island group, the Chikurachki volcano is an active stratovolcano on Russia's Paramushir Island (just south of the Kamchatka Peninsula).

In the upper panel of the still image pair, this scene is displayed as a natural-color view from MISR's vertical-viewing (nadir) camera. The white and brownish-grey plume streaks several hundred kilometers from the eastern edge of Paramushir Island toward the southeast. The darker areas of the plume typically indicate volcanic ash, while the white portions of the plume indicate entrained water droplets and ice. According to the Kamchatkan Volcanic Eruptions Response Team (KVERT), the temperature of the plume near the volcano on April 22 was -12o C.

The lower panel shows heights derived from automated stereoscopic processing of MISR's multi-angle imagery, in which the plume is determined to reach heights of about 2.5 kilometers above sea level. Heights for clouds above and below the eruption plume were also retrieved, including the high-altitude cirrus clouds in the lower left (orange pixels). The distinctive patterns of these features provide sufficient spatial contrast for MISR's stereo height retrieval to perform automated feature matching between the images acquired at different view angles. Places where clouds or other factors precluded a height retrieval are shown in dark gray.

The multi-angle 'fly-over' animation (below) allows the motion of the plume and of the surrounding clouds to be directly observed. The frames of the animation consist of data acquired by the 70-degree, 60-degree, 46-degree and 26-degree forward-viewing cameras in sequence, followed by the images from the nadir camera and each of the four backward-viewing cameras, ending with the view from the 70-degree backward camera.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17776. The panels cover an area of approximately 296 kilometers x 216 kilometers (still images) and 185 kilometers x 154 kilometers (animation), and utilize data from blocks 50 to 51 within World Reference System-2 path 100.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

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Study of the thermodynamic phase of hydrometeors in convective clouds in the Amazon Basin

NASA Astrophysics Data System (ADS)

Ferreira, W. C.; Correia, A. L.; Martins, J.

2012-12-01

Aerosol-cloud interactions are responsible for large uncertainties in climatic models. One key fator when studying clouds perturbed by aerosols is determining the thermodynamic phase of hydrometeors as a function of temperature or height in the cloud. Conventional remote sensing can provide information on the thermodynamic phase of clouds over large areas, but it lacks the precision needed to understand how a single, real cloud evolves. Here we present mappings of the thermodynamic phase of droplets and ice particles in individual convective clouds in the Amazon Basin, by analyzing the emerging infrared radiance on cloud sides (Martins et al., 2011). In flights over the Amazon Basin with a research aircraft Martins et al. (2011) used imaging radiometers with spectral filters to record the emerging radiance on cloud sides at the wavelengths of 2.10 and 2.25 μm. Due to differential absorption and scattering of these wavelengths by hydrometeors in liquid or solid phases, the intensity ratio between images recorded at the two wavelengths can be used as proxy to the thermodynamic phase of these hydrometeors. In order to analyze the acquired dataset we used the MATLAB tools package, developing scripts to handle data files and derive the thermodynamic phase. In some cases parallax effects due to aircraft movement required additional data processing before calculating ratios. Only well illuminated scenes were considered, i.e. images acquired as close as possible to the backscatter vector from the incident solar radiation. It's important to notice that the intensity ratio values corresponding to a given thermodynamic phase can vary from cloud to cloud (Martins et al., 2011), however inside the same cloud the distinction between ice, water and mixed-phase is clear. Analyzing histograms of reflectance ratios 2.10/2.25 μm in selected cases, we found averages typically between 0.3 and 0.4 for ice phase hydrometeors, and between 0.5 and 0.7 for water phase droplets, consistent with the findings in Martins et al., (2011). Figure 1 shows an example of thermodynamic phase classification obtained with this technique. These experimental results can potentially be used in fast derivations of thermodynamic phase mappings in deep convective clouds, providing useful information for studies regarding aerosol-cloud interactions. Image of the ratio of reflectances at 2.10/2.25μm

Validation of Local-Cloud Model Outputs With the GOES Satellite Imagery

NASA Astrophysics Data System (ADS)

Malek, E.

2005-05-01

Clouds (visible aggregations of minute droplets of water or tiny crystals of ice suspended in the air) affect the radiation budget of our planet by reflecting, absorbing and scattering solar radiation, and the re-emission of terrestrial radiation. They affect the weather and climate by positive or negative feedbacks. Many researchers have worked on the parameterization of clouds and their effects on the radiation budget. There is little information about ground-based approaches for continuous evaluation of cloud, such as cloud base height, cloud base temperature, and cloud coverage, at local and regional scales. This present article deals with the development of an algorithm for continuous (day and night) evaluation of cloud base temperature, cloud base height and percent of skies covered by cloud at local scale throughout the year. The Vaisala model CT-12K laser beam ceilometer is used at the Automated Surface Observing Systems (ASOS) to measure the cloud base height and report the sky conditions on an hourly basis or at shorter intervals. This laser ceilometer is a fixed-type whose transmitter and receiver point straight up at the cloud (if any) base. It is unable to measure clouds that are not above the sensor. To report cloudiness at the local scale, many of these type of ceilometers are needed. This is not a perfect method for cloud measurement. A single cloud hanging overhead the sensor will cause overcast readings, whereas, a hole in the clouds could cause a clear reading to be reported. To overcome this problem, we have set up a ventilated radiation station at Logan-Cache airport, Utah, U.S.A., since 1995, which is equipped with one of the above-mentioned ceilometers. This radiation station (composed of pyranometers, pyrgeometers and net radiometer) provides continuous measurements of incoming and outgoing shortwave and longwave radiation and the net radiation throughout the year. We have also measured the surface temperature and pressure, the 2-m air temperature and humidity, precipitation, and the 3-m wind and direction at this station. Having the air temperature, moisture, and the measured cloudless incoming longwave (atmospheric) radiation during 1999 through 2004, based upon the ASOS and the algorithm data, we found the appropriate formula (among four reported approaches) for computation of the cloudless-skies atmospheric emissivity. Considering the additional longwave radiation captured by the facing-up pyrgeometer during the cloudy skies, coming from the cloud in the wave band which the gaseous emission lacks (from 8-13 ìm), we developed an algorithm which provides the continuous 20-min cloud information (cloud base height, cloud base temperature, and percent of skies covered by cloud) over the Cache Valley during day and night throughout the year. The comparisons between the ASOS and the algorithm data during the period of 8-12 June, 2004 are reported in this article. The proposed algorithm is a promising approach for evaluation of the cloud base temperature, cloud base height, and percent of skies covered by cloud at the local scale throughout the year. It also reports the comparison between model outputs and GOES 10 satellite images.

Rabi cropped area forecasting of parts of Banaskatha District,Gujarat using MRS RISAT-1 SAR data

NASA Astrophysics Data System (ADS)

Parekh, R. A.; Mehta, R. L.; Vyas, A.

2016-10-01

Radar sensors can be used for large-scale vegetation mapping and monitoring using backscatter coefficients in different polarisations and wavelength bands. Due to cloud and haze interference, optical images are not always available at all phonological stages important for crop discrimination. Moreover, in cloud prone areas, exclusively SAR approach would provide operational solution. This paper presents the results of classifying the cropped and non cropped areas using multi-temporal SAR images. Dual polarised C- band RISAT MRS (Medium Resolution ScanSAR mode) data were acquired on 9thDec. 2012, 28thJan. 2013 and 22nd Feb. 2013 at 18m spatial resolution. Intensity images of two polarisations (HH, HV) were extracted and converted into backscattering coefficient images. Cross polarisation ratio (CPR) images and Radar fractional vegetation density index (RFDI) were created from the temporal data and integrated with the multi-temporal images. Signatures of cropped and un-cropped areas were used for maximum likelihood supervised classification. Separability in cropped and umcropped classes using different polarisation combinations and classification accuracy analysis was carried out. FCC (False Color Composite) prepared using best three SAR polarisations in the data set was compared with LISS-III (Linear Imaging Self-Scanning System-III) image. The acreage under rabi crops was estimated. The methodology developed was for rabi cropped area, due to availability of SAR data of rabi season. Though, the approach is more relevant for acreage estimation of kharif crops when frequent cloud cover condition prevails during monsoon season and optical sensors fail to deliver good quality images.

A comparative analysis of extended water cloud model and backscatter modelling for above-ground biomass assessment in Corbett Tiger Reserve

NASA Astrophysics Data System (ADS)

Kumar, Yogesh; Singh, Sarnam; Chatterjee, R. S.; Trivedi, Mukul

2016-04-01

Forest biomass acts as a backbone in regulating the climate by storing carbon within itself. Thus the assessment of forest biomass is crucial in understanding the dynamics of the environment. Traditionally the destructive methods were adopted for the assessment of biomass which were further advanced to the non-destructive methods. The allometric equations developed by destructive methods were further used in non-destructive methods for the assessment, but they were mostly applied for woody/commercial timber species. However now days Remote Sensing data are primarily used for the biomass geospatial pattern assessment. The Optical Remote Sensing data (Landsat8, LISS III, etc.) are being used very successfully for the estimation of above ground biomass (AGB). However optical data is not suitable for all atmospheric/environmental conditions, because it can't penetrate through clouds and haze. Thus Radar data is one of the alternate possible ways to acquire data in all-weather conditions irrespective of weather and light. The paper examines the potential of ALOS PALSAR L-band dual polarisation data for the estimation of AGB in the Corbett Tiger Reserve (CTR) covering an area of 889 km2. The main focus of this study is to explore the accuracy of Polarimetric Scattering Model (Extended Water Cloud Model (EWCM) with respect to Backscatter model in the assessment of AGB. The parameters of the EWCM were estimated using the decomposition components (Raney Decomposition) and the plot level information. The above ground biomass in the CTR ranges from 9.6 t/ha to 322.6 t/ha.

Marine Layer Clouds off the California Coast

NASA Image and Video Library

2017-12-08

NASA image acquired September 27, 2012 On September 27, 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured this nighttime view of low-lying marine layer clouds along the coast of California. The image was captured by the VIIRS “day-night band,” which detects light in a range of wavelengths from green to near-infrared and uses filtering techniques to observe signals such as gas flares, auroras, wildfires, city lights, and reflected moonlight. An irregularly-shaped patch of high clouds hovers off the coast of California, and moonlight caused the high clouds to cast distinct shadows on the marine layer clouds below. VIIRS acquired the image when the Moon was in its waxing gibbous phase, meaning it was more than half-lit, but less than full. Low clouds pose serious hazards for air and ship traffic, but satellites have had difficulty detecting them in the past. To illustrate this, the second image shows the same scene in thermal infrared, the band that meteorologists generally use to monitor clouds at night. Only high clouds are visible; the low clouds do not show up at all because they are roughly the same temperature as the ground. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using VIIRS Day-Night Band data from the Suomi National Polar-orbiting Partnership. Suomi NPP is the result of a partnership between NASA, the National Oceanic and Atmospheric Administration, and the Department of Defense. Caption by Adam Voiland. Instrument: Suomi NPP - VIIRS Credit: NASA Earth Observatory Click here to view all of the Earth at Night 2012 images Click here to read more about this image NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Bamboo mapping of Ethiopia, Kenya and Uganda for the year 2016 using multi-temporal Landsat imagery

NASA Astrophysics Data System (ADS)

Zhao, Yuanyuan; Feng, Duole; Jayaraman, Durai; Belay, Daniel; Sebrala, Heiru; Ngugi, John; Maina, Eunice; Akombo, Rose; Otuoma, John; Mutyaba, Joseph; Kissa, Sam; Qi, Shuhua; Assefa, Fiker; Oduor, Nellie Mugure; Ndawula, Andrew Kalema; Li, Yanxia; Gong, Peng

2018-04-01

Mapping the spatial distribution of bamboo in East Africa is necessary for biodiversity conservation, resource management and policy making for rural poverty reduction. In this study, we produced a contemporary bamboo cover map of Ethiopia, Kenya and Uganda for the year 2016 using multi-temporal Landsat imagery series at 30 m spatial resolution. This is the first bamboo map generated using remotely sensed data for these three East African countries that possess most of the African bamboo resource. The producer's and user's accuracies of bamboos are 79.2% and 84.0%, respectively. The hotspots with large amounts of bamboo were identified and the area of bamboo coverage for each region was estimated according to the map. The seasonal growth status of two typical bamboo zones (one highland bamboo and one lowland bamboo) were analyzed and the multi-temporal imagery proved to be useful in differentiating bamboo from other vegetation classes. The images acquired in September to February are less contaminated by clouds and shadows, and the image series cover the dying back process of lowland bamboo, which were helpful for bamboo identification in East Africa.

Low Clouds and Cosmic Rays: Possible Reasons for Correlation Changes

NASA Astrophysics Data System (ADS)

Veretenenko, S. V.; Ogurtsov, M. G.

2015-03-01

In this work we investigated the nature of correlations between low cloud cover anomalies (LCA) and galactic cosmic ray (GCR) variations detected on the decadal time scale, as well as possible reasons for the violation of these correlations in the early 2000s. It was shown that the link between cloud cover at middle latitudes and GCR fluxes is not direct, but it is realized through GCR influence on the development of extratropical baric systems (cyclones and troughs) which form cloud field. As the sign of GCR effects on the troposphere dynamics seems to depend on the strength of the stratospheric polar vortex, a possible reason for the violation of a positive correlation between LCA and GCR fluxes in the early 2000s may be the change of the vortex state which resulted in the reversal of GCR effects on extratropical cyclone development.

Infrared Extinction and the Initial Conditions for Star and Planet Formation

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2004-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular clouds and investigate the physical conditions which give rise to star and planet formation. The goals of the this program are to: 1) acquire deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds, 2) reduce and analyze the data obtained in order to produce detailed extinction maps of the clouds, 3) prepare results, where appropriate, for publication. A description of how these goals were met are included.

Studies in the use of cloud type statistics in mission simulation

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Willand, J. H.; Chang, D. T.; Cogan, J. L.

1974-01-01

A study to further improve NASA's global cloud statistics for mission simulation is reported. Regional homogeneity in cloud types was examined; most of the original region boundaries defined for cloud cover amount in previous studies were supported by the statistics on cloud types and the number of cloud layers. Conditionality in cloud statistics was also examined with special emphasis on temporal and spatial dependencies, and cloud type interdependence. Temporal conditionality was found up to 12 hours, and spatial conditionality up to 200 miles; the diurnal cycle in convective cloudiness was clearly evident. As expected, the joint occurrence of different cloud types reflected the dynamic processes which form the clouds. Other phases of the study improved the cloud type statistics for several region and proposed a mission simulation scheme combining the 4-dimensional atmospheric model, sponsored by MSFC, with the global cloud model.

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

NASA Technical Reports Server (NTRS)

Yao, Mao-Sung; Cheng, Ye

2013-01-01

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

NASA Technical Reports Server (NTRS)

Kidder, Stanley Q.; Hafner, Jan

1997-01-01

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect local and regional climate and air quality. Clouds play a significant role in this relationship. Using GOES images, we found that in a 63-day period (5 July-5 September 1996) there were zero days which were clear for the entire daylight period. Days which are cloud-free in the morning become partly cloudy with small cumulus clouds in the afternoon in response to solar heating. This result casts doubt on the applicability of California-style air quality models which run in perpetual clear skies. Days which are clear in the morning have higher ozone than those which are cloudy in the morning. Using the RAMS model, we found that urbanization increases the skin surface temperature by about 1.0-1.5 C on average under cloudy conditions, with an extreme of +3.5 C. Clouds cool the surface due to their shading effect by 1.5-2.0 C on average, with an extreme of 5.0 C. RAMS simulates well the building stage of the cumulus cloud field, but does poorly in the decaying phase. Next year's work: doing a detailed cloud climatology and developing improved RAMS cloud simulations.

Spatial and Temporal Inter-Relationships Between Anomalies of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, percent cloud cover and cloud top pressure, and OLR. Near real time products, stating with September 2002, have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. Results in this paper included products through April 2008. The time period studied is marked by a substantial warming trend of Northern Hemisphere Extropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, are shown below, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. The ability to match this data represents a good test of a model's response to El Nino.

Lessons Learned From Large-Scale Evapotranspiration and Root Zone Soil Moisture Mapping Using Ground Measurements (meteorological, LAS, EC) and Remote Sensing (METRIC)

NASA Astrophysics Data System (ADS)

Hendrickx, J. M. H.; Allen, R. G.; Myint, S. W.; Ogden, F. L.

2015-12-01

Large scale mapping of evapotranspiration and root zone soil moisture is only possible when satellite images are used. The spatial resolution of this imagery typically depends on its temporal resolution or the satellite overpass time. For example, the Landsat satellite acquires images at 30 m resolution every 16 days while the MODIS satellite acquires images at 250 m resolution every day. In this study we deal with optical/thermal imagery that is impacted by cloudiness contrary to radar imagery that penetrates through clouds. Due to cloudiness, the temporal resolution of Landsat drops from 16 days to about one clear sky Landsat image per month in the southwestern USA and about one every ten years in the humid tropics of Panama. Only by launching additional satellites can the temporal resolution be improved. Since this is too costly, an alternative is found by using ground measurements with high temporal resolution (from minutes to days) but poor spatial resolution. The challenge for large-scale evapotranspiration and root zone soil moisture mapping is to construct a layer stack consisting of N time layers covering the period of interest each containing M pixels covering the region of interest. We will present examples of the Phoenix Active Management Area in AZ (14,600 km2), Green River Basin in WY (44,000 km2), the Kishwaukee Watershed in IL (3,150 km2), the area covered by Landsat Path 28/Row 35 in OK (30,000 km2) and the Agua Salud Watershed in Panama (200 km2). In these regions we used Landsat or MODIS imagery for mapping evapotranspiration and root zone soil moisture by the algorithm Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) together with meteorological measurements and sometimes either Large Aperture Scintillometers (LAS) or Eddy Covariance (EC). We conclude with lessons learned for future large-scale hydrological studies.

Light availability controls ecosystem fluxes in native and non-native tropical montane wet forests in Hawai`i

NASA Astrophysics Data System (ADS)

Giambelluca, T. W.; Mudd, R. G.; Huang, M.; Nullet, M.; Asner, G. P.; Martin, R.; Ostertag, R.; Miyazawa, Y.; Litton, C. M.

2016-12-01

Uncertainty about the local and regional effects of global climate warming on terrestrial ecosystems and their ability to produce ecosystem goods and services is a serious constraint for land-based natural resource managers. In Hawai`i and other Pacific Islands, this issue is complicated by the presence of numerous and widespread non-native invasive species, including invasive trees. As warming continues and other climate variables change in response to temperature increases, how will native- and non-native-dominated ecosystems respond? To address this question, eddy covariance flux towers were established and operated for approximately a decade over native forest and at a site invaded by a non-native tree. Flux data were analyzed to determine the sensitivity of carbon exchange rates to fluctuations in ambient CO2 concentration, temperature (T), humidity, photosynthetically active radiation (PAR), and soil moisture (SM). At both sites, gross primary production (GPP) is strongly controlled by PAR and to a lesser extent by T. Ecosystem respiration (Re) responds to T and SM at both sites, as expected. Net ecosystem carbon exchange (NEE) is predominantly controlled by PAR at both sites. Higher temperature is associated with higher rates of photosynthesis and greater Re, thereby canceling the net effect of temperature on carbon exchange. Hence, no significant effect of temperature on NEE was found at either site. These results suggest that the direct effects of future warming will be small in relation to the effects of any changes in cloud cover that affect incident solar radiation. Cloud cover in Hawai`i could be affected by projected increases in atmospheric stability (reduced cloud cover) and increases in humidity (increased cloud cover). Light response (GPP sensitivity to PAR) was found to be significantly greater at the non-native site, suggesting that a future decrease in cloud cover would favor the non-native ecosystem, while increased cloudiness would cause a greater reduction in carbon uptake in the non-native forest.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability

NASA Astrophysics Data System (ADS)

Hamdan, Lubna

Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update. The analysis showed that the main atmospheric parameters that affect the amount of global radiation received on earth's surface are cloud cover and relative humidity. Global radiation correlates negatively with both variables. Linear models are excellent approximations for the relationship between atmospheric parameters and global radiation. A linear model with the predictors total cloud cover, relative humidity, and extraterrestrial radiation is able to explain around 98% of the variability in global radiation. For diffuse radiation, the analysis showed that the main atmospheric parameters that affect the amount received on earth's surface are cloud cover and aerosol optical depth. Diffuse radiation correlates positively with both variables. Linear models are very good approximations for the relationship between atmospheric parameters and diffuse radiation. A linear model with the predictors total cloud cover, aerosol optical depth, and extraterrestrial radiation is able to explain around 91% of the variability in diffuse radiation. Prediction analysis showed that the linear models we fitted were able to predict diffuse radiation with efficiency of test adjusted R2 values equal to 0.93, using the data of total cloud cover, aerosol optical depth, relative humidity and extraterrestrial radiation. However, for prediction purposes, using nonlinear terms or nonlinear models might enhance the prediction of diffuse radiation.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

MODIS-based Snow Cover Variability of the Upper River Grande Basin

NASA Astrophysics Data System (ADS)

Yu, B.; Wang, X.; Xie, H.

2007-12-01

Snow cover and its spring melting in the Upper Rio Grande Basin provides a major water source for the Upper to Middle Rio Grande valley and Elephant Butte Reservoir. Thus understanding the snowpack and its variability in the context of global climate change is crucial to the sustainable water resources for the region. MODIS instruments (on Terra and Aqua) have provided time series of snow cover products since 2000, but suffering with cloud contaminations. In this study, we evaluated four newly developed cloudless snow cover products (less than 10%) and four standard products: daily (MOD10A1, MYD10A1) and 8-day (MOD10A2, MYD10A2), in comparison with in situ Snowpack Telemetry (SNOTEL) measurements for the hydrological year 2003-2004. The four new products are daily composite of Terra and Aqua (MODMYD10DC), multi-day composites of Terra (MOD10MC), Aqua (MYD10MC), and Terra and Aqua (MODMYD10MC). The standard daily and 8-day products can classify land correctly, but had fairly low accuracy in snow classification due to cloud contamination (a average of 39.4% for Terra and 45% for Aqua in the year 2003-2004). All the new multi-day composite products tended to have high accuracy in classifying both snow and land (over 90%), as the cloud cover has been reduced to less than 10% (~5% for the year) under the new algorithm . This result is consistent with a previous study in the Xinjiang area, China (Wang and Xie, 2007). Therefore, MOD10MC (before the Aqua data available) and MODMYD10MC products are used to get the mean snow cover of the Upper Rio Grande Basin from 2000 to 2007. The snow depletion curve derived from the new cloud-free snow cover map will be used to examine its effect on stream discharge.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

A Jovian Hotspot in True and False Colors (Time set 3)

NASA Technical Reports Server (NTRS)

1997-01-01

True and false color views of an equatorial 'hotspot' on Jupiter. These images cover an area 34,000 kilometers by 11,000 kilometers. The top mosaic combines the violet (410 nanometers or nm) and near-infrared continuum (756 nm) filter images to create an image similar to how Jupiter would appear to human eyes. Differences in coloration are due to the composition and abundances of trace chemicals in Jupiter's atmosphere. The bottom mosaic uses Galileo's three near-infrared wavelengths (756 nm, 727 nm, and 889 nm displayed in red, green, and blue) to show variations in cloud height and thickness. Bluish clouds are high and thin, reddish clouds are low, and white clouds are high and thick. The dark blue hotspot in the center is a hole in the deep cloud with an overlying thin haze. The light blue region to the left is covered by a very high haze layer. The multicolored region to the right has overlapping cloud layers of different heights. Galileo is the first spacecraft to distinguish cloud layers on Jupiter.

North is at the top. The mosaics cover latitudes 1 to 10 degrees and are centered at longitude 336 degrees West. The planetary limb runs along the right edge of the image. Cloud patterns appear foreshortened as they approach the limb. The smallest resolved features are tens of kilometers in size. These images were taken on December 17, 1996, at a range of 1.5 million kilometers by the Solid State Imaging system aboard NASA's Galileo spacecraft.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Dynamics of Venus' Southern hemisphere and South Polar Vortex from VIRTIS data obtained during the Venus Expres Mission

NASA Astrophysics Data System (ADS)

Hueso, R.; Garate-Lopez, I.; Sanchez-Lavega, A.

2011-12-01

The VIRTIS instrument onboard Venus Express observes Venus in two channels (visible and infrared) obtaining spectra and multi-wavelength images of the planet. The images have been used to trace the motions of the atmosphere at different layers of clouds [1-3]. We review the VIRTIS cloud image data and wind results obtained by different groups [1-3] and we present new results concerning the morphology and evolution of the South Polar Vortex at the upper and lower cloud levels with data covering the first 900 days of the mission. We present wind measurements of the South hemisphere obtained by cloud tracking individual cloud features and higher-resolution wind results of the polar region covering the evolution of the South polar vortex. The later were obtained by an image correlation algorithm run under human supervision to validate the data. We present day-side data of the upper clouds obtained at 380 and 980 nm sensitive to altitudes of 66-70 km, night-side data in the near infrared at 1.74 microns of the lower cloud (45-50 km) and day and night-side data obtained in the thermal infrared (wavelengths of 3.8 and 5.1 microns) which covers the dynamical evolution of Venus South Polar vortex at the cloud tops (66-70 km). We explore the different dynamics associated to the varying morphology of the vortex, its dynamical structure at different altitudes, the variability of the global wind data of the southern hemisphere and the interrelation of the polar vortex dynamics with the wind dynamics at subpolar and mid-latitudes. Acknowledgements: Work funded by Spanish MICIIN AYA2009-10701 with FEDER support and Grupos Gobierno Vasco IT-464-07. References [1] A. Sánchez-Lavega et al., Geophys. Res. Lett. 35, L13204, (2008). [2] D. Luz et al., Science, 332, 577-580 (2011). [3] R. Hueso, et al., Icarus doi:10.1016/j.icarus.2011.04.020 (2011)

A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity

NASA Astrophysics Data System (ADS)

Rune Karlsen, Stein; Anderson, Helen B.; van der Wal, René; Bremset Hansen, Brage

2018-02-01

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R 2 = 0.51 and 0.44, respectively). The commonly used ‘maximum NDVI’ plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.

Assessment of diffuse radiation models in Azores

NASA Astrophysics Data System (ADS)

Magarreiro, Clarisse; Brito, Miguel; Soares, Pedro; Azevedo, Eduardo

2014-05-01

Measured irradiance databases usually consist of global solar radiation data with limited spatial coverage. Hence, solar radiation models have been developed to estimate the diffuse fraction from the measured global irradiation. This information is critical for the assessment of the potential of solar energy technologies; for example, the decision to use photovoltaic systems with tracking system. The different solar radiation models for this purpose differ on the parameters used as input. The simplest, and most common, are models which use global radiation information only. More sophisticated models require meteorological parameters such as information from clouds, atmospheric turbidity, temperature or precipitable water content. Most of these models comprise correlations with the clearness index, kt (portion of horizontal extra-terrestrial radiation reaching the Earth's surface) to obtain the diffuse fraction kd (portion of diffuse component from global radiation). The applicability of these different models is related to the local atmospheric conditions and its climatic characteristics. The models are not of general validity and can only be applicable to locations where the albedo of the surrounding terrain and the atmospheric contamination by dust are not significantly different from those where the corresponding methods were developed. Thus, models of diffuse fraction exhibit a relevant degree of location dependence: e.g. models developed considering data acquired in Europe are mainly linked to Northern, Central or, more recently, Mediterranean areas. The Azores Archipelago, with its particular climate and cloud cover characteristics, different from mainland Europe, has not yet been considered for the development of testing of such models. The Azorean climate reveals large amounts of cloud cover in its annual cycle, with spatial and temporal variabilities more complex than the common Summer/Winter pattern. This study explores the applicability of different existing correlation models of diffuse fraction and clearness index or other plain parameters to the Azorean region. Reliable data provided by the Atmospheric Radiation Measurements (ARM) Climate Research Facility from the Graciosa Island deployment of the ARM Mobile Facility (http://www.arm.gov/sites/amf/grw) was used to perform the analysis. Model results showed a tendency to underestimate higher values of diffuse radiation. From the performance results of the correlation models reviewed it was clear that there is room for improvement.

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhuosen; King, Michael D.

2012-01-01

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhousen; King, Michael D.

2011-01-01

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

NASA Technical Reports Server (NTRS)

Bender, Frida A-M.; Rananathan, V.; Tselioudis, G.

2012-01-01

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Typhoon Sinlaku

Atmospheric Science Data Center

2013-04-16

... before the storm weakened as it moved inland. While the nature and formation of individual storm events is relatively well understood, ... clouds on climate is difficult to assess due to the variable nature of cloud cover at various altitudes. MISR's data products are designed ...

Upper-Tropospheric Cloud Ice from IceCube

NASA Astrophysics Data System (ADS)

Wu, D. L.

2017-12-01

Cloud ice plays important roles in Earth's energy budget and cloud-precipitation processes. Knowledge of global cloud ice and its properties is critical for understanding and quantifying its roles in Earth's atmospheric system. It remains a great challenge to measure these variables accurately from space. Submillimeter (submm) wave remote sensing has capability of penetrating clouds and measuring ice mass and microphysical properties. In particular, the 883-GHz frequency is a highest spectral window in microwave frequencies that can be used to fill a sensitivity gap between thermal infrared (IR) and mm-wave sensors in current spaceborne cloud ice observations. IceCube is a cubesat spaceflight demonstration of 883-GHz radiometer technology. Its primary objective is to raise the technology readiness level (TRL) of 883-GHz cloud radiometer for future Earth science missions. By flying a commercial receiver on a 3U cubesat, IceCube is able to achieve fast-track maturation of space technology, by completing its development, integration and testing in 2.5 years. IceCube was successfully delivered to ISS in April 2017 and jettisoned from the International Space Station (ISS) in May 2017. The IceCube cloud-ice radiometer (ICIR) has been acquiring data since the jettison on a daytime-only operation. IceCube adopted a simple design without payload mechanism. It makes maximum utilization of solar power by spinning the spacecraft continuously about the Sun vector at a rate of 1.2° per second. As a result, the ICIR is operated under the limited resources (8.6 W without heater) and largely-varying (18°C-28°C) thermal environments. The spinning cubesat also allows ICIR to have periodical views between the Earth (atmosphere and clouds) and cold space (calibration), from which the first 883-GHz cloud map is obtained. The 883-GHz cloud radiance, sensitive to ice particle scattering, is proportional to cloud ice amount above 10 km. The ICIR cloud map acquired during June 20-July 2, 2017 shows a clear distribution of the inter-tropical convergence zone (ITCZ), as well as the classic Gill-model pattern over the Western Pacific and Indian monsoon regions. Like the ISS, the coverage of ICIR observations is limited to low-to-mid latitudes. More science results and IceCube experiments with the cubesat operation will be discussed.

Complexity in Climatic Controls on Plant Species Distribution: Satellite Data Reveal Unique Climate for Giant Sequoia in the California Sierra Nevada

NASA Astrophysics Data System (ADS)

Waller, Eric Kindseth

A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. Every location has a unique and constantly changing climate so that any distribution could be explained by some aspect of climate. Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.).

Study of Huizhou architecture component point cloud in surface reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Runmei; Wang, Guangyin; Ma, Jixiang; Wu, Yulu; Zhang, Guangbin

2017-06-01

Surface reconfiguration softwares have many problems such as complicated operation on point cloud data, too many interaction definitions, and too stringent requirements for inputing data. Thus, it has not been widely popularized so far. This paper selects the unique Huizhou Architecture chuandou wooden beam framework as the research object, and presents a complete set of implementation in data acquisition from point, point cloud preprocessing and finally implemented surface reconstruction. Firstly, preprocessing the acquired point cloud data, including segmentation and filtering. Secondly, the surface’s normals are deduced directly from the point cloud dataset. Finally, the surface reconstruction is studied by using Greedy Projection Triangulation Algorithm. Comparing the reconstructed model with the three-dimensional surface reconstruction softwares, the results show that the proposed scheme is more smooth, time efficient and portable.

Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

Treesearch

Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

2017-01-01

As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik; Hollmann, Rainer; Schwarz, Katharina

2017-10-01

This study investigates the impact of air mass origin and dynamics on cloud property changes in the Southeast Atlantic (SEA) during the biomass burning season. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget and thus prominent in climate system research. In this study, the thermodynamically stable SEA stratocumulus cover is observed not only as the result of local environmental conditions but also as connected to large-scale meteorology by the often neglected but important role of spatial origins of air masses entering this region. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a Hybrid Single-Particle Lagrangian Integrated Trajectory cluster analysis is conducted linking satellite observations of cloud properties (Spinning-Enhanced Visible and Infrared Imager), information on aerosol species (Monitoring Atmospheric Composition and Climate), and meteorological context (ERA-Interim reanalysis) to air mass clusters. It is found that a characteristic pattern of air mass origins connected to distinct synoptical conditions leads to marked cloud property changes in the southern part of the study area. Long-distance air masses are related to midlatitude weather disturbances that affect the cloud microphysics, especially in the southwestern subdomain of the study area. Changes in cloud effective radius are consistent with a boundary layer deepening and changes in lower tropospheric stability (LTS). In the southeastern subdomain cloud cover is controlled by a generally higher LTS, while air mass origin plays a minor role. This study leads to a better understanding of the dynamical drivers behind observed stratocumulus cloud properties in the SEA and frames potentially interesting conditions for aerosol-cloud interactions.

Junocam: Juno's Outreach Camera

NASA Astrophysics Data System (ADS)

Hansen, C. J.; Caplinger, M. A.; Ingersoll, A.; Ravine, M. A.; Jensen, E.; Bolton, S.; Orton, G.

2017-11-01

Junocam is a wide-angle camera designed to capture the unique polar perspective of Jupiter offered by Juno's polar orbit. Junocam's four-color images include the best spatial resolution ever acquired of Jupiter's cloudtops. Junocam will look for convective clouds and lightning in thunderstorms and derive the heights of the clouds. Junocam will support Juno's radiometer experiment by identifying any unusual atmospheric conditions such as hotspots. Junocam is on the spacecraft explicitly to reach out to the public and share the excitement of space exploration. The public is an essential part of our virtual team: amateur astronomers will supply ground-based images for use in planning, the public will weigh in on which images to acquire, and the amateur image processing community will help process the data.

Studies for the Loss of Atomic and Molecular Species from Io

NASA Technical Reports Server (NTRS)

Smyth, William H.

1998-01-01

Updated neutral emission rates for electron impact excitation of atomic oxygen and sulfur based upon the Collisional Radiative Equilibrium (COREQ) model have been incorporated in the neutral cloud models. An empirical model for the Io plasma torus wake has also been added in the neutral cloud model to describe important enhancements in the neutral emission rates and lifetime rates in this spatial region. New insights into Io's atmosphere and its interaction with the plasma torus are discussed. These insights are based upon an initial comparison of simultaneous lo observations on October 14, 1997, for [0I] 6300 Angstrom emissions acquired by groundbased facilities and several ultraviolet emissions acquired by HST/STIS in the form of high-spatial- resolution images for atomic oxygen and sulfur.

Volcanic Plume from Mt. Unzen, Dust Cloud, cloud Vortices

NASA Image and Video Library

1991-12-01

Stable, south flowing air over the western Pacific Ocean (26.0N, 131.0E) is disturbed by islands south of Korea, resulting in sinuous clouds known as von Karman vortices. The smoke plume from Japan's Mount Unzen Volcano on Kyushu, is visible just west of the large cloud mass and extending southward. A very large, purple tinged dust pall, originating in Mongolia, can be seen on the Earth's Limb, covering eastern China and extending into the East China Sea.

AIRS First Light Data: Typhoon Ramasun, July 3, 2002

NASA Technical Reports Server (NTRS)

2002-01-01

[figure removed for brevity, see original site] [figure removed for brevity, see original site] Figure 1Figure 2Figure 3

Four images of Tropical Cyclone Ramasun were obtained July 3, 2002 by the Atmospheric Infrared Sounder experiment system onboard NASA's Aqua spacecraft. The AIRS experiment, with its wide spectral coverage in four diverse bands, provides the ability to obtain complete 3-D observations of severe weather, from the surface, through clouds to the top of the atmosphere with unprecedented accuracy. This accuracy is the key to understanding weather patterns and improving weather predictions.

Viewed separately, none of these images can provide accurate 3-D descriptions of the state of the atmosphere because of interference from clouds. However, the ability to make simultaneous observations at a wide range of wavelengths allows the AIRS experiment to 'see' through clouds.

This visible light picture from the AIRS instrument provides important information about the location of the cyclone, cloud structure and distribution.

The AIRS instrument image at 900 cm-1 (Figure 1) is from a 10 micron transparent 'window channel' that is little affected by water vapor but still cannot see through clouds. In clear areas (like the eye of the cyclone and over northwest Australia) it measures a surface temperature of about 300K (color encoded red). In cloudy areas it measures the cloud top temperature, about 200K for the cyclone, which translates to a cloud top height of about 50,000 feet.

On the other hand, most clouds are relatively transparent in microwave, and the Advanced Microwave Sounding Instrument channel image (Figure 2) can see through all but the densest clouds. For example, Taiwan, which is covered by clouds, is clearly visible.

The Humidity Sounder for Brazil instrument channel (Figure 3), also in the microwave, is more sensitive to both clouds and humidity. Only in clear, dry regions, such as the eye of the cyclone or the area north of Australia, does it see the surface. It is also severely affected by suspended ice particles formed by strong convection, which causes scattering and appears to be extremely cold. These blue areas indicate intense precipitation.

The Atmospheric Infrared Sounder is an instrument onboard NASA's Aqua satellite under the space agency's Earth Observing System. The sounding system is making highly accurate measurements of air temperature, humidity, clouds and surface temperature. Data will be used to better understand weather and climate. It will also be used by the National Weather Service and the National Oceanic and Atmospheric Administration to improve the accuracy of their weather and climate models.

The instrument was designed and built by Lockheed Infrared Imaging Systems (recently acquired by British Aerospace) under contract with JPL. The Aqua satellite mission is managed by NASA's Goddard Space Flight Center.

The structure and phase of cloud tops as observed by polarization lidar

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Hansen, M. Z.; Simpson, J.

1983-01-01

High-resolution observations of the structure of cloud tops have been obtained with polarization lidar operated from a high altitude aircraft. Case studies of measurements acquired from cumuliform cloud systems are presented, two from September 1979 observations in the area of Florida and adjacent waters and a third during the May 1981 CCOPE experiment in southeast Montana. Accurate cloud top height structure and relative density of hydrometers are obtained from the lidar return signal intensity. Correlation between the signal return intensity and active updrafts was noted. Thin cirrus overlying developing turrets was observed in some cases. Typical values of the observed backscatter cross section were 0.1-5 (km/sr) for cumulonimbus tops. The depolarization ratio of the lidar signals was a function of the thermodynamic phase of cloud top areas. An increase of the cloud top depolarization with decreasing temperature was found for temperatures above and below -40 C.

Cloud Properties Derived from Surface-Based Near-Infrared Spectral Transmission

NASA Technical Reports Server (NTRS)

Pilewskie, Peter; Twomey, S.; Gore, Warren J. Y. (Technical Monitor)

1996-01-01

Surface based near-infrared cloud spectral transmission measurements from a recent precipitation/cloud physics field study are used to determine cloud physical properties and relate them to other remote sensing and in situ measurements. Asymptotic formulae provide an effective means of closely approximating the qualitative and quantitative behavior of transmission computed by more laborious detailed methods. Relationships derived from asymptotic formulae are applied to measured transmission spectra to test objectively the internal consistency of data sets acquired during the field program and they confirmed the quality of the measurements. These relationships appear to be very useful in themselves, not merely as a quality control measure, but also a potentially valuable remote-sensing technique in its own right. Additional benefits from this analysis have been the separation of condensed water (cloud) transmission and water vapor transmission and the development of a method to derive cloud liquid water content.

3D point cloud analysis of structured light registration in computer-assisted navigation in spinal surgeries

NASA Astrophysics Data System (ADS)

Gupta, Shaurya; Guha, Daipayan; Jakubovic, Raphael; Yang, Victor X. D.

2017-02-01

Computer-assisted navigation is used by surgeons in spine procedures to guide pedicle screws to improve placement accuracy and in some cases, to better visualize patient's underlying anatomy. Intraoperative registration is performed to establish a correlation between patient's anatomy and the pre/intra-operative image. Current algorithms rely on seeding points obtained directly from the exposed spinal surface to achieve clinically acceptable registration accuracy. Registration of these three dimensional surface point-clouds are prone to various systematic errors. The goal of this study was to evaluate the robustness of surgical navigation systems by looking at the relationship between the optical density of an acquired 3D point-cloud and the corresponding surgical navigation error. A retrospective review of a total of 48 registrations performed using an experimental structured light navigation system developed within our lab was conducted. For each registration, the number of points in the acquired point cloud was evaluated relative to whether the registration was acceptable, the corresponding system reported error and target registration error. It was demonstrated that the number of points in the point cloud neither correlates with the acceptance/rejection of a registration or the system reported error. However, a negative correlation was observed between the number of the points in the point-cloud and the corresponding sagittal angular error. Thus, system reported total registration points and accuracy are insufficient to gauge the accuracy of a navigation system and the operating surgeon must verify and validate registration based on anatomical landmarks prior to commencing surgery.

Quantifying the radiative and microphysical impacts of fire aerosols on cloud dynamics in the tropics using temporally offset satellite observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O.

2013-12-01

Anthropogenic fires in Southeast Asia and Central America emit smoke that affects cloud dynamics, meteorology, and climate. We measured the cloud response to direct and indirect forcing from biomass burning aerosols using aerosol retrievals from the Multi-angle Imaging SpectroRadiometer (MISR) and non-synchronous cloud retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) from collocated morning and afternoon overpasses. Level 2 data from thirty-one individual scenes acquired between 2006 and 2010 were used to quantify changes in cloud fraction, cloud droplet size, cloud optical depth and cloud top temperature from morning (10:30am local time) to afternoon (1:30pm local time) in the presence of varying aerosol burdens. We accounted for large-scale meteorological differences between scenes by normalizing observed changes to the mean difference per individual scene. Elevated AODs reduced cloud fraction and cloud droplet size and increased cloud optical depths in both Southeast Asia and Central America. In mostly cloudy regions, aerosols significantly reduced cloud fraction and cloud droplet sizes, but in clear skies, cloud fraction, cloud optical thickness and cloud droplet sizes increased. In clouds with vertical development, aerosols reduced cloud fraction via semi-direct effects but spurred cloud growth via indirect effects. These results imply a positive feedback loop between anthropogenic burning and cloudiness in both Central America and Southeast Asia, and are consistent with previous studies linking smoke aerosols to both cloud reduction and convective invigoration.

Monitoring Aircraft Motion at Airports by LIDAR

NASA Astrophysics Data System (ADS)

Toth, C.; Jozkow, G.; Koppanyi, Z.; Young, S.; Grejner-Brzezinska, D.

2016-06-01

Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.

Secure Cloud Computing Implementation Study For Singapore Military Operations

DTIC Science & Technology

2016-09-01

COMPUTING IMPLEMENTATION STUDY FOR SINGAPORE MILITARY OPERATIONS by Lai Guoquan September 2016 Thesis Advisor: John D. Fulp Co-Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE SECURE CLOUD COMPUTING IMPLEMENTATION STUDY FOR SINGAPORE MILITARY OPERATIONS 5. FUNDING NUMBERS...addition, from the military perspective, the benefits of cloud computing were analyzed from a study of the U.S. Department of Defense. Then, using

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.

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

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

2014-01-01

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

NASA Astrophysics Data System (ADS)

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.

Thirty Years of Cloud Cover Patterns from Satellite Data: Fog in California's Central Valley and Coast

NASA Astrophysics Data System (ADS)

Waller, E.; Baldocchi, D. D.

2012-12-01

In an effort to assess long term trends in winter fog in the Central Valley of California, custom maps of daily cloud cover from an approximately 30 year record of AVHRR (1981-1999) and MODIS (2000-2012) satellite data were generated. Spatial rules were then used to differentiate between fog and general cloud cover. Differences among the sensors (e.g., spectral content, spatial resolution, overpass time) presented problems of consistency, but concurrent climate station data were used to resolve systematic differences in products, and to confirm long term trends. The frequency and extent of Central Valley ("Tule") fog appear to have some periodic oscillation, but also appear to be on the decline, especially in the Sacramento Valley and in the "shoulder" months of November and February. These results may have strong implications for growers of fruit and nut trees in the Central Valley dependent on winter chill hours that are augmented by the foggy daytime conditions. Conclusions about long term trends in fog are limited to daytime patterns, as results are primarily derived from reflectance-based products. Similar analyses of daytime cloud cover are performed on other areas of concern, such as the coastal fog belt of California. Large area and long term patterns here appear to have periodic oscillation similar to that for the Central Valley. However, the relatively coarse spatial resolution of the AVHRR LTDR (Long Term Data Record) data (~5-km) may be limiting for fine-scale analysis of trends.

The Apparent Bluing of Aerosols Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. I describe a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. Examples from the MODIS observations that illustrate the apparent bluing of aerosols near clouds will be discussed.

Radiative Forcing by Contrails

NASA Technical Reports Server (NTRS)

Meerkoetter, R.; Schumann, U.; Doelling, D. R.; Nakajima, T.; Tsushima, Y.

1999-01-01

A parametric study of the instantaneous radiative impact of contrails is presented using three different radiative transfer models for a series of model atmospheres and cloud parameters. Contrails are treated as geometrically and optically thin plane parallel homogeneous cirrus layers in a static atmospheres The ice water content is varied as a function of ambient temperature. The model atmospheres include tropical, mid-latitude, and subarctic summer and winter atmospheres Optically thin contrails cause a positive net forcing at top of the atmosphere. At the surface the radiative forcing is negative during daytime. The forcing increases with the optical depth and the amount of contrail cover. At the top of the atmosphere a mean contrail cover of 0.1% with average optical depth of 0.2 to 0.5 causes about 0.01 to 0.03 W/m(exp 2)a daily mean instantaneous radiative forcing. Contrails cool the surface during the day and heat the surface during the night, and hence reduce the daily temperature amplitude The net effect depends strongly on the daily variation of contrail cloud cover. The indirect radiative forcing due to particle changes in natural cirrus clouds may be of the same magnitude as the direct one due to additional cover.

Changes in minimum and maximum temperatures at the Pic du Midi in relation with humidity and cloudiness, 1882-1984

NASA Astrophysics Data System (ADS)

Dessens, J.; Bücher, A.

In an attempt to contribute to the investigation on a global climate change, a historical series of minimum and maximum temperature data at the Pic du Midi, a mountain observatory at 2862 m a.s.l. in the French Pyrenees, is updated after correction of a systematic deviation due to a relocation of the station in 1971. These data, which now cover the 1882-1984 period, are examined in parallel with humidity and cloud cover data for the same period. From the beginning to the end of this period, observations show that the mean night-time temperature has increased by 2.39° C/100 yr while the mean daytime temperature has decreased by 0.50° C/100 yr. In consequence, the mean annual diurnal temperature range has dropped by 36%/100 yr. The maximum seasonal decrease is 46%/100 yr in spring. Season-to-season and year-to-year inter-relationships between minimum temperature, maximum temperature, relative humidity and cloud cover suggest that the decrease in maximum temperature is related to a concomitant increase of 15%/100 yr in both relative humidity and cloud cover.

Spatial and Temporal Inter-Relationships between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extratropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

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

NASA Astrophysics Data System (ADS)

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 indicators of environmental health, and can detect growth and changes in cities that are displacing historical agricultural zones.

Distribution of Aerosols in the Arctic as Observed by CALIOP

NASA Astrophysics Data System (ADS)

Winker, D.; Kittaka, C.

2007-12-01

The Arctic climate is now recognized to be uniquely sensitive to atmospheric perturbations. Pollution aerosols and smoke from boreal fires have potentially important impacts on Arctic climate but there are many uncertainties. Aerosol in the Arctic, generally referred to as "Arctic haze", has been studied with great interest for over thirty years. Much has been learned about the composition and sources of the haze yet our knowledge is largely based on long term measurements at a very few widely dispersed sites, augmented by modeling activities and occasional field campaigns. Transport pathways from source regions into the Arctic are not well understood. Emission patterns have changed over the last several decades, but the impact of this on concentrations and distribution of Arctic haze are understood only in the crudest sense. Due to poor lighting conditions, extended periods of darkness, and surfaces covered by snow and ice, satellite sensors have been unable to provide much information on Arctic haze to date. The CALIPSO satellite carries CALIOP, a two-wavelength polarization lidar, optimized for profiling clouds and aerosols. CALIOP has been acquiring global observations since June 2006 and provides our first opportunity to observe the distribution and seasonal variation of aerosol in the Arctic. The Arctic is characterized by the prevalence of optically thin ice clouds and clouds composed of supercooled water, often occurring in the same atmospheric column along with aerosol. CALIOP depolarization signals are used to discriminate Arctic haze from optically thin cirrus and diamond dust. Two-wavelength returns aid in the discrimination of aerosol and optically thin water cloud. Results of initial analyses of CALIOP aerosol observations in the Arctic will be presented. This work is a preliminary analysis in support of the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign planned for April 2008.

MACCS : Multi-Mission Atmospheric Correction and Cloud Screening tool for high-frequency revisit data processing

NASA Astrophysics Data System (ADS)

Petrucci, B.; Huc, M.; Feuvrier, T.; Ruffel, C.; Hagolle, O.; Lonjou, V.; Desjardins, C.

2015-10-01

For the production of Level2A products during Sentinel-2 commissioning in the Technical Expertise Center Sentinel-2 in CNES, CESBIO proposed to adapt the Venus Level-2 , taking advantage of the similarities between the two missions: image acquisition at a high frequency (2 days for Venus, 5 days with the two Sentinel-2), high resolution (5m for Venus, 10, 20 and 60m for Sentinel-2), images acquisition under constant viewing conditions. The Multi-Mission Atmospheric Correction and Cloud Screening (MACCS) tool was born: based on CNES Orfeo Toolbox Library, Venμs processor which was already able to process Formosat2 and VENμS data, was adapted to process Sentinel-2 and Landsat5-7 data; since then, a great effort has been made reviewing MACCS software architecture in order to ease the add-on of new missions that have also the peculiarity of acquiring images at high resolution, high revisit and under constant viewing angles, such as Spot4/Take5 and Landsat8. The recursive and multi-temporal algorithm is implemented in a core that is the same for all the sensors and that combines several processing steps: estimation of cloud cover, cloud shadow, water, snow and shadows masks, of water vapor content, aerosol optical thickness, atmospheric correction. This core is accessed via a number of plug-ins where the specificity of the sensor and of the user project are taken into account: products format, algorithmic processing chaining and parameters. After a presentation of MACCS architecture and functionalities, the paper will give an overview of the production facilities integrating MACCS and the associated specificities: the interest for this tool has grown worldwide and MACCS will be used for extensive production within the THEIA land data center and Agri-S2 project. Finally the paper will zoom on the use of MACCS during Sentinel-2 In Orbit Test phase showing the first Level-2A products.

Variability of Cloud Cover and Its Relation to Snowmelt and Runoff in the Mountainous Western United States

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.; Iacobellis, S.

2014-12-01

Obtaining accurate solar radiation input to snowmelt runoff models remains a fundamental challenge for water supply forecasters in the mountainous western U.S. The variability of cloud cover is a primary source of uncertainty in estimating surface radiation, especially given that ground-based radiometer networks in mountain terrains are sparse. Thus, remote sensed cloud properties provide a way to extend in situ observations and more importantly, to understand cloud variability in montane environment. We utilize 17 years of NASA/NOAA GOES visible albedo product with 4 km spatial and half-hour temporal resolutions to investigate daytime cloud variability in the western U.S. at elevations above 800 m. REOF/PC analysis finds that the 5 leading modes account for about two-thirds of the total daily cloud albedo variability during the whole year (ALL) and snowmelt season (AMJJ). The AMJJ PCs are significantly correlated with de-seasonalized snowmelt derived from CDWR CDEC and NRCS SNOTEL SWE data and USGS stream discharge across the western conterminous states. The sum of R2 from 7 days prior to the day of snowmelt/discharge amounts to as much as ~52% on snowmelt and ~44% on discharge variation. Spatially, the correlation patterns take on broad footprints, with strongest signals in regions of highest REOF weightings. That the response of snowmelt and streamflow to cloud variation is spread across several days indicates the cumulative effect of cloud variation on the energy budget in mountain catchments.

High-resolution mapping of Martian water ice clouds using Mars Express OMEGA observations - Derivation of the diurnal cloud life cycle

NASA Astrophysics Data System (ADS)

Szantai, Andre; Audouard, Joachim; Madeleine, Jean-Baptiste; Forget, Francois; Pottier, Alizée; Millour, Ehouarn; Gondet, Brigitte; Langevin, Yves; Bibring, Jean-Pierre

2016-10-01

The mapping in space and time of water ice clouds can help to explain the Martian water cycle and atmospheric circulation. For this purpose, an ice cloud index (ICI) corresponding to the depth of a water ice absorption band at 3.4 microns is derived from a series of OMEGA images (spectels) covering 5 Martian years. The ICI values for the corresponding pixels are then binned on a high-resolution regular grid (1° longitude x 1° latitude x 5° Ls x 1 h local time) and averaged. Inside each bin, the cloud cover is calculated by dividing the number of pixels considered as cloudy (after comparison to a threshold) to the number of all (valid) pixelsWe compare the maps of clouds obtained around local time 14:00 with collocated TES cloud observations (which were only obtained around this time of the day). A good agreement is found.Averaged ICI compared to the water ice column variable from the Martian Climate Database (MCD) show a correct correlation (~0.5) , which increases when values limited to the tropics only are compared.The number of gridpoints containing ICI values is small ( ~1%), but by taking several neighbor gridpoints and over longer periods, we can observe a cloud life cycle during daytime. An example in the the tropics, around the northern summer solstice, shows a decrease of cloudiness in the morning followed by an increase in the afternoon.

The Sensitivity of Numerical Simulations of Cloud-Topped Boundary Layers to Cross-Grid Flow

NASA Astrophysics Data System (ADS)

Wyant, Matthew C.; Bretherton, Christopher S.; Blossey, Peter N.

2018-02-01

In mesoscale and global atmospheric simulations with large horizontal domains, strong horizontal flow across the grid is often unavoidable, but its effects on cloud-topped boundary layers have received comparatively little study. Here the effects of cross-grid flow on large-eddy simulations of stratocumulus and trade-cumulus marine boundary layers are studied across a range of grid resolutions (horizontal × vertical) between 500 m × 20 m and 35 m × 5 m. Three cases are simulated: DYCOMS nocturnal stratocumulus, BOMEX trade cumulus, and a GCSS stratocumulus-to-trade cumulus case. Simulations are performed with a stationary grid (with 4-8 m s-1 horizontal winds blowing through the cyclic domain) and a moving grid (equivalent to subtracting off a fixed vertically uniform horizontal wind) approximately matching the mean boundary-layer wind speed. For stratocumulus clouds, cross-grid flow produces two primary effects on stratocumulus clouds: a filtering of fine-scale resolved turbulent eddies, which reduces stratocumulus cloud-top entrainment, and a vertical broadening of the stratocumulus-top inversion which enhances cloud-top entrainment. With a coarse (20 m) vertical grid, the former effect dominates and leads to strong increases in cloud cover and LWP, especially as horizontal resolution is coarsened. With a finer (5 m) vertical grid, the latter effect is stronger and leads to small reductions in cloud cover and LWP. For the BOMEX trade cumulus case, cross-grid flow tends to produce fewer and larger clouds with higher LWP, especially for coarser vertical grid spacing. The results presented are robust to choice of scalar advection scheme and Courant number.

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

NASA Technical Reports Server (NTRS)

Fairall, C. W.; Hare, J. E.; Snider, Jack B.

1990-01-01

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Remote-Sensing Data Distribution and Processing in the Cloud at the ASF DAAC

NASA Astrophysics Data System (ADS)

Stoner, C.; Arko, S. A.; Nicoll, J. B.; Labelle-Hamer, A. L.

2016-12-01

The Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) has been tasked to archive and distribute data from both SENTINEL-1 satellites and from the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite in a cost effective manner. In order to best support processing and distribution of these large data sets for users, the ASF DAAC enhanced our data system in a number of ways that will be detailed in this presentation.The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band Synthetic Aperture Radar (SAR) imaging, enabling them to acquire imagery regardless of the weather. SENTINEL-1A was launched by the European Space Agency (ESA) in April 2014. SENTINEL-1B is scheduled to launch in April 2016.The NISAR satellite is designed to observe and take measurements of some of the planet's most complex processes, including ecosystem disturbances, ice-sheet collapse, and natural hazards such as earthquakes, tsunamis, volcanoes and landslides. NISAR will employ radar imaging, polarimetry, and interferometry techniques using the SweepSAR technology employed for full-resolution wide-swath imaging. NISAR data files are large, making storage and processing a challenge for conventional store and download systems.To effectively process, store, and distribute petabytes of data in a High-performance computing environment, ASF took a long view with regard to technology choices and picked a path of most flexibility and Software re-use. To that end, this Software tools and services presentation will cover Web Object Storage (WOS) and the ability to seamlessly move from local sunk cost hardware to public cloud, such as Amazon Web Services (AWS). A prototype of SENTINEL-1A system that is in AWS, as well as a local hardware solution, will be examined to explain the pros and cons of each. In preparation for NISAR files which will be even larger than SENTINEL-1A, ASF has embarked on a number of cloud initiatives, including processing in the cloud at scale, processing data on-demand, and processing end-user computations on DAAC data in the cloud.

Integrating solar energy and climate research into science education

NASA Astrophysics Data System (ADS)

Betts, Alan K.; Hamilton, James; Ligon, Sam; Mahar, Ann Marie

2016-01-01

This paper analyzes multi-year records of solar flux and climate data from two solar power sites in Vermont. We show the inter-annual differences of temperature, wind, panel solar flux, electrical power production, and cloud cover. Power production has a linear relation to a dimensionless measure of the transmission of sunlight through the cloud field. The difference between panel and air temperatures reaches 24°C with high solar flux and low wind speed. High panel temperatures that occur in summer with low wind speeds and clear skies can reduce power production by as much as 13%. The intercomparison of two sites 63 km apart shows that while temperature is highly correlated on daily (R2=0.98) and hourly (R2=0.94) timescales, the correlation of panel solar flux drops markedly from daily (R2=0.86) to hourly (R2=0.63) timescales. Minimum temperatures change little with cloud cover, but the diurnal temperature range shows a nearly linear increase with falling cloud cover to 16°C under nearly clear skies, similar to results from the Canadian Prairies. The availability of these new solar and climate datasets allows local student groups, a Rutland High School team here, to explore the coupled relationships between climate, clouds, and renewable power production. As our society makes major changes in our energy infrastructure in response to climate change, it is important that we accelerate the technical education of high school students using real-world data.

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Roeckner, E.; Zhang, J.

2007-03-01

The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, 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 -1.8 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed.

Weather on Titan

NASA Astrophysics Data System (ADS)

Griffith, C. A.; Hall, J. L.; Geballe, T. R.

2000-10-01

Titan's atmosphere potentially sports a cycle similar to the hydrologic one on Earth with clouds, rain and seas, but with methane playing the terrestrial role of water. Over the past ten years many independent efforts indicated no strong evidence for cloudiness until some unique spectra were analyzed in 1998 (Griffith et al.). These surprising observations displayed enhanced fluxes of 14-200% on two nights at precisely the wavelengths (windows) that sense Titan's lower altitude where clouds might reside. The morphology of these enhancements in all 4 windows observed indicate that clouds covered ~6-9% of Titan's surface and existed at ~15 km altitude. Here I discuss new observations recorded in 1999 aimed to further characterize Titan's clouds. While we find no evidence for a massive cloud system similar to the one observed previously, 1%-4% fluctuations in flux occur daily. These modulations, similar in wavelength and morphology to the more pronounced ones observed earlier, suggest the presence of clouds covering <=1% of Titan's disk. The variations are too small to have been detected by most prior measurements. Repeated observations, spaced 30 minutes apart, indicate a temporal variability observable in the time scale of a couple of hours. The cloud heights hint that convection governs their evolutions. Their short lives point to the presence of rain. C. A. Griffith and J. L. Hall are supported by the NASA Planetary Astronomy Program NAG5-6790.