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Monday, May 11, 2020 | History

3 edition of Cloud cover classification of AVHRR imagery of North British waters found in the catalog.

Cloud cover classification of AVHRR imagery of North British waters

Anderson, J. M.

Cloud cover classification of AVHRR imagery of North British waters

October 1978-September 1983

by Anderson, J. M.

  • 38 Want to read
  • 20 Currently reading

Published by University of Dundee in Dundee .
Written in English


Edition Notes

StatementJ.M. Anderson andA.P. Cracknell. 3.
ContributionsCracknell, A. P. 1940-
ID Numbers
Open LibraryOL20063846M
ISBN 100901396168
OCLC/WorldCa213799787

  Cloud properties from 8 years (–93) of the ISCCP are summarized in Table average cloud cover and the day–night differences are slightly different than those obtained from surface observations (Table 1).The optical thickness (opacity) and cloud water path (vertically integrated liquid water content) inferred from the satellite radiances are smaller . Global Maps Jul — Dec Net radiation is the balance between incoming and outgoing energy at the top of the atmosphere. It is the total energy available to influence climate after light and heat are reflected, absorbed, or emitted by clouds and land. Global Maps Mar — Dec Greenness is an important indicator of health for.

  Cloud cover frequency in the UK leads to a requirement for higher temporal resolution remote sensing data to monitor changes in vegetation phenology. This research shows that on the basis of satellite-derived cloud cover data at least one cloud-free image per month (and often more) may be acquired at both sites in the North West of England. EPA//R/ July A Research Plan for the Use of Thermal AVHRR Imagery to Study Annual and Seasonal Mean Surface Temperatures for Large Lakes in North America Principal Investigator S. Taylor Jarnagin Co-Investigator E. Terrence Slonecker NERL/ESD/LEB/EPIC Sunrise Valley Drive National Center Reston, Virginia .

Even in the VIS image the cloud top is rather flat and featureless, but the edges of the cloud sheet are clearly distinguishable in places where there are no overlying upper level clouds. The Water vapour image shows only the water vapour content in the upper and middle troposphere and does not directly help the detection of St/Fog. Snow cover changes the heat and water flow between soil and atmosphere and changes the radiative properties of the surface. Metop/AVHRR product have some overlap in the images in the North, but usually there is only one image per day. Cloud cover is not as extensive as in the February case and both products cover most of the Europe. In.


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Cloud cover classification of AVHRR imagery of North British waters by Anderson, J. M. Download PDF EPUB FB2

Using imagery from NOAA's Advanced Very High Resolution Radiometer (AVHRR) orbiting sensor, one of the authors (RLB) earlier developed a probabilistic neural network cloud classifier valid over. Cloud Cover Classification of AVHRR Imagery of North Brit-ish Waters 3, October September (f.

Anderson and A. Cracknell,pp., $, paperbound, from University of Dundee, Scotland). The Advanced Very High Resolution Radiometer (AVHRR) that accompanied the TI-RO S-N satellite that was launched in generated data that.

Pressure Reconstructions for Europe (Back to ) and North America (to ),National Technical Information Service (6/87) Cracknell, A. (with J. Anderson), Cloud Cover Classification of AVHRR Imagery of North British Waters 3.

October Sep tember, University of Dundee (11/87). cloud fraction is realized over snow and ice surfaces; over open water or snow-free land, all versions perform similarly.

Since the inclusion of SMMR for surface analysis and additional. A new cloud detection algorithm for nighttime Advanced Very High Resolution Radiometer (AVHRR) data has been developed and applied to a large number of images from various locations around Japan.

An algorithm for the remote sensing of global cloud cover using multispectral radiance measurements from the Advanced Very High Resolution Radiometer (AVHRR) on board National Oceanic and. The approach converts AVHRR Channel 1 and 2 data to a land and water thematic image, finds the offset to maximize classification accuracy, and repositions the AVHRR and SST images.

Application of Satellite AVHRR to Water Balance, Mixing Dynamics, and the Chemistry of Lake Edward, East Africa. Abstract. Surface heat balance and evaporation rates for Lake Edward were calculated as part of a model for mixed layer dynamics.

Evaporation rates were combined with rainfall and fluvial income to estimate water by: Smoke is shown in yellow, clouds in pink and white, and land in green. It was created by combining two NN outputs (“smoke” and “clouds”) in red, reflectance from channel 2 AVHRR in green, and output NN of “cloud” alone in blue.

Fire pixels, detected using the algorithm of Li et al. (), are shown in red. The classification of clouds is based on a book written by Luke Howard, a London pharmacist and amateur meteorologist, in His book, The Modifications of Clouds, named the various cloud structures he had studied.

The Sun is very similar to a black body. Despite significant variations of the solar spectrum near the surface due to many atmospheric processes, especially clouds, total solar radiation in space has been found to be fairly constant.

For example, at km ASL, the daily average total solar radiation ranged from to W m −2. Tucker & Choudhury () produced cloud-free NDVI single date images by using AVHRR thermal radiation as a cloud mask. The resulting images were used to study drought conditions in the Sahel.

Mill-ington et al. (a) have conducted a comprehensive study of land cover for the entire continent of Africa south of the Sahara, emphasizing the. Land Cover Distribution and Assessment. From the interpretation of /93 AVHRR data four major land cover types viz.

forests, agriculture, paddy field (irrigated) and waterbodies were discerned. It was extremely difficult to discriminate evergreen and deciduous forests in the north as they occur in complex mosaic.

temporal information improved the classification results, with an overall accuracy of ca. 82% for 10 classes [25]. Five land use/land cover types (forests, urban infrastructure, surface water and marsh wetland) were mapped from multi-temporal polarimetric RADARSAT-2 imagery in North-eastern Ontario, Canada [26].File Size: 2MB.

By providing data of higher spatial resolution and, in some cases, of higher absolute accuracy, satellite infrared scanning radiometers complement those detecting microwave radiation.

Infrared measurements are, however, much more susceptible to contamination by the presence of by: 2. cloud classification[′klau̇d ‚klasəfə′kāshən] (meteorology) A scheme of distinguishing and grouping clouds according to their appearance and, where possible, to their process of formation.

A scheme of classifying clouds according to their altitudes: high, middle, or low clouds. A scheme of classifying clouds according to their. Analysis of satellite imagery, compared with colocated PIREPs, indicates that CAT is found not only in clear air but also in cirrus clouds, and along borders of large-scale convective cloud systems.

Zones of turbulence associated with the subtropical jet stream and convective outflow are often denoted by pronounced cirrus cloud bands that are. This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems.

Severe weather can Cited by: Considering the resolution, the frequency of image availability and the cost of the images (Kite, ), it was decided to develop a model which would use Landsat images for a land-use classification of a basin and to use National Oceanic and Atmospheric Adminstration/Advanced Very High Resolution Ra~diometer (NOAA/AVHRR) imagery for daily data Cited by: A logistic model was constructed to assess the risk of forest fire and tested over the central region of Mexico.

The model incorporates both static and dynamic predictive variables: elevation, aspect, slope, vegetation type, precipitation, Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and cloud cover.

The latter three variables were derived from National Cited by:. By contrast, clouds and snow tend to be rather bright in the red (as well as other visible wavelengths) and quite dark in the near-infrared. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from to µm) for use in photosynthesis.

The cell structure of the leaves, on the other hand.Imagery available from AVHRR Imagery Janu Atchafalaya Bay SST. Daily Swaths. GCOOS SST. Gulf of Mexico SST. Mississippi River Plume SST. See all AVHRR images for Janu Filter Results.

Area: Variable: Satellite: Found 1 images. Jan 10 UTC AVHRR Swath.Cover Application of the NOAA-AVHRR images to the study of the large forest fires in Spain in the summer of Interactions between land cover and convective cloud cover over Midwestern North America detected from GOES satellite data.

M. O'NEAL. Pages: Classification of remotely-sensed imagery using an indicator kriging.