Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
NWCSAF AVHRR cloud detection and analysis using dynamic thresholds and radiative transfer modeling. Part II: Tuning and validation
SMHI, Core Services.
SMHI, Research Department, Atmospheric remote sensing.ORCID iD: 0000-0001-8256-0228
SMHI, Research Department, Atmospheric remote sensing.ORCID iD: 0000-0003-2138-4325
2005 (English)In: Journal of applied meteorology (1988), ISSN 0894-8763, E-ISSN 1520-0450, Vol. 44, no 1, 55-71 p.Article in journal (Refereed) Published
Abstract [en]

Algorithms for cloud detection (cloud mask) and classification (cloud type) at high and midlatitudes using data from the Advanced Very High Resolution Radiometer (AVHRR) on board the current NOAA satellites and future polar Meteorological and Operational Weather Satellites (METOP) of the European Organisation for the Exploitation of Meteorological Satellites have been extensively validated over northern Europe and the adjacent seas. The algorithms have been described in detail in Part I and are based on a multispectral grouped threshold approach, making use of cloud-free radiative transfer model simulations. The thresholds applied in the algorithms have been validated and tuned using a database interactively built up over more than 1 yr of data from NOAA-12, -14, and -15 by experienced nephanalysts. The database contains almost 4000 rectangular (in the image data)-sized targets (typically with sides around 10 pixels), with satellite data collocated in time and space with atmospheric data from a short-range NWP forecast model, land cover characterization, elevation data, and a label identifying the given cloud or surface type as interpreted by the nephanalyst. For independent and objective validation, a large dataset of nearly 3 yr of collocated surface synoptic observation (Synop) reports, AVHRR data, and NWP model output over northern and central Europe have been collected. Furthermore, weather radar data were used to check the consistency of the cloud type. The cloud mask performs best over daytime sea and worst at twilight and night over land. As compared with Synop, the cloud cover is overestimated during night (except for completely overcast situations) and is underestimated at twilight. The algorithms have been compared with the more empirically based Swedish Meteorological and Hydrological Institute (SMHI) Cloud Analysis Model Using Digital AVHRR Data (SCANDIA), operationally run at SMHI since 1989, and results show that performance has improved significantly.

Place, publisher, year, edition, pages
2005. Vol. 44, no 1, 55-71 p.
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
URN: urn:nbn:se:smhi:diva-1289DOI: 10.1175/JAM-2189.1ISI: 000227145800005OAI: oai:DiVA.org:smhi-1289DiVA: diva2:818690
Available from: 2015-06-09 Created: 2015-05-26 Last updated: 2015-06-09Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Dybbroe, AdamKarlsson, Karl-GöranThoss, Anke
By organisation
Core ServicesAtmospheric remote sensing
In the same journal
Journal of applied meteorology (1988)
Meteorology and Atmospheric Sciences

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 18 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.28.0
|