Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Computationally efficient method for retrieving aerosol optical depth from ATSR-2 and AATSR data.

William M F Grey1, Peter R J North, Sietse O Los

  • 1Climate and Land Surface Systems Interaction Centre, School of Environment and Society, Swansea University, United Kingdom. w.m.f.grey@swan.ac.uk

Applied Optics
|April 25, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A global climate niche for giant trees.

Global change biology·2018
Same author

Morton et al. reply.

Nature·2016
Same author

Amazon forests maintain consistent canopy structure and greenness during the dry season.

Nature·2014
See all related articles

This study introduces an efficient method to calculate aerosol optical depth (AOD) using ATSR-2 and AATSR satellite data. The approach accurately estimates global AOD from an 11-year archive, correlating well with ground-based measurements.

Area of Science:

  • Earth Observation
  • Atmospheric Science
  • Remote Sensing

Background:

  • Accurate aerosol optical depth (AOD) retrieval is crucial for climate modeling and air quality monitoring.
  • Existing methods often require extensive computational resources or a priori land surface information.

Purpose of the Study:

  • To develop a computationally efficient and robust method for global AOD retrieval from ATSR-2 and AATSR data.
  • To utilize the 11-year (A)ATSR archive for long-term AOD trend analysis.

Main Methods:

  • A physical light scattering model is employed, eliminating the need for prior land surface data.
  • Precalculated lookup tables (LUTs) are used for efficient numerical inversion of atmospheric radiative transfer models.
  • The method is applied to top-of-atmosphere reflectance data from ATSR-2 and AATSR.

Related Experiment Videos

Main Results:

  • The developed method demonstrates computational efficiency for global-scale AOD retrieval.
  • Retrieved AOD estimates from AATSR data show high correlation with 550 nm sunphotometer measurements (r² = 0.71).
  • The approach is validated across diverse global land surfaces.

Conclusions:

  • The LUT-based approach provides a reliable and efficient means for retrieving AOD from historical (A)ATSR data.
  • This method facilitates long-term global aerosol monitoring and climate studies.
  • The technique offers a valuable tool for atmospheric research without requiring a priori surface information.