Martin Kannel will defend his doctoral thesis titled "Development of broadband aerosol optical depth models"
on 10. June 2016 at 14.15 at W. Ostwaldi 1, room B103.
Hanno Ohvril, Institute of Physics, University of Tartu
Priit Tisler, Finnish Institut of Meteorology
Enn Kaup, Tallinn University of Technology
In meteorological practice the Sun is considered as a stable source of light. The amount of broadband solar energy encompassing all wavelengths, incident on a unit area at the top of the atmosphere (TOA) may be calculated with a high precision. The ratio between the solar intensity at the Earth’s surface after attenuation in the air, and this at the TOA, easily gives atmospheric optical depth. It is convenient to divide atmosphere into three virtual layers based on attenuation reasons:
a) atmospheric base-gases (mainly nitrogen, oxygen and argon), also known as a clean and dry atmosphere (CDA),
b) water vapor,
c) aerosol particles (smokes, dusts, fogs).
In terms of atmospheric optics, each layer has its own broadband optical depth. The most interesting is the layer of aerosol particles. Its characterization with broadband aerosol optical depth (BAOD) was in Estonia feasible already in the 1930s. Measurements of BAOD’s spectral counterpart, AODλ, became available only since June 2002, after enlargement of NASA AERONET project to Tõravere. Compared to BAOD, spectral approach allows considerably more detailed investigation of aerosols. Starting writing the thesis, it was logical to look for a correlation between BAOD and AOD500. This correlation was found and it allowed transition from BAOD to AOD500. Considerable part of the thesis is dedicated to test runs of created computational scheme and to comparisons with other broadband models elaborated in USA and Russia. Although all models gave reasonable results for estimating AOD500, this work's model performed slightly better. Concerning environmental research, a practical benefits from use of created model for estimation of AOD500 would be: a) retrospective retrieval of AOD500 for periods in the past when spectral measurements were not available, b) a quick AOD500 estimation for correction of satellite remotely sensed data, c) quality assurance of recorded spectral data.