Research output: Contribution to journal › Article › peer-review
Technique for Determining Tropospheric Ozone Content from Spectral Measurements of Outgoing Thermal Radiation by the IKFS-2 Satellite Instrument. / Поляков, Александр Викторович; Виролайнен, Яна Акселевна; Неробелов, Георгий Максимович; Акишина, Светлана Васильевна.
In: Izvestiya - Atmospheric and Oceanic Physics, Vol. 60, No. 5, 01.10.2024, p. 533-543.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Technique for Determining Tropospheric Ozone Content from Spectral Measurements of Outgoing Thermal Radiation by the IKFS-2 Satellite Instrument
AU - Поляков, Александр Викторович
AU - Виролайнен, Яна Акселевна
AU - Неробелов, Георгий Максимович
AU - Акишина, Светлана Васильевна
PY - 2024/10/1
Y1 - 2024/10/1
N2 - A technique for determining the tropospheric ozone (TO) content from the spectra of outgoing thermal infrared (IR) radiation based on the principal component method and neural network approach is proposed. To train the artificial neural networks, TO data calculated from ozone profiles of vertical ozone content derived from ozonesondes are used. The TCO is considered the ozone content in the atmospheric layers from the earth’s surface to pressure levels of 400 and 300 hPa. The error of approximating TO values on training data is 2.7 and 3.6 DU for layers below 400 and 300 hPa, respectively. The methodology is validated on the basis of comparison with ground-based TO measurements at the NDACC international observing network of stations using solar infrared spectra. The mean standard deviations of the differences between the groundbased infrared measurements at 19 stations and the derived TO values from the IKFS-2 data were about 3 DU.The mean differences depend on the altitude and geographical location of the ground station, varying from +3 to –12 DU. The discrepancies between the ground-based measurements and satellite data correspond to the results of other authors obtained for the IASI satellite instrument, which is close in characteristics. The paper presents examples of the global distribution of mean monthly TO values for different seasons.
AB - A technique for determining the tropospheric ozone (TO) content from the spectra of outgoing thermal infrared (IR) radiation based on the principal component method and neural network approach is proposed. To train the artificial neural networks, TO data calculated from ozone profiles of vertical ozone content derived from ozonesondes are used. The TCO is considered the ozone content in the atmospheric layers from the earth’s surface to pressure levels of 400 and 300 hPa. The error of approximating TO values on training data is 2.7 and 3.6 DU for layers below 400 and 300 hPa, respectively. The methodology is validated on the basis of comparison with ground-based TO measurements at the NDACC international observing network of stations using solar infrared spectra. The mean standard deviations of the differences between the groundbased infrared measurements at 19 stations and the derived TO values from the IKFS-2 data were about 3 DU.The mean differences depend on the altitude and geographical location of the ground station, varying from +3 to –12 DU. The discrepancies between the ground-based measurements and satellite data correspond to the results of other authors obtained for the IASI satellite instrument, which is close in characteristics. The paper presents examples of the global distribution of mean monthly TO values for different seasons.
KW - IKFS-2
KW - remote sensing of the atmosphere
KW - tropospheric ozone
UR - https://www.mendeley.com/catalogue/ca266d4e-c7d8-3f85-972c-659dbb7cc192/
U2 - 10.1134/s000143382470049x
DO - 10.1134/s000143382470049x
M3 - Article
VL - 60
SP - 533
EP - 543
JO - Izvestiya, Atmospheric and Oceanic Physics
JF - Izvestiya, Atmospheric and Oceanic Physics
SN - 0001-4338
IS - 5
ER -
ID: 127596735