TY - JOUR

T1 - Comparison of CO2 Content in the Atmosphere of St. Petersburg According to Numerical Modeling and Observations

AU - Nerobelov, G. M.

AU - Timofeyev, Yu. M.

AU - Smyshlyaev, S. P.

AU - Foka, S. Ch.

AU - Imhasin, H. H.

PY - 2023/6/1

Y1 - 2023/6/1

N2 - Abstract: Due to the increase in CO2 content in the earth’s atmosphere, which is highly dependent on anthropogenic emissions of CO2, the quality of emission estimation should be improved. Advanced experiment-based methods of the CO2 anthropogenic emission estimation are built on solving an inverse problem using highly accurate measurements of CO2 content and numerical models of transport and chemistry in the atmosphere. The accuracy of such models greatly determines the errors of the emission estimations. In the current study, temporal variations of column-average CO2 content in an atmospheric layer from the surface to a height of ~70–75 km (XCO2) in the Russian metropolis of St. Petersburg from January 2019 to March 2020 simulated by the WRF-Chem model and measured by a Bruker EM27/SUN IR Fourier transform spectrometer are compared. The research has demonstrated that the WRF-Chem model simulates the observed temporal variation of XCO2 in the area of St. Petersburg well (correlation coefficient of ~0.95). However, using CarbonTracker v2022-1 data as chemical boundary conditions, the model overestimates XCO2 relative to the observations significantly during almost the entire period of investigation—systematic difference and standard deviation of the difference are 4.2 and 1.9 ppm (1 and 0.5%). A correction of the chemical boundary conditions which is based on an analysis of a relation between near-surface wind direction and XCO2 variation notably decreases the systematic difference between the modeled and observed data (almost by a factor of 2). The XCO2 variation by the observations and modeling with uncorrected chemical boundary conditions are in a better agreement during vegetation season. This is probably related to the compensation of the systematic difference by inaccuracies in estimated biogenic contribution. Hence, the reason for the still existing mean difference between the modeled and observed data can be inaccuracies in setting chemical boundary conditions for the upper troposphere and in estimating how the biosphere influences CO2 content.

AB - Abstract: Due to the increase in CO2 content in the earth’s atmosphere, which is highly dependent on anthropogenic emissions of CO2, the quality of emission estimation should be improved. Advanced experiment-based methods of the CO2 anthropogenic emission estimation are built on solving an inverse problem using highly accurate measurements of CO2 content and numerical models of transport and chemistry in the atmosphere. The accuracy of such models greatly determines the errors of the emission estimations. In the current study, temporal variations of column-average CO2 content in an atmospheric layer from the surface to a height of ~70–75 km (XCO2) in the Russian metropolis of St. Petersburg from January 2019 to March 2020 simulated by the WRF-Chem model and measured by a Bruker EM27/SUN IR Fourier transform spectrometer are compared. The research has demonstrated that the WRF-Chem model simulates the observed temporal variation of XCO2 in the area of St. Petersburg well (correlation coefficient of ~0.95). However, using CarbonTracker v2022-1 data as chemical boundary conditions, the model overestimates XCO2 relative to the observations significantly during almost the entire period of investigation—systematic difference and standard deviation of the difference are 4.2 and 1.9 ppm (1 and 0.5%). A correction of the chemical boundary conditions which is based on an analysis of a relation between near-surface wind direction and XCO2 variation notably decreases the systematic difference between the modeled and observed data (almost by a factor of 2). The XCO2 variation by the observations and modeling with uncorrected chemical boundary conditions are in a better agreement during vegetation season. This is probably related to the compensation of the systematic difference by inaccuracies in estimated biogenic contribution. Hence, the reason for the still existing mean difference between the modeled and observed data can be inaccuracies in setting chemical boundary conditions for the upper troposphere and in estimating how the biosphere influences CO2 content.

KW - Bruker EE27/SUN

KW - CarbonTracker

KW - WRF-Chem

KW - XCO2 in St. Petersburg

KW - anthropogenic emissions of CO2

KW - remote measurements

UR - https://www.mendeley.com/catalogue/acfa2882-aadd-3388-a255-1f34ec9d4d32/

U2 - 10.1134/s0001433823020056

DO - 10.1134/s0001433823020056

M3 - Article

VL - 59

SP - 275

EP - 286

JO - Izvestiya, Atmospheric and Oceanic Physics

JF - Izvestiya, Atmospheric and Oceanic Physics

SN - 0001-4338

IS - 3

ER -