Atmosphere aerosol modeling by GEOS-Chem for the “Aerosol-UA” space project validation
Heading:
| 1Miatselskaya, NS, 1Kabashnikov, VP, Norko, AV, 1Chaikovsky, AP, Bril, AI, 2Milinevsky, GP, 3Danylevsky, VO 1B.I. Stepanov Institute of Physics of the National Academy of Sciences of Belarus, Minsk, Belarus 2Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine 3Astronomical Observatory of the Taras Shevchenko National University of Kyiv, Kyiv, Ukraine; (2) Main Astronomical Observatory of the NAS of Ukraine, Kyiv, Ukraine |
| Space Sci.&Technol. 2017, 23 ;(3):03-10 |
| https://doi.org/10.15407/knit2017.03.003 |
| Publication Language: English |
Abstract: We used a global chemical transport model GEOS-Chem to compute monthly mean fine, coarse, and total aerosol volume concentration for Minsk and Kyiv in the period from 2010 to 2015. We compared results of the model simulation with sun-photometer observations at the ground-based AERONET network sites. We obtained that the aerosol volume concentrations retrieved from observations are in reasonably good agreement with model-simulated ones. However, the agreement is not good enough for the validation of the results of simulation with the satellite measurements in the future space mission Aerosol-UA.
To improve the accuracy of estimating the spatial-temporal distribution of the aerosol volume concentration we decided to apply the optimal interpolation method for assimilating AERONET data in GEOS-Chem model. The temporal correlation function for fine aerosol volume concentration is obtained on the basis of measurements at AERONET Minsk site over the 2002−2015 period and Kyiv site over the 2008−2015 period. We describe the analyzed values of fine aerosol volume concentration at all temporal grid points over the period of 2002 to 2015 for Minsk site and of 2008 to 2015 for Kyiv site, which were determined on the basis of the optimal interpolation method. We propose to use the optimal averaging method for AERONET data on the basis of the temporal optimization interpolation method.
|
| Keywords: aerosol, chemical transport GEOS-Chem, data assimilation, sun photometer |
References:
1. Milinevsky G., Yatskiv Ya., Degtyaryov O., et al. Remote sensing of aerosol in the terrestrial atmosphere from space:new missions. Advs in Astron. and Space Phys., 5, 11—16 (2015).
https://doi.org/10.17721/2227-1481.5.11-16
2. Milinevsky G., Yatskiv Ya., Degtyaryov O., et al. New satellite project Aerosol-UA: Remote sensing of aerosols in the terrestrial atmosphere. Acta Astronautica, 123, 292—300 (2016).
https://doi.org/10.1016/j.actaastro.2016.02.027
3. Sica R. J., Izawa M. R. M., Walker K. A., et al. Validation of the Atmospheric Chemistry Experiment (ACE) version 2.2 temperature using ground-based and space-borne measurements. Atmospheric Chemistry and Phys.,8 , 35—62 (2008).
https://doi.org/10.5194/acp-8-35-2008
https://doi.org/10.17721/2227-1481.5.11-16
2. Milinevsky G., Yatskiv Ya., Degtyaryov O., et al. New satellite project Aerosol-UA: Remote sensing of aerosols in the terrestrial atmosphere. Acta Astronautica, 123, 292—300 (2016).
https://doi.org/10.1016/j.actaastro.2016.02.027
3. Sica R. J., Izawa M. R. M., Walker K. A., et al. Validation of the Atmospheric Chemistry Experiment (ACE) version 2.2 temperature using ground-based and space-borne measurements. Atmospheric Chemistry and Phys.,8 , 35—62 (2008).
https://doi.org/10.5194/acp-8-35-2008
4. Ionov D. V., Timofeyev Y. M., Sinyakov V. P., et al. Groundbased validation of EOS-Aura OMI NO2 vertical column data in the midlatitude mountain ranges of Tien Shan (Kyrgyzstan) and Alps (France). J. Geophys. Res., 113, D15S08 (2008).
https://doi.org/10.1029/2007JD008659
5. Brogniez C., Auriol F., Deroo C., et al. Validation of satellite-based noontime UVI with NDACC groundbased instruments: influence of topography, environment and satellite overpass time. Atmos. Chem. Phys., 16, 15049—15074 (2016).
https://doi.org/10.5194/acp-16-15049-2016
6. Holben B. N., Eck T. F., Slutsker I., et al. AERONET — A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 1—16 (1998).
https://doi.org/10.1016/S0034-4257(98)00031-5
https://doi.org/10.1029/2007JD008659
5. Brogniez C., Auriol F., Deroo C., et al. Validation of satellite-based noontime UVI with NDACC groundbased instruments: influence of topography, environment and satellite overpass time. Atmos. Chem. Phys., 16, 15049—15074 (2016).
https://doi.org/10.5194/acp-16-15049-2016
6. Holben B. N., Eck T. F., Slutsker I., et al. AERONET — A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 1—16 (1998).
https://doi.org/10.1016/S0034-4257(98)00031-5
7. Holben B. N., Tanre D., Smirnov A., et al. An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET. J. Geophys. Res.: Atmospheres, 106, 12067—12097 (2001).
https://doi.org/10.1029/2001JD900014
8. Milinevsky G., Danylevsky V., Bovchaliuk V., et al. Aerosol seasonal variations over urban sites in Ukraine and Belarus according to AERONET and POLDER measurements. Atmospheric Measurements Techniques, 7(5), 1459—1474 (2014).
https://doi.org/10.5194/amt-7-1459-2014
9 . Bovchaliuk A., Milinevsky G., Danylevsky V., et al. Variability of aerosol properties over Eastern Europe observed from ground and satellites in the period from 2003 to 2011. Atmospheric Chemistry and Physics, 13(13), 6587—6602 (2013).
https://doi.org/10.5194/acp-13-6587-2013
10. Dubovik O., King M. D. A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. J. Geophys. Res., 105(D16), 20673—20696 (2000).
https://doi.org/10.1029/2000JD900282
11. Miatselskaya N., Kabashnikov V., Milinevsky G., et al. Atmospheric aerosol distribution in the Belarus-Ukraine region by the GEOS–Chem model and AERONET measurements, International J. Remote Sensing, 37(14), 3181—3195 (2016).
http://doi.org/10.1080/01431161.2016.1194541
12. Molod A., Takacs L., Suarez M., et al. The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna. Technical Report Series on Global Modeling and Data Assimilation, 28 (2012).
13. Bey I., Jacob D. J., Yantosca R. M., et al. Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. J. Geophys. Res., 106 (D19), 23073—23095 (2001).
https://doi.org/10.1029/2001JD000807
14. Martin R. V., Jacob D. J., Yantosca R. M., et al. Global and regional decreases in tropospheric oxidants from photochemical effects of aerosols. J. Geophys. Res: Atmospheres (1984—2012), 108(D3). ACH 6-1–ACH 6-9 (2003).
https://doi.org/10.1029/2002JD002622
15. GandinL. S. Objective Analysis of Meteorological Fields.(Israel Program for Scientific Trans.), (Gidrometeorologicheskoe Izdatelstvo, Leningrad, 1963).
16. Lorenc A. C. Analysis methods for numerical weather prediction. Quart. J. R. Met. Soc., 112, 1177—1194 (1986).
https://doi.org/10.1002/qj.49711247414
https://doi.org/10.1029/2001JD900014
8. Milinevsky G., Danylevsky V., Bovchaliuk V., et al. Aerosol seasonal variations over urban sites in Ukraine and Belarus according to AERONET and POLDER measurements. Atmospheric Measurements Techniques, 7(5), 1459—1474 (2014).
https://doi.org/10.5194/amt-7-1459-2014
9 . Bovchaliuk A., Milinevsky G., Danylevsky V., et al. Variability of aerosol properties over Eastern Europe observed from ground and satellites in the period from 2003 to 2011. Atmospheric Chemistry and Physics, 13(13), 6587—6602 (2013).
https://doi.org/10.5194/acp-13-6587-2013
10. Dubovik O., King M. D. A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. J. Geophys. Res., 105(D16), 20673—20696 (2000).
https://doi.org/10.1029/2000JD900282
11. Miatselskaya N., Kabashnikov V., Milinevsky G., et al. Atmospheric aerosol distribution in the Belarus-Ukraine region by the GEOS–Chem model and AERONET measurements, International J. Remote Sensing, 37(14), 3181—3195 (2016).
http://doi.org/10.1080/01431161.2016.1194541
12. Molod A., Takacs L., Suarez M., et al. The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna. Technical Report Series on Global Modeling and Data Assimilation, 28 (2012).
13. Bey I., Jacob D. J., Yantosca R. M., et al. Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. J. Geophys. Res., 106 (D19), 23073—23095 (2001).
https://doi.org/10.1029/2001JD000807
14. Martin R. V., Jacob D. J., Yantosca R. M., et al. Global and regional decreases in tropospheric oxidants from photochemical effects of aerosols. J. Geophys. Res: Atmospheres (1984—2012), 108(D3). ACH 6-1–ACH 6-9 (2003).
https://doi.org/10.1029/2002JD002622
15. GandinL. S. Objective Analysis of Meteorological Fields.(Israel Program for Scientific Trans.), (Gidrometeorologicheskoe Izdatelstvo, Leningrad, 1963).
16. Lorenc A. C. Analysis methods for numerical weather prediction. Quart. J. R. Met. Soc., 112, 1177—1194 (1986).
https://doi.org/10.1002/qj.49711247414
17. Zhang, X. F., Heemink, A. W., van Eijkeren, J. C. H. Data assimilation in transport models. Appl. Math. Modelling, 21, 2—14 (1997).
https://doi.org/10.1016/S0307-904X(96)00107-2
18. Smirnov A., Holben B. N., Eck T. F., et al. Cloud-screening and Quality Control Algorithms for the AERONET Database. Remote Sens. Environ., 73, 337—349 (2000).
https://doi.org/10.1016/S0034-4257(00)00109-7
https://doi.org/10.1016/S0307-904X(96)00107-2
18. Smirnov A., Holben B. N., Eck T. F., et al. Cloud-screening and Quality Control Algorithms for the AERONET Database. Remote Sens. Environ., 73, 337—349 (2000).
https://doi.org/10.1016/S0034-4257(00)00109-7