Simulating Atmospheric Characteristics and Daytime Astronomical Seeing Using Weather Research and Forecasting Model
Source abstract
Abstract
The present study is aimed at the development of a novel empirical base for application to ground-based astronomical telescopes. A Weather Research and Forecasting (WRF) model is used for description of atmospheric flow structure with a high spatial resolution within the Baikal Astrophysical Observatory (BAO) region. Mesoscale vortex structures are found within the atmospheric boundary layer, which affect the quality of astronomical images. The results of simulations show that upward air motions in the lower atmosphere are suppressed both above the cold surface of Lake Baikal and inside mesoscale eddy structures. A model of the outer scale of turbulence for BAO is developed. In this work, we consider the seeing parameter that represents the full width at half-maximum of the point spread function. Optical turbulence profiles are obtained and daytime variations of seeing are estimated. Vertical profiles of optical turbulence are optimized taking into account data from direct optical observations of solar images.
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Research context
OpenAlex topics: Adaptive optics and wavefront sensing · Meteorological Phenomena and Simulations · Atmospheric aerosols and clouds
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Solar-Terrestrial Physics, The Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia
Institute of Computational Mathematics and Mathematical Geophysics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia
Departament of Mechanics and Mathematics, Novosibrsk State University, Novosibirsk 630090, Russia
Institute of Nature Management, National Academy of Sciences of Belarus, 220076 Minsk, Belarus
Limnological Institute, The Siberian Branch of the Russian Academy of Sciences, Irkutsk 664033, Russia
Funding
RSF
References (37)
Show source-provided references
1. Precipitable Water Vapor, Temperature and Wind Statistics At Sites Suitable for mm and Submm Wavelength Astronomy in Northern Chile10.1088/1538-3873/aafb78 ↗
2. Site-testing at Muztag-Ata site. IV. Precipitable Water Vapor10.1088/1538-3873/ac427b ↗
3. Atmospheric research for adaptive optics10.1134/S1024856022030022 ↗
4. Astroclimatic statistics at the Sayan Solar Observatory
5. Astroclimate Studies in the Special Astrophysical Observatory of the Russian Academy of Sciences10.1134/S1024856019010111 ↗
6. Tillayev, Y., Azimov, A., Ehgamberdiev, S., and Ilyasov, S. (2023). Astronomical Seeing and Meteorological Parameters at Maidanak Observatory. Atmosphere, 14.10.3390/atmos14020199 ↗
7. Eurasian Submillimeter Telescopes (ESMT) project. Possibility of submm image quality improvement using adaptive optics
8. Khaikin, V., Lebedev, M., Shmagin, V., Zinchenko, I., Vdovin, V., Bubnov, G., Edelman, V., Yakopov, G., Shikhovtsev, A., and Marchiori, G. (2020, January 25–27). On the Eurasian SubMillimeter Telescopes Project (ESMT). Proceedings of the 7th All-Russian Microwave Conference (RMC), Moscow, Russia.10.1109/RMC50626.2020.9312233 ↗
9. Searching for New Sites for THz Observations in Eurasia10.1109/TTHZ.2014.2380473 ↗
10. Bubnov, G., Vdovin, V., Khaikin, V., Tremblin, P., and Baron, P. (2020, January 25–27). Analysis of variations in factors of specific absorption of sub-terahertz waves in the Earth’s atmosphere. Proceedings of the 7th All-Russian Microwave Conference (RMC), Moscow, Russia.
11. Direct Measurements of Atmospheric Absorption of Subterahertz Waves in the Northern Caucasus10.1134/S1028335822010013 ↗
12. Sensitive analysis of mesoscale simulations to physics parametrizations over the Belgian North Sea using Weather Research and Forecasting-Advanced Research WRF (WRF-ARW)10.5194/wes-7-1869-2022 ↗
13. Performance evaluation of the WRF model in a tropic region: Wind speed analysis at different sites
14. Estimates of the Earth surface influence on the accuracy of numerical prediction of air temperature in Belarus using the WRF model
15. Interaction of the Sea Breeze with the Urban Area of Rome: WRF Meso-scale and WRF Large-Eddy Simulations Compared to Ground-Based Observations10.1007/s10546-022-00734-5 ↗
16. Zhang, Z., Yang, W., Zhang, S., and Chen, S. (2023). Impacts of Pollutant Emissions from Typical Petrochemical Enterprises on Air Quality in the North China Plain. Atmosphere, 14.10.3390/atmos14030545 ↗
17. De Bode, M., Hedde, T., Roubin, P., and Durand, P. (2021). Fine-Resolution WRF Simulation of Stably Stratified Flows in Shallow Pre-Alpine Valleys: A Case Study of the KASCADE-2017 Campaign. Atmosphere, 12.10.3390/atmos12081063 ↗
18. Optical Turbulence Characterization by WRF model above Ali, Tibet10.1088/1742-6596/595/1/012037 ↗
19. Optical turbulence simulations at Mt Graham using the Meso-NH model10.1111/j.1365-2966.2010.18097.x ↗
20. Estimating the astronomical seeing above Dome A using Polar WRF based on the Tatarskii equation10.1364/OE.439819 ↗
21. Weather Research and Forecasting prevision model as a tool to search for the best sites for astronomy: Application to La Palma, Canary Islands10.1093/mnras/stu356 ↗
22. Forecasting surface-layer optical turbulence above the Tibetan Plateau using the WRF model10.1016/j.optlastec.2022.108217 ↗
23. Modelling of atmospheric optical turbulence with the Weather Research and Forecasting model at the Ali observatory, Tibet10.1093/mnras/stab1316 ↗
24. The History of the Development and Genesis of Works on Adaptive Optics in the Institute of Atmospheric Optics10.1134/S1024856020010078 ↗
25. Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D., Duda, M.G., Huang, X.-Y., Wang, W., and Powers, J.G. (2008). A Description of the Advanced Research WRF Version 3, University Corporation for Atmospheric Research. Ncar Technical Note.
26. Turbulence velocity profiling for high sensitivity and vertical-resolution atmospheric characterization with Stereo-SCIDAR10.1093/mnras/stw2685 ↗
27. Adaptive Imaging and Stabilization System for a Large-Aperture Solar Telescope10.1134/S1024856022030101 ↗
28. Optical turbulence in the atmospheric surface layer at the Ali Observatory, Tibet10.1093/mnras/stab3811 ↗
29. Propagation of an infinite Plane Wave in a Randomly Inhomogeneous Medium10.1364/JOSA.56.001667 ↗
30. Dewan, M.E., Good, R., Beland, R., and Brown, J. (1993). Model for Cn(2) (Optical Turbulence) Profiles Using Radiosonde Data, Phillips Laboratory, Directorate of Geophysics, Air Force Materiel Command.
31. Xu, M., Shao, S., Weng, N., and Liu, Q. (2022). Analysis of the Optical Turbulence Model Using Meteorological Data. Remote Sens., 14.10.3390/rs14133085 ↗
32. Estimation of the astronomical seeing at the Large Solar Vacuum Telescope site from optical and meteorological measurements10.1134/S102485601402002X ↗
33. Turbulence energetics in stably stratified geophysical flows: Strong and weak mixing regimes10.1002/qj.264 ↗
34. Dynamics of the kinetic energy in the atmospheric boundary layer from the results of minisodar measurements10.1007/s11182-019-01668-1 ↗
35. Nosov, V., Lukin, V., Nosov, E., Torgaev, A., and Bogushevich, A. (2019). Measurement of Atmospheric Turbulence Characteristics by the Ultrasonic Anemometers and the Calibration Processes. Atmosphere, 10.10.3390/atmos10080460 ↗
36. Mao, J., Zhang, Y., Li, J., Gong, X., Zhao, H., and Rao, Z. (2023). Novel Detection of Atmospheric Turbulence Profile Using Mie-Scattering Lidar Based on Non-Kolmogorov Turbulence Theory. Entropy, 25.10.3390/e25030477 ↗
37. Modulation Transfer Function Associated with Image Transmission through Turbulent Media10.1364/JOSA.54.000052 ↗