Zhurnal Radioelektroniki - Journal of Radio Electronics. eISSN 1684-1719. 2020. No. 11
Contents

Full text in Russian (pdf)

Russian page

 

DOI https://doi.org/10.30898/1684-1719.2020.11.6

UDC 528.8; 517

 

Adaptive algorithm for detection and monitoring of atmospheric rivers

 

E. V. Savchenko, S. M. Maklakov

Fryazino branch of Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences, Vvedenskogo sq., 1, Fryazino 141190, Moscow region, Russia


The paper is received on November 2, 2020, after correction - on November 24, 2020

 

Abstract. A new adaptive method for detecting and monitoring atmospheric rivers (ARs) over the ocean surface is proposed. ARs is the filamentous structures in the field of atmospheric water vapor, which provide a rapid transfer of moisture from the tropics to mid and high latitudes. Currently, certain difficulties remain in their detection and monitoring. The method is based on an adaptive algorithm for calculating the Jeffreys - Matusita distance between areas of the ocean with a high integral water vapor content and the places surrounding these areas with its background low values. The efficiency of the developed method is confirmed by the results of analysis of real data on the integral content of water vapor in the North Pacific Ocean. For the purpose of a qualitative comparative analysis, the authors give a brief overview of the methods used for the detection and monitoring of ARs, summarized the work on the study of the influence of ARs on regional weather conditions, singled out and characterized individual stages of these studies, indicated the most promising hardware for AR remote sensing. The results of the work are proposed to be used to improve the accuracy and reliability of automated AR detection by server means of a geoportal of satellite radio-thermal imaging (https://fireras.su/tpw/). The results of the work are of interest for multidisciplinary research, in particular, for predicting medium-term atmospheric processes.

Key words: atmospheric rivers, atmosphere, atmospheric processes, climate, climate study, remote sensing, satellite sensing, geoportal.

References

1. Lackmann G.M., Gyakum J.R. Heavy Cold-Season Precipitation in the Northwestern United States: Synoptic Climatology and an Analysis of the Flood of 1718 January 1986. Weather and Forecasting. 1999. Vol.14. No.5. P.687-700.

2. Waliser D., Guan B. Extreme winds and precipitation during landfall of atmospheric rivers. Nature Geoscience. 2017. Vol. 10. P.179183.

3. Newell R.E., Newell N.E., Zhu Y., Scott C. Tropospheric rivers? A pilot study. Geophysical Research Letters. 1992. Vol.19. P.2401-2404.

4. Zhu Y, Newell R.E. Atmospheric rivers and bombs. Geophysical Research Letters. 1994. Vol.21.No.18. P.1999-2002.

5. Zhu Y., Newell R.E. A proposed algorithm for moisture fluxes from atmospheric rivers. Monthly Weather Review. 1998. Vol.126 (3). P.725735.

6. Ermakov D.M. Satellite Radiothermovision of Atmospheric Processes: Method and Applications. Springer Praxis Publishing, 2020. Chapter 5. P.121 150.

7. Ermakov D.M., Sharkov E.A., Chernushich A.P. Satellite radiothermovision on synoptic and climatically significant scales. Izvestiya Atmos. Oceanic Phys. 2017. Vol.59. No.9. P.973978.

8. Dirmeyer P, Kinter J.L. The Maya Express: floods in the U.S. Midwest. 2009. https://doi.org/10.1029/2009EO120001.

9. Nayak M.A., Villarini G. Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States. Journal of Hydrology. 2018. Vol.556. P.10381049.

10. Lavers D.A., Allan R.P., Wood E.F., Villarini G., Brayshaw D.J., Wade A.J. Winter floods in Britain are connected to atmospheric rivers. Geophysical Research Letters. 2011. Vol.38., L23803.

11. Komatsu K.K., Alexeev V.A., Repina I.A., Tachibana Y. Poleward upgliding Siberian atmospheric rivers over sea ice heat up Arctic upper air. Scientific reports. 2018. Vol.8. P.2872. https://doi.org/10.1038/s41598-018-21159-6

12. Ralph F.M., Dettinger M.D. Storms, floods, and the science of Atmospheric rivers. EOS, Transactions, American Geophysical Union. 2011. Vol.92. No.32. P.265266.

13. Matrosov S.Y. Characteristics of Landfalling Atmospheric Rivers Inferred from Satellite Observations over the Eastern North Pacific Ocean. Monthly Weather Review. 2013. Vol. 141. P.3757-3768.

14. Wen Y., Behrangi A., Chen H., Lambrigtsen B. How well were the early 2017 California Atmospheric River precipitation events captured by satellite products and ground-based radars? Q J R Meteorol. Soc. 2018. Vol.144 (Suppl. 1), P.344359.

15. Ralph F.M, Neiman P.J., Wick G.A. Satellite and CALJET Aircraft Observations of Atmospheric Rivers over the Eastern North Pacific Ocean during the Winter of 1997/98. Monthly Weather Review. 2004. Vol.132. P.1721-1745.

16. Shields C. A. et al. Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design. Geosci. Model Dev. 2018. Vol.11. P.24552474.

17. Kailath T. The Divergence and Bhattacharyya Distance Measures in Signal Selection. IEEE Transactions on Communication Technology. 1967. Vol.15. P.52-60.

18. Ermakov D.M., Chernushich A.P., Sharkov E.A. Geoportal for satellite radio thermal imaging: data, services, development prospects. Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa - Modern problems of remote sensing of the Earth from space. 2016. Vol.13. No.3. P.46-57. (In Russian)

19. Savchenko E.V., Maklakov S.M., Vasil'yev V.S. Development of technologies for virtual integration of satellite earth monitoring data in the geoportal of satellite radio thermal imaging. Proceeings of XV Conference of young scientists Fundamental'nyye i prikladnyye kosmicheskiye issledovaniya [Fundamental and applied space research]. April 11-13, 2018. Moscow, Inst. of Space Research of the Russian Academy of Sciences. P.93. (In Russian)

 

For citation:

Savchenko E.V., Maklakov S.M. Adaptive algorithm for detection and monitoring of atmospheric rivers. Zhurnal Radioelektroniki - Journal of Radio Electronics. 2020. No.11. https://doi.org/10.30898/1684-1719.2020.11.6 (In Russian)