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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 5, pp. 306-321

Trends in Lake Baikal surface temperature: Long-term analysis based on validated satellite products

E.A. Mamash 1 , I.A. Pestunov 1, 2 , V.V. Blinov 3 , A.N. Mazyar 4 , I.A. Aslamov 3 
1 Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia
2 Matrosov Institute for System Dynamics and Control Theory SB RAS, Irkutsk, Russia
3 Limnological Institute SB RAS, Irkutsk, Russia
4 Novosibirsk State University, Novosibirsk, Russia
Accepted: 11.08.2025
DOI: 10.21046/2070-7401-2025-22-5-306-321
This study analyzes long-term trends in Lake Baikal skin temperature (ST) using validated satellite data. The work addresses two main objectives: (1) validation of Terra/Aqua MODIS and Landsat-8, -9 ST products against in situ ship measurements from LIN SB RAS (Limnological Institute SB RAS) (2021–2024), and (2) identification of spatiotemporal trends in the lake ST. Validation confirmed the applicability of all considered products for ST estimation while revealing their specific characteristics. Terra/Aqua MODIS products exhibit a bias of 0,13–0,8 °C (absolute value) and a root mean square error (RMSE) of 1,47–1,77 °C relative to in situ data. Analyses were conducted separately for daytime and nighttime observations. Landsat data showed the highest accuracy, with a coefficient of determination (R2) of 0.98, RMSE of 0.62 °C, and a mean bias of −0.14 °C, likely attributable to their high spatial resolution. Consequently, Landsat is preferable for detailed analysis, whereas MODIS high temporal resolution maintains its utility for near-real-time monitoring. Long-term trend analysis based on validated data revealed statistically significant warming of Lake Baikal ST. The warming is most pronounced in the central and northern basins during the open-water period (June–November), with trend magnitudes varying by dataset and time period (0,066–0,095 °C/year). These results consistently indicate ongoing surface temperature increase.
Keywords: validation, satellite data, Lake Baikal surface layer temperature, temperature trends, Terra/Aqua MODIS, Landsat
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References:

  1. Aslamov I. A., Gnatovsky R. Yu., Makarov M. M., Tyurnev I. N., Blinov V. V., Climatic changes and thermobaric instability of the upper layer of the hypolimnion of Lake Baikal during summer stratification, Materialy 3-i Mezhdunarodnoi konferentsii “Ozera Evrazii: problemy i puti ikh resheniya” (Proc. 3rd Intern. Conf. “Lakes of Eurasia: problems and ways of their solution”, Kazan: Publishing house of the Academy of Sciences of the Republic of Tatarstan), Kazan: Izd. Akademii nauk RT, 2025, pp. 247–252 (in Russian).
  2. Evdokimov S. I., Shtefuryak A. V., Comparative analysis of water temperature using satellite images (on the example of Lake Pskov), Pskovskii regionologicheskii zhurnal, 2024, V. 20, No. 4, pp. 121–135 (in Russian), DOI: 10.37490/S221979310032412-6.
  3. Rossolimo L. L., Temperature regime of Lake Baikal, Trudy Baikal’skoi limnologicheskoi stantsii VSF AN SSSR, 1957, V. 16, 552 p. (in Russian).
  4. Sutyrina E. N., Izuchenie vnutrennikh vodoemov i vodosborov s primeneniem dannykh distantsionnogo zondirovaniya Zemli (Study of inland water bodies and watersheds using remote sensing data), Irkutsk: Izd. IGU, 2014, 133 p. (in Russian).
  5. Troitskaya E. S., Shimaraev M. N., Tsekhanovsky V. V., Multiyear changes in water surface temperature in Baikal, Geografiya i prirodnye resursy, 2003, No. 2, pp. 47–50 (in Russian).
  6. Ananina T. L., Ananin A. A., Long-term climatic changes in the northeastern Baikal Region (Russia), J. Atmospheric Science Research, 2020, V. 3, No. 4, pp. 10–15, DOI: 10.30564/jasr.v3i4.2255.
  7. Aranda A. C., Rivera-Ruiz D., Rodríguez-López L. et al., Evidence of climate change based on lake surface temperature trends in South Central Chile, Remote Sensing, 2021, V. 13, Article 4535, DOI: 10.3390/rs13224535.
  8. Attiah G., Kheyrollah Pour H., Scott K. A., Lake surface temperature retrieved from Landsat satellite series (1984 to 2021) for the North Slave Region, Earth System Science Data, 2023, V. 15, pp. 1329–1355, DOI: 10.5194/essd-15-1329-2023.
  9. Berk A., Conforti P., Kennett R. et al., MODTRAN6: A major upgrade of the MODTRAN radiative transfer code, 6 th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lausanne, Switzerland, 2014, pp. 1–4, DOI: 10.1109/WHISPERS.2014.8077573.
  10. Bolgrien D. W., Granin N. G., Levin L., Surface temperature dynamics of Lake Baikal observed from AVHRR images, Photogrammetric Engineering and Remote Sensing, 1995, V. 61, No. 2, pp. 111–116.
  11. Carrea L., Crétaux J.-F., Liu X. et al., ESA Lakes Climate Change Initiative (Lakes_cci): Lake Products, Version 2.0.2, NERC EDS Centre for Environmental Data Analysis, 2022, DOI: 10.5285/a07deacaffb8453e93d57ee214676304.
  12. Carrea L., Crétaux J.-F., Liu X. et al., Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies, Scientific Data, 2023, V. 10, Article 30, DOI: 10.1038/s41597-022-01889-z.
  13. Cook M., Schott J. R., Mandel J., Raqueno N., Development of an operational calibration methodology for the Landsat thermal data archive and initial testing of the atmospheric compensation component of a land surface temperature (LST) product from the archive, Remote Sensing, 2014, V. 6, No. 11, pp. 11244–11266, DOI: 10.3390/rs61111244.
  14. Davies P., Gather U., The identification of multiple outliers, J. American Statistical Association, 1993, V. 88, No. 423, pp. 782–792, DOI: 10.2307/2290763.
  15. Dörnhöfer K., Oppelt N., Remote sensing for lake research and monitoring — Recent advances, Ecological Indicators, 2016, V. 64, pp. 105–122, DOI: 10.1016/j.ecolind.2015.12.009.
  16. Du J., Jacinthe P.-A., Zhou H. et al., Monitoring of water surface temperature of Eurasian large lakes using MODIS land surface temperature product, Hydrological Processes, 2020, V. 34, No. 16, pp. 3582–3595, DOI: 10.1002/hyp.13830.
  17. Dyba K., Ermida S., Ptak M. et al., Evaluation of methods for estimating lake surface water temperature using Landsat 8, Remote Sensing, 2022, V. 14, No. 15, Article 3839, DOI: 10.3390/rs14153839.
  18. Fiedler E. K., Martin M. J., Roberts-Jones J., An operational analysis of Lake Surface Water Temperature, Tellus A: Dynamic Meteorology and Oceanography, 2014, V. 66, No. 1, Article 21247, DOI: 10.3402/tellusa.v66.21247.
  19. Guo L., Zheng H., Wu Y. et al., An integrated dataset of daily lake surface water temperature over the Tibetan Plateau, Earth System Science Data, 2022, V. 14, No. 7, pp. 3411–3422, DOI: 10.5194/essd-14-3411-2022.
  20. Hampton S. E., Izmest’eva L. R., Moore M. V. et al., Sixty years of environmental change in the world’s largest freshwater lake — Lake Baikal, Siberia, Global Change Biology, 2008, V. 14, No. 8, pp. 1947–1958, DOI: 10.1111/j.1365-2486.2008.01616.x.
  21. Herrick C., Steele B. G., Brentrup J. A. et al., lakeCoSTR: A tool to facilitate use of Landsat Collection 2 to estimate lake surface water temperatures, Ecosphere, 2023, V. 14, No. 1, Article e4357, 16 p., DOI: 10.1002/ecs2.4357.
  22. Hook S. J., Chander G., Barsi J. A. et al., In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe, IEEE Trans. Geoscience and Remote Sensing, 2004, V. 42, No. 12, pp. 2767–2776, DOI: 10.1109/TGRS.2004.839092.
  23. Hulley G., Veraverbeke S., Hook S., Thermal-based techniques for land cover change detection using a new dynamic MODIS multispectral emissivity product (MOD21), Remote Sensing of Environment, 2014, V. 140, pp. 755–765, DOI: 10.1016/j.rse.2013.10.014.
  24. Hulley G., Hook S., Abbott E. et al., The ASTER Global Emissivity Database (ASTER GED): Mapping Earth’s emissivity at 100 meter spatial resolution, Geophysical Research Letters, 2015, V. 42, pp. 7966–7976, DOI: 10.1002/2015GL065564.
  25. Jia T., Yang K., Peng Z. et al., Review on the change trend, attribution analysis, retrieval, simulation, and prediction of lake surface water temperature, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2022, V. 15, pp. 6324–6355, DOI: 10.1109/JSTARS.2022.3188788.
  26. Korver M. C., Lehner B., Jeffrey A. et al., Surface water temperature observations and ice phenology estimations for 1.4 million lakes globally, Remote Sensing of Environment, 2024, V. 308, Article 114164, DOI: 10.1016/j.rse.2024.114164.
  27. Liu G., Ou W., Zhang Y. et al., Validating and mapping surface water temperatures in Lake Taihu: Results from MODIS land surface temperature products, IEEE J. Selected Topics in Applied Earth Observations and Remote Sensing, 2015, V. 8, No. 3, pp. 1230–1244, DOI: 10.1109/JSTARS.2014.2386333.
  28. Maligaya V. H., Baltodano A., Agramont A. et al., Exploring trends and variability of water quality over Lake Titicaca using global remote sensing products, Remote Sensing, 2024, V. 16, No. 24, Article 4785, DOI: 10.3390/rs16244785.
  29. McCarville D., Buenemann M., Bleiweiss M., Barsi J., Atmospheric correction of Landsat thermal infrared data: A calculator based on North American Regional Reanalysis (NARR) data, American Soc. for Photogrammetry and Remote Sensing Annual Conf., 2011, V. 15, pp. 319–330.
  30. Merchant C., MacCallum S., Lake Surface Water Temperature ARC-Lake v3 (1995–2012), University of Reading, 2018, DOI: 10.17864/1947.186.
  31. Mogilev N. Y., Gnatovskiy R. Y., Satellite imagery in the study of Lake Baykal surface temperatures, Mapping Sciences and Remote Sensing, 2003, V. 40, No. 1, pp. 41–50, DOI: 10.2747/0749-3878.40.1.41.
  32. Moore M. V., Hampton S. E., Izmest’eva L. R. et al., Climate change and the world’s “Sacred Sea” — Lake Baikal, Siberia, BioScience, 2009, V. 59, No. 5, pp. 405–417, DOI: 10.1525/bio.2009.59.5.8.
  33. Moukomla S., Blanken P. D., Remote sensing of the North American Laurentian Great Lakes’ surface temperature, Remote Sensing, 2016, V. 8, No. 4, Article 286, DOI: 10.3390/rs8040286.
  34. O’Reilly C. M., Sharma S., Gray D. K. et al., Rapid and highly variable warming of lake surface waters around the globe, Geophysical Research Letters, 2015, V. 42, No. 24, pp. 10773–10781, DOI: 10.1002/2015GL066235.
  35. Pareeth S., Salmaso N., Adrian R., Neteler M., Homogenised daily lake surface water temperature data generated from multiple satellite sensors: A long-term case study of a large sub-Alpine lake, Scientific Reports, 2016, V. 6, Article 31251, DOI: 10.1038/srep31251.
  36. Phan T. N., Kappas M., Application of MODIS land surface temperature data: a systematic literature review and analysis, J. Applied Remote Sensing, 2018, V. 12, No. 4, Article 41501, DOI: 10.1117/1.JRS.12.041501.
  37. Piccolroaz S., Zhu S., Ladwig R. et al., Lake water temperature modeling in an Era of climate change: Data sources, models, and future prospects, Reviews of Geophysics, 2024, V. 62, No. 1, Article e2023RG000816, DOI: 10.1029/2023RG000816.
  38. Ptak M., Choiński A., Piekarczyk J., Pryłowski T., Applying Landsat satellite thermal images in the analysis of Polish lake temperatures, Polish J. Environmental Studies, 2017, V. 26, No. 5, pp. 2159–2165, DOI: 10.15244/pjoes/69444.
  39. Saunders R., Hocking J., Turner E. et al., An update on the RTTOV fast radiative transfer model (currently at version 12), Geoscientific Model Development, 2018, V. 11, Iss. 7, pp. 2717–2737, DOI: 10.5194/gmd-11-2717-2018.
  40. Sharaf N., Fadel A., Bresciani M. et al., Lake surface temperature retrieval from Landsat-8 and retrospective analysis in Karaoun Reservoir, Lebanon, J. Applied Remote Sensing, 2019, V. 13, No. 4, Article 044505, DOI: 10.1117/1.JRS.13.044505.
  41. Shimaraev M. N., Troitskaya E. S., Current trends in upper water layer temperature in coastal zones of Baikal, Geography and Natural Resources, 2018, V. 39, pp. 349–357, DOI: 10.1134/S187537281804008X.
  42. Shimaraev M. N., Kuimova L. N., Sinyukovich V. N. et al., Manifestation of global climatic changes in Lake Baikal during the 20th century, Doklady Earth Sciences, 2002, V. 383, No. 3, pp. 288–291.
  43. Simis S., Liu X., Calmettes B. et al., ESA CCI Lakes Product Validation and Intercomparison Report Product (PVIR), Report CCI-LAKES-0031-PVIR, European Space Agency, 2021, 175 p., https://climate.esa.int/media/documents/CCI-LAKES-0031-PVIR_v2.1.pdf.
  44. Sobrino J. A., García-Monteiro S., Julien Y., An analysis of the Lake Surface Water Temperature evolution of the world’s largest lakes during the years 2003–2020 using MODIS data, Recent Advances in Remote Sensing, 2024, V. 1, pp. 1–9, DOI: 10.62880/rars240001.
  45. Wan Z., Dozier J., A generalized split-window algorithm for retrieving land-surface temperature from space, IEEE Trans. Geoscience and Remote Sensing, 1996, V. 34, No. 4, pp. 892–905, DOI: 10.1109/36.508406.
  46. Xie C., Zhang X., Zhuang L. et al., Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data, Scientific Reports, 2022, V. 12, Article 2415, DOI: 10.1038/s41598-022-06363-9.