Critical Analysis of Satellite Data of NSIDC, NOAA NESDIS in Determining the Spatial Distribution of Ice on Lakes
Author:
Baklagin Nikolaevich Vyacheslav1
Affiliation:
1. Northern Water Problems Institute, Karelian Research Centre, Russian Academy of Sciences , Republic of Karelia , Aleksander Nevsky st., 50, 185030 Petrozavodsk , Russia
Abstract
Abstract
The process of formation and rotting of ice on lakes is an integral part of the hydrological cycle of many lakes. The conditions of the ice regime significantly influence the ecological system of lakes. The article includes calculation and analysis of errors in the determination of the spatial ice distribution (spatial resolution of 4–6 km) on Lake Onego, Lake Ladoga, Lake Segozero and Lake Vigozero within the period of 2006−2017 according to National Snow and Ice Data Center (NSIDC), National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service (NOAA NESDIS) data with regard to reliable Moderate Resolution Imaging Spectroradiometer (MODIS) data (spatial resolution of 500 m). It was established that within the monitoring period, NSIDC data have the minimum mean values of errors in determining the spatial distribution of ice on lakes (3−10%) compared to NOAA NESDIS data (11−19%) and are also of more practical interest in estimating the ice coverage of lakes. The dependence of the mean value of errors that occur in the determination of the spatial distribution of ice (according to NSIDC, NOAA and NESDIS data) on the actual value of ice coverage (according to MODIS) was revealed. The results show that the NSIDC data allow estimating adequately the phases of the ice regime; however, the formation of a daily time series of ice coverage during freeze-up and break-up phases is possible only with a significant error (mean value of absolute deviations according to MODIS data is up to 35%).
Publisher
Walter de Gruyter GmbH
Reference7 articles.
1. Abd Rahman, M.A., Khiruddin, A., Hwee, S.L., Muhd, F.E., Fadhli, A. & Rosnan Y. (2016). Development of Regional TSS Algorithm over Penang using Modis Terra (250 M) Surface Reflectance Product. Ekológia (Bratislava), 35(3), 289−294, DOI: 10.1515/eko-2016-0023.10.1515/eko-2016-0023 2. Abd Rahman, M.A., Fadhli, A. & Khiruddin A. (2017). Discriminating sediment and clear water over coastal water using GD technique. Ekológia (Bratislava), 36(1), 10−24. DOI: 10.1515/eko-2017-0002.10.1515/eko-2017-0002 3. Adrian, R., O’Reilly, C.M., Zagarese, H., Baines, S.B., Hessen, D.O., Keller, W., Livingstone, D.M., Sommaruga, R., Straile, D., Donk, E.V., Weyhenmeyer, G.A. & Winder M. (2009). Lakes as sentinels of climate change. Limnology and Oceanography, 54(6), 2283−2297. DOI: 10.4319/lo.2009.54.6_part_2.2283.10.4319/lo.2009.54.6_part_2.2283 4. Baklagin, V.N. (2017). Selection of parameters and architecture of multilayer perceptrons for predicting ice coverage of lakes. Ekológia (Bratislava), 36(3), 226−234. DOI: 10.1515/eko-2017-0019.10.1515/eko-2017-0019 5. Filatov, N.N., Georgiev, A.P., Efremova, T.V., Nazarova, L.E., Pal’Shin, N.I., Tolstikov, A.V., Sharov, A.N. & Rukhovets L.A. (2012). Response of lakes in Eastern Fennoscandia and Eastern Antarctica to climate changes. Doklady Earth Sciences, 444(2), 752–755. DOI: 10.1134/S1028334X1206013X.10.1134/S1028334X1206013X
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