Long-Term Forecasting Techniques for the Terms of the Complete Disappearance of Ice on Reservoirs of the Angara-Yenisei Cascade

Abstract

МЕТОДИКИ ДОЛГОСРОЧНОГО ПРОГНОЗИРОВАНИЯ СРОКОВ ПОЛНОГО ОЧИЩЕНИЯ ОТО ЛЬДА ВОДОХРАНИЛИЩ АНГАРО-ЕНИСЕЙСКОГО КАСКАДА Иркутский государственный университет, г. ИркутскОсновная цель настоящего исследования -разработка методик долгосрочного прогнозирования сроков полного очищения ото льда Красноярского, Иркутского, Братского и Усть-Илимского водохранилищ с использованием значений телеконнекционного индекса AO (Arctic Oscillation). Установленные в ходе исследования прогнозные зависимости позволяют предвидеть характер развития данного ледового явления со средней заблаговременностью от 29 до 46 сут., максимальной заблаговременностью -от 38 до 58 сут. Величина обеспеченности допустимой погрешности полученных прогностических зависимостей составляет от 89,5 до 94,7%, индекс корреляции имеет значения от 0,89 до 0,91, что определяет категорию качества предложенных методик прогнозирования сроков полного очищения ото льда Красноярского, Иркутского, Братского и Усть-Илимского водохранилищ как хорошую. Значения коэффициента прогностической информативности выше 0,82 демонстрируют временную устойчивость и возможность практического использования полученных методик прогнозирования.К л ю ч е в ы е с л о в а : индекс AO, ледовые прогнозы, полное очищение ото льда, Ангаро-Енисейский каскад. E.N. Sutyrina LONG-TERM FORECASTING TECHNIQUES FOR THE TERMS OF THE COMPLETE DISAPPEARANCE OF ICE ON RESERVOIRS OF THE ANGARA-YENISEI CASCADE Irkutsk State University, IrkutskThe main purpose of the research is to develop techniques for long-term forecasting of when there comes complete disappearance of ice on Krasnoyarsk, Irkutsk, Bratsk and Ust'-Ilimsk reservoirs using teleconnection AO (Arctic Oscillation) index values. The predictive dependencies obtained in the course of the study permit to anticipate forecasted ice phenomena with an average lead time from 29 to 46 days and maximum lead time from 38 to 58 days. The probability values for the margin of error of the received predictive dependencies are from 89.5 to 94.7%, their correlation index ranges from 0.89 to 0.91. Thus, the qualtity class for the proposed forecasting techniques for the terms of the complete disappearance of ice on Krasnoyarsk, Irkutsk, Bratsk and Ust'-Ilimsk reservoirs is identified as a good one. The values of prognostic information coefficient above 0.82 reveal the temporal stability and possibility of practical use of the predictive techniques obtained.K e y w o r d s : AO index, ice forecasts, complete disappearance of ice, Angara-Yenisei cascade

Long-term forecasting of appearance dates of ice phenomena and freeze-up at the Dnipro Cascade reservoirs by teleconnection indicators

“…So, the basis of the forecasting concept by the teleconnection indicators is the idea of the influence of remote atmospheric circulation fluctuations on the formation of ice phenomena. At the same time, the state of atmospheric circulation is characterized by the various quantitative indices and patterns both in space and time (Sutyrina, 2017). At the Dnipro Cascade reservoirs, the methods of long-term forecasting of the appearance timing of ice phenomena and freeze-up are developed by searching for the best correlation or regression relationship between their dates and teleconnection indicators of the NOAA USA.…”

“…Along with this, there are no methods for the long-term forecasting of the appearance dates of ice phenomena and freeze-up at the reservoirs of the Dnipro Cascade, therefore, such methods need to be developed. The development problem of the reliable long-term forecasts of the water bodies ice regime is one of the most difficult in hydrometeorology and has not yet received a fully satisfactory solution (WMO, 1975;1979;2009;Sutyrina, 2017). The widespread approaches in the longterm forecasting of the ice regime of water bodies are statistical, discriminant, correlation, regression analyses, orthogonal functions for determining optimal predictors of atmospheric processes (WMO, 1979;GOH, 2012;Das et al, 2022).…”

“…The second approach is based on physical and statistical methods that use multiple linear regression equations with the representation of hydrometeorological fields when decomposing them by natural orthogonal components or Chebyshev polynomials (WMO, 1979). In recent decades, methods of satellite sensing, teleconnection indices and patterns, and methods of machine learning are intensively developed and used (Massie et al, 2002;Lindenschmidt et al, 2010;Sutyrina, 2017;Vyshnevskyi and Shevchuk, 2020;Graf et al, 2022). In papers (Shimaraev, 2007;Sizova et al, 2013;Sutyrina, 2017;Khrystiuk and Gorbachova, 2022) the teleconnection indices were used for the long-term forecasting of the water bodies ice regime and acceptable results were obtained.…”

“…In recent decades, methods of satellite sensing, teleconnection indices and patterns, and methods of machine learning are intensively developed and used (Massie et al, 2002;Lindenschmidt et al, 2010;Sutyrina, 2017;Vyshnevskyi and Shevchuk, 2020;Graf et al, 2022). In papers (Shimaraev, 2007;Sizova et al, 2013;Sutyrina, 2017;Khrystiuk and Gorbachova, 2022) the teleconnection indices were used for the long-term forecasting of the water bodies ice regime and acceptable results were obtained. In the world, the use of the teleconnection indices and patterns is a well-known methodological approach in the hydroclimatic forecasting, which allows forecasting weeks to months in advance (van den Dool, 2007;Chen and Georgakakos, 2014;Chen and Lee, 2017).…”

“…Teleconnection indices and patterns are becoming increasingly popular in the hydrological research. So, the teleconnection indicators are used to forecast and analyze the flow of rivers (Peters et al, 2013;Wang et al, 2020), precipitation (He and Guan, 2013;Mekanik et al, 2015), water equivalent of snow cover on the river catchments (Sobolowski and Frei, 2007), droughts (Chiew et al, 1998;Chen and Lee, 2017), ice phenomena (Shimaraev, 2007;Sizova et al, 2013;Sutyrina, 2017;Khrystiuk and Gorbachova, 2022). The main objective of this research is to develop the longterm forecasting methods of the appearance dates of ice phenomena and freeze-up at the Dnipro Cascade reservoirs using the teleconnection indicators.…”