Юшков Владислав Пролетарьевич

Юшков Владислав Пролетарьевич

Должность: старший научный сотрудник

Степень: кандидат физико-математических наук

Контакты:

Подразделение: Отдел динамики водной среды

Лаборатория: Лаборатория глобальной гидрологии

Руководитель подразделения: Добровольский Сергей Гавриилович

Образование / работа

В 1987 г. окончил Физический факультет МГУ им. М.В. Ломоносова.

С 1987 г. по 1993 г. работал в ИРЭ АН СССР.

1988-1992 гг. – заочная аспирантура, ИРЭ АН СССР.

В 1993 г. защитил диссертацию по теме «Имитационная система для вычислительного эксперимента в области изучения глобального влагооборота» на соискание степени кандидата физико-математических наук.

С 1993 г. работает на Физическом факультете МГУ.

В настоящее время сотрудник МГУ им. М.В. Ломоносова (Физический факультет) и ИВП РАН (с 2015 г.).

Область научных интересов

Геофизическая гидродинамика (динамика пограничных слоёв атмосферы и океана, общая циркуляция атмосферы, математическое моделирование климата), теория турбулентности, гидрология суши.

Специалист по динамике и турбулентности атмосферы, теории климата и глобальному гидрологическому циклу.

В течение ряда лет являлся руководителем работ, выполняемых в рамках научных проектов РФФИ (гранты №№ 02-05-64916, 05-05-64786, 08-05-00984 и др.)

Основные научные результаты

Оригинальные результаты получены в области изучения флуктуаций энтропии в турбулентной среде. Является автором теории неопределенности вероятности.

Профили автора

http://elibrary.ru/author_profile.asp?id=58922

Общее количество публикаций

Автор и соавтор более 40 публикаций.

Основные научные публикации

1. Yushkov V. The Hamiltonian Formalism and Quantum Mechanical Analogy in the Probabilistic Description of Turbulence // Theoretical and Mathematical Physics. Moscow University Physics Bulletin. 2015, Volume 70, Issue 4, pp. 217-225 DOI: 10.3103/S0027134915040153

Abstract. It is shown here that (i) the interaction of adiabatic waves with incompressible turbulence makes it possible to statistically describe the transfer of the energy of turbulent pulsations over the spectrum, (ii) the fundamental parameter that allows the effect of adiabatic motions on incompressible turbulence to be parameterized is the entropy dissipation coefficient in the equation that is called the Obukhov equation in this paper, and (iii) the generalized coordinates or canonical variables of the Zakharov equation should be interpreted as wave functions.

2. Privalsky V., Yushkov V. Validation of CMIP5 models for the contiguous United States // Atmosph. Sci. Lett. 2015, Volume 16, Issue 4, pp. 461–464. DOI: 10.1002/asl.582

Abstract. Major statistical characteristics – trend rates, mean values, standard deviations, probability densities, autoregressive model orders, persistence criteria, and spectra – of annual surface temperature over the contiguous United States from 1889 through 2005 are compared with respective characteristics of 47 time series generated within the CMIP5 historical experiment. The observed and most simulated time series are Gaussian. Most autoregressive orders, persistence criteria, and spectra of simulated time series are close to what is found in nature. Although the multi-model mean value is not biased, individual models can err by almost 3.5° C. In addition, the models exaggerate linear trend rates and temperature variance is overestimated.

3. Privalsky V., Yushkov V. ENSO influence upon global temperature in nature and in CMIP5 simulations // Atmosph. Sci. Lett. 2014, Volume 16, Issue 3, pp. 240–245. DOI: 10.1002/asl2.548

Abstract. Statistical properties of observed and CMIP5-simulated bivariate time series ‘annual global surface temperature (AGST) – sea surface temperature in the Niño area 3.4 (SST3.4)’ are analyzed in the time and frequency domains. Both observed and most simulated data show that AGST is explicitly affected by SST3.4 but not vice versa. Though the AGST spectral density is low at intermediate frequencies, most CMIP5 models reproduce its behavior and show the high coherence observed in nature inside that frequency band. However, CMIP5 models show a dependence between AGST and SST3.4 at frequencies below 0.1 year −1 , which is not found in nature.

4. Privalsky V., Yushkov V.P. Validation of Numerical Climate Models for the El Niño-Southern Oscillation System // The International Journal of Ocean and Climate Systems. 2014, Volume 5, № 1, pp. 1-12. DOI: 10.1260/1759-3131.5.1.1

Abstract. Statistical properties of the observed bi-variate ENSO time series (sea surface temperature within the Niño area 3.4 and the Southern Oscillation Index) from 1876 through 2005 are compared with respective properties of 46 CMIP5 models used in the historical experiment, one run per model. The models were found to exaggerate linear trend rates of SST; mean value and variance estimates have a large scatter, most probability densities are Gaussian, the shape of spectra is reproduced correctly in most cases though the spectra of simulated Southern Oscillation have a negative bias. Most estimates of coherence correctly reproduce the behavior of coherence between the observed SST and SOI that exceeds 0.9 at moderate frequencies. The average coherent spectrum of simulated SST is close to the "observed" coherent spectrum and has a negative bias in the SOI case. The results for the time domain require improvement; the frequency domain results are satisfactory.

5. Yushkov V.P. A Probabilistic Description of Atmospheric Turbulence // Moscow University Physics Bulletin. 2013, Volume 68, Issue 4, pp. 330-337 DOI: 10.3103/S0027134913040103

Abstract. A way from the statistical description of homogeneous and isotropic turbulence to the anisotropic probability distribution is proposed. The role of adiabatic motions in the transfer of energy of turbulent fluctuations by spectrum is discussed. We justify the proposition that for large Reynolds numbers the distribution of the energy of adiabatic fluctuations at scales of homogeneous and isotropic turbulence has the form of a Planck curve.

Публикации