Calculating of snow cover characteristics on a plain territory using the model SPONSOR and data of reanalyses (by the example of Moscow region)

The technique for calculating the snow cover characteristics (a water equivalent and a snow cover thickness) with high spatial and time resolution on spacious plains is proposed. The model SPONSOR of local heat- and moisture exchange (Land-Surface Model, LSM) and data of reanalyses NCEP/DOE and ECMWF ERA-Interim were used for calculations. The above characteristics of the snow cover on the test area of the Moscow region were calculated using this method over the period 1979–1996. The results were compared with actual data of the snow gauge stations and with data on snow cover, derived directly from reanalysis. The data from the NCEP/DOE reanalysis did not show satisfactory agreement with data of the observations for both the water equivalent and the thickness (Fig.  1,  б and Fig. 2, б): deviations reached 60–70%. Monthly mean values of snow water equivalent from the ERA-Interim reanalysis were in a good agreement with the observations, but the snow thicknesses were reproduced much worse. At the same time, using the LSM SPONSOR with input meteorological data from the reanalyses allowed obtaining the snow cover characteristics which were in a good agreement with data of the observations for both the monthly means and individual daily values. The correlation coefficients with the data of snow gauge surveys increased, on the average, up to 0.83–0.89 for the water equivalent, and up to 0.85–0.91 for the snow depth (see the Тable in the text). Especially good results were obtained when meteorological data from the ERA-Interim reanalysis were used together with the LSM SPONSOR (Fig. 1, д and Fig. 2, д). It allows us to conclude that meteorological data from the ERA-Interim reanalysis together with data of regular observational network can be used as an additional source of information for calculations of the snow characteristics. This conclusion is especially important for areas with sparse network of regular observations

Расчёт характеристик снежного покрова равнинных территорий с использованием модели локального тепловлагообмена SPONSOR и данных реанализа на примере Московской области

The technique for calculating the snow cover characteristics (a water equivalent and a snow cover thickness) with high spatial and time resolution on spacious plains is proposed. The model SPONSOR of local heat- and moisture exchange (Land-Surface Model, LSM) and data of reanalyses NCEP/DOE and ECMWF ERA-Interim were used for calculations. The above characteristics of the snow cover on the test area of the Moscow region were calculated using this method over the period 1979–1996. The results were compared with actual data of the snow gauge stations and with data on snow cover, derived directly from reanalysis. The data from the NCEP/DOE reanalysis did not show satisfactory agreement with data of the observations for both the water equivalent and the thickness (Fig.  1,  б and Fig. 2, б): deviations reached 60–70%. Monthly mean values of snow water equivalent from the ERA-Interim reanalysis were in a good agreement with the observations, but the snow thicknesses were reproduced much worse. At the same time, using the LSM SPONSOR with input meteorological data from the reanalyses allowed obtaining the snow cover characteristics which were in a good agreement with data of the observations for both the monthly means and individual daily values. The correlation coefficients with the data of snow gauge surveys increased, on the average, up to 0.83–0.89 for the water equivalent, and up to 0.85–0.91 for the snow depth (see the Тable in the text). Especially good results were obtained when meteorological data from the ERA-Interim reanalysis were used together with the LSM SPONSOR (Fig. 1, д and Fig. 2, д). It allows us to conclude that meteorological data from the ERA-Interim reanalysis together with data of regular observational network can be used as an additional source of information for calculations of the snow characteristics. This conclusion is especially important for areas with sparse network of regular observations.Предложена методика расчёта характеристик снежного покрова с высоким пространственным и временным разрешением с использованием модели локального тепловлагообмена (Land-Surface Model, LSM) SPONSOR и метеоданных реанализов NCEP/DOE и ECMWF ERA-Interim. Выполнены расчёты для тестового региона Московской области за период 1979–1996 гг. и проведено сравнение с данными наблюдений и реанализа. Данные о снежном покрове из реанализа существенно отличаются от данных наблюдений. Использование модели SPONSOR с входными метеоданными, взятыми из реанализа ECMWF ERA-Interim, позволяет получить характеристики снежного покрова с высоким пространственным и временным разрешением, которые хорошо согласуются с данными наблюдений

Level Anticrossing of Impurity States in Semiconductor Nanocrystals

The size dependence of the quantized energies of elementary excitations is an essential feature of quantum nanostructures, underlying most of their applications in science and technology. Here we report on a fundamental property of impurity states in semiconductor nanocrystals that appears to have been overlooked—the anticrossing of energy levels exhibiting different size dependencies. We show that this property is inherent to the energy spectra of charge carriers whose spatial motion is simultaneously affected by the Coulomb potential of the impurity ion and the confining potential of the nanocrystal. The coupling of impurity states, which leads to the anticrossing, can be induced by interactions with elementary excitations residing inside the nanocrystal or an external electromagnetic field. We formulate physical conditions that allow a straightforward interpretation of level anticrossings in the nanocrystal energy spectrum and an accurate estimation of the states\u27 coupling strength

Оценки современных изменений снегозапасов в бассейне Северной Двины по данным наблюдений и моделирования

The variability of snow accumulation in the Northern Dvina River basin at the end of March 1980-2016 was studied using data on the snow water equivalent of (SWE) obtained from archives of the Russian Institute of HydroMeteorological Information-World Data Center (RIHMI-WCD) as well as calculated by models of the local heat and moisture exchange SWAP and SPONSOR using the WATCH reanalysis (WFDEI) as input data. A possibility to use the SWE data from these sources to describe long-term variability of the SWE values, including trend, high-frequency component, quasi-decadal fluctuations, and spatial distribution, is evaluated. When describing the structure of the SWE variability, in particular, the contribution of trend and quasi-decadal fluctuations, as well as spatial characteristics, uncertainty remains associated with both the capabilities of the models under consideration and the imperfection of the observation network (insufficient density, measurement errors, etc.). Taking into account these uncertainties, the following conclusions can be made: the SWE variability in the Northern Dvina basin at the end of March has a low-frequency component (trend), as well as high-frequency, two- and five-year quasi-periodicities and quasi-decadal fluctuations. Long-lasting SWE anomalies in 1989–1995 and 1999–2005 and the absolute minimum in 1996 associated with quasi-decadal fluctuations are almost synchronously reflected in spring runoff anomalies. The informativeness of the considered data was also investigated from the point of view of the influence of SWE on the anomalies of the spring runoff of the Northern Dvina. The results of regression estimates and calculations of predictive values point to the advantage of the model SWE data for describing anomalies of spring river discharge compared to observations, which is primarily due to the high resolution of the model data. All the considered data sources indicate a long period of SWE deficits, starting from 2005 – 15-20%. Estimates of trend parameters are in a wide range. Depending on the data source, the rate of the SWE decrease over the basin, can vary from 4 mm per 10 years according to observations and up to 10 mm per 10 years according to calculations using the SPONSOR model.Изменчивость снегозапасов в бассейне р. Северная Двина (1980–2016 гг.) исследуется на основе данных о водном эквиваленте снега (ВЭС), полученных из станционных наблюдений и в результате расчётов на моделях тепло- и влагообмена. Обсуждаются оценки параметров тренда и вклада высокочастотных и квазидесятилетних колебаний, а также особенности пространственного распределения изменчивости ВЭС, полученные по сведениям из разных источников. В качестве критерия информативности наблюдений и модельных расчётов рассматриваются оценки вклада изменчивости ВЭС в конце марта в аномалии весеннего стока

Определение снегозапасов Западной Сибири по расчётам на модели локального тепловлагообмена SPONSOR с использованием данных реанализа

Obtaining of reliable information about the characteristics of snow cover with high spatial and temporal resolution for large areas of Northern Eurasia, with rare or absent network of ground-based observations stations is an important and urgent task. Currently estimation of the value of the snow water equivalent (SWE) and the snow depth have a large degree of uncertainty, especially if we are moving from data at the point of observation stations to distributed space values. In this article, the simulations of SWE and the snow depth using Land-Surface Model (LSM) SPONSOR with input meteorological data taken from the ECMWF ERAInterim reanalysis was performed for Western Siberia for the period from 1979 to 2013. Fields of SWE and of the snow depth with high spatial and temporal resolution corresponding to the resolution of meteorological data of the ECMWF ERA-Interim reanalysis (time step of 6 hours, the grid resolution of 0.75° × 0.75° in latitude and longitude) were obtained. For the entire period SWE data were compared with observations, as simulated using the model and taken directly from the reanalysis ERA-Interim at points corresponding of observation stations. Also comparison of observations and satellite data of SWE for points of observation stations was performed. Correlation coefficients between observations and model and satellite data for SWE and the snow depth were calculated for the period from 1979 to 2013. These correlation coefficients between observations and results of simulations using LSM SPONSOR for SWE, and especially for the snow depth are the best of all methods. Maps with high spatial resolution for SWE, obtained by different methods, were constructed for February averaged. Comparing of constructed maps shows significant uncertainty of the SWE fields, besides field’s distortions are not evenly distributed across the region. It appears that no one of these methods currently can be used as a reference (unique) to determine SWE in the absence of data of ground-based observations. Overall, model simulations using LSM SPONSOR somewhat overstate SWE, however, this overestimation is not more than 10–20% for most part of the territory, except in the South. Model data are reasonably well reproduce SWE for Central, Eastern and, most probably, for Northern parts of the region, differing from a real at 10–15%. Data from used satellite archive a few underestimate of SWE. SWE data taken directly from the reanalysis ERA-Interim, give large distortions of the SWE field: these values for Northern parts of the region, are likely greatly underestimated, and for Western and Eastern parts of the region – inflated. It is shown that in general, the method of simulation of snow cover characteristics using LSM SPONSOR with input data taken from the ECMWF ERA-Interim reanalysis gives good results for the region of Western Siberia.Для территории Западной Сибири за период с 1979 по 2013 г. проведены расчёты снегозапасов и толщины снежного покрова с помощью модели локального тепловлагообмена SPONSOR с входными метеоданными, взятыми из реанализа ECMWF ERA-Interim. Показано, что коэффициенты корреляции между данными наблюдений и результатами численных расчётов на модели SPONSOR – наилучшие из всех методов. С помощью модели SPONSOR достаточно хорошо воспроизводятся данные снегозапасов по центральной, восточной и, наиболее вероятно, северной частям Западной Сибири

The main directions in the organizational and financial optimization of preventive and therapeutic measures for HIV infection (based on the Sverdlovsk region experience)

Russia is among the countries where the problem of HIV I AIDS poses a serious threat to national, demographic and socio­economic development, affecting all sectors of society. To achieve results in combating the HIV I AIDS epidemic, the problem requires an expansion of scale of action, mobilization of various resources, and intersectional collaboration. Analysis of trends in the epidemiological situation of HIV infection, as well as trends in organizational development, in interagency system to counter the spread of HIV / AIDS at the regional and municipal levels, including the impact of a set of measures implemented in the -Sverdlovsk region, allowed to develop the main recommendations for improvement of organizational and financial support of therapeutic and preventive measures on HIV-infections taking into account the need of changing the existing legal framework on HIV.Россия относится к числу стран, где проблема распространения ВИЧ/СПИДа представляет серьезную угрозу национальному, демографическому и социально-экономическому развитию, затрагивая все слои общества, и требует расширения масштаба принимаемых мер, мобилизации различных ресурсов и межсекторального сотрудничества для достижения результатов в противодействии эпидемии. Анализ тенденций изменения эпидемической ситуации по ВИЧ-инфекции, организационного развития межведомственной системы противодействия распространению ВИЧ/СПИДа на региональном и муниципальном уровнях, а также результативности комплекса мероприятий, реализованных в Свердловской области позволили разработать основные направления совершенствования организационного и финансового обеспечения лечебных и профилактических мероприятий по ВИЧ-инфекции с учетом необходимости изменения действующей нормативно-правовой базы

ESM-SnowMIP: Assessing snow models and quantifying snow-related climate feedbacks

This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP)

Evaluation of snow storage in Western Siberia based on the land-surface model SPONSOR simulation using reanalysis data

Obtaining of reliable information about the characteristics of snow cover with high spatial and temporal resolution for large areas of Northern Eurasia, with rare or absent network of ground-based observations stations is an important and urgent task. Currently estimation of the value of the snow water equivalent (SWE) and the snow depth have a large degree of uncertainty, especially if we are moving from data at the point of observation stations to distributed space values. In this article, the simulations of SWE and the snow depth using Land-Surface Model (LSM) SPONSOR with input meteorological data taken from the ECMWF ERAInterim reanalysis was performed for Western Siberia for the period from 1979 to 2013. Fields of SWE and of the snow depth with high spatial and temporal resolution corresponding to the resolution of meteorological data of the ECMWF ERA-Interim reanalysis (time step of 6 hours, the grid resolution of 0.75° × 0.75° in latitude and longitude) were obtained. For the entire period SWE data were compared with observations, as simulated using the model and taken directly from the reanalysis ERA-Interim at points corresponding of observation stations. Also comparison of observations and satellite data of SWE for points of observation stations was performed. Correlation coefficients between observations and model and satellite data for SWE and the snow depth were calculated for the period from 1979 to 2013. These correlation coefficients between observations and results of simulations using LSM SPONSOR for SWE, and especially for the snow depth are the best of all methods. Maps with high spatial resolution for SWE, obtained by different methods, were constructed for February averaged. Comparing of constructed maps shows significant uncertainty of the SWE fields, besides field’s distortions are not evenly distributed across the region. It appears that no one of these methods currently can be used as a reference (unique) to determine SWE in the absence of data of ground-based observations. Overall, model simulations using LSM SPONSOR somewhat overstate SWE, however, this overestimation is not more than 10–20% for most part of the territory, except in the South. Model data are reasonably well reproduce SWE for Central, Eastern and, most probably, for Northern parts of the region, differing from a real at 10–15%. Data from used satellite archive a few underestimate of SWE. SWE data taken directly from the reanalysis ERA-Interim, give large distortions of the SWE field: these values for Northern parts of the region, are likely greatly underestimated, and for Western and Eastern parts of the region – inflated. It is shown that in general, the method of simulation of snow cover characteristics using LSM SPONSOR with input data taken from the ECMWF ERA-Interim reanalysis gives good results for the region of Western Siberia