VEGA-Agrometeorologist" is the information system for comprehensive analysis of agrometeorological monitoring data.It integrates a wide range of data, primarily obtained by remote sensing methods.Various vegetation indices available in the system are particular valuable, as they make it possible to conduct a detailed study of the development of agricultural vegetation on the entire territory of agricultural lands of Russia, taking into account agro-climatic zoning.The high degree of automation of all processes ensures the continuity and homogeneity of all the data series used.

Технология спутникового мониторинга агрометеорологических условий проведения полевых работ основана на анализе данных об относительной влажности верхнего слоя почвы, получаемых с активного микроволнового зондировщика ASCAT (ИСЗ MetOp-A,B). Оценка состояния верхнего слоя почвы проводится по градациям. Новый информационный продукт может использоваться в области агрометеорологии, агрономии и страхования.

Изучены пространственные корреляции станционных данных измерений запасов продуктивной влаги в пахотном и 10-сантиметровом слоях почвы и спутниковых данных об относительной влажности верхнего слоя почвы (ИСЗ MetOp-А и В, скаттерометр ASCAT) по европейской территории России. Для этого в тестовом режиме использовалась версия компьютерной технологии, при помощи которой осуществлялся контроль станционных данных, а затем выполнялся объективный анализ.

The following data was used: the archives of measurements of available water capacity carried out at Roshydromet network of stations and satellite measurements of relative humidity of the upper soil layer from ASCAT data (from the MetOp satellites). The statistical structure of the field of available water capacity in the upper 10- and 20-cm soil layers is assessed. The correlations between the Earth remote sensing data and data from agrometeorological stations are revealed. The procedure of automatic data checking from ground-based observations is developed. The algorithm is suggested for statistically optimal conversion of the Earth remote sensing data to the estimate of moisture content in the upper soil layer.

Using COSMO-CLM (a nonhydrostatic atmospheric model designed for climate experiments), we simulate the summer anomalies in the meteorological regime of 2010 and 2002 over the central part of the East European Plain. The module of soil moisture treatment is shown to demonstrate reliable results and the radiation module of the model needs to incorporate the optical properties of haze generated by the smoke of forest and peat fires. It is shown that the soil moisture content formed in the spring can (due to its inertial behavior and by changing the heat balance structure) participate in the formation of temperature and humidity anomalies over 3–4 months. The extremeness of the thermal regime in the summer of 2010 in the central part of the East European Plain is due to (all other conditions being equal) the specific values of soil moisture content w 0 = 0.6–0.65. The revealed fine dependence of the phenomenon on the spring state of soil moisture makes it important to improve the monitoring of soil moisture as a key factor in the dynamics of extreme weather anomalies.