All Russian Research Institute of Hydrometeorological information World Data Center

Digital twins reflect the state of the environment and the activities of enterprises affected by the hydrometeorological conditions. It is proposed to use models to calculate indicators for assessing impacts of natural hazards or of climate change; of forecasts of these impacts; damage estimates; of calculating the cost of actions to protect enterprises; of assessing the feasibility of carrying out preventive actions in order to optimize them. Requirements for impact assessment models working with a digital twin are given. The difficulties in using such models are presented. Proposals for the development of impact models are being considered. A diagram of the use of digital twins in modeling impacts of environmental on enterprises is shown.

Earth's global climate system is vast, complex, and intricately interrelated. Many areas are influenced by global-scale phenomena, including the "triple dip" La Niña conditions that

Regional Climates is one chapter from the State of the Climate in 2021 annual report. Compiled
\nby NOAA’s National Centers for Environmental Information, State of the Climate in 2021 is
\nbased on contributions from scientists from around the world. It provides a detailed update on
\nglobal climate indicators, notable weather events, and other data collected by environmental
\nmonitoring stations and instruments located on land, water, ice, and in space.

Changes in the frequency and intensity of atmospheric severe convective events, including heavy rainfall, thunderstorm, hailstorm, squall, and tornado, in the Russian regions during the warm season are analyzed using different independent sources of information. Based on observations at Russian weather stations in 1966–2020, the frequency of thunderstorm, hailstorm, and strong wind, the contribution of extreme showers to total precipitation, and the cumulonimbus cloud fraction are estimated. Based on satellite data, the frequency and intensity of tornado and squall events that caused windthrows for 1986–2021 and the height of the top of deep convective clouds for 2002–2021 are also evaluated. The ERA5 reanalysis data are used to analyze the frequency of conditions favorable for the development of moderate and intense severe convective events in 1979–2020. The results indicate a general intensification of severe convective events in most Russian regions, except for a number of regions in the south of the European part of Russia. The frequency of moderate hazards has a decreasing trend, and the frequency of the most intense severe hazards has an increasing trend. It is reasonable to take the results into account when developing plans for the adaptation of Russian regions and industries to climate change.

We have described the current hydrological state of the Agrakhan Bay, studied its features and defined trends, factors and parameters of hydrologic-morphological evolution of the Bay, mainly in the XX and early XXI centuries, and proposed measures for its restoration. The study was based on field measurements and long-term networked hydrological observations, comparative analysis of multitemporal cartographic material and satellite images, and laboratory analysis of water samples. Agrakhan Bay is a unique hydrographic and ecologically valuable object in the south-eastern part of the Terek delta, which 100 years ago had the features of a typical sea gulf and an area of 340 km2, was one of the main habitats for sturgeon spawning and fishery. Now it is divided into two different parts. Water areas and watered reed cover only 258 km2. Their area continues to decrease, which generates negative environmental and socio-economic consequences. The fishing value of the bay has been lost.

Remote correlative relationships of temperatures in the near-surface layer are studied. The paper considers the observational data of 1879-2016 on air temperature at the meteorological station 'Moscow' and surface temperature data from different parts of the World ocean according to the array Extended Reconstructed Sea Surface Temperature (ERSSTv3b). The series of three-year running averages from which linear trends are deducted were analyzed. Maps of estimates of the correlation coefficient under optimal shift (i.e., providing maximum correlation) of the sea surface temperature series were constructed. The range 0-36 years for the time lag was explored. Substantial correlation was found between oscillations of the annual mean ocean surface temperature in the current of Westerly Winds and oscillations of the annual mean air temperature in Moscow with a time lag of 30 years.

Abstract Global dynamical reanalyses of the atmosphere and ocean fundamentally rely on observations, not just for the assimilation (i.e., for the definition of the state of the Earth system components) but also in many other steps along the production chain. Observations are used to constrain the model boundary conditions, for the calibration or uncertainty determination of other observations, and for the evaluation of data products. This requires major efforts, including data rescue (for historical observations), data management (including metadatabases), compilation and quality control, and error estimation. The work on observations ideally occurs one cycle ahead of the generation cycle of reanalyses, allowing the reanalyses to make full use of it. In this paper we describe the activities within ERA-CLIM2, which range from surface, upper-air, and Southern Ocean data rescue to satellite data recalibration and from the generation of snow-cover products to the development of a global station data metadatabase. The project has not produced new data collections. Rather, the data generated has fed into global repositories and will serve future reanalysis projects. The continuation of this effort is first contingent upon the organization of data rescue and also upon a series of targeted research activities to address newly identified in situ and satellite records.

Abstract. Snow cover variability has significant effects on local and global climate evolution. By changing surface energy fluxes and hydrological conditions, changes in snow cover can alter atmospheric circulation and lead to remote climate effects. To document such multi-scale climate effects, atmospheric reanalysis and derived products offer the opportunity to analyze snow variability in great detail far back to the early 20th century. So far only little is know about their quality. Comparing snow depth in four long-term reanalysis datasets with Russian in situ snow depth data, we find a moderately high daily correlation (around 0.6–0.7), which is comparable to correlations for the recent era (1981–2010), and a good representation of sub-decadal variability. However, the representation of pre-1950 inter-decadal snow variability is questionable, since reanalysis products divert towards different base states. Limited availability of independent long-term snow data makes it difficult to assess the exact cause for this bifurcation in snow states, but initial investigations point towards representation of the atmosphere rather than differences in assimilated data or snow schemes. This study demonstrates the ability of long-term reanalysis to reproduce snow variability accordingly.

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