The climate is always changing, however, such an unprecedented increase in the rate of changes in climatic characteristics over the past 50 - 60 years has not been observed in the entire history of observations. Climate change brings new challenges to humanity, so the relevance of accounting for weather and climate factors is growing every day.
Weather and climate studies require long time series of observational data. However, in practice, the observations do not cover the study region regularly and often contain gaps for one reason or another. Reanalyses are used to obtain reliable and consistent data on past weather and climate.
Reanalysis is the result of the work of a numerical model or a group of models combined into a single multi-model system with the assimilation of a wide range of observational network data, including satellite information, measurements from aircraft and probes, ships and buoys, as well as radar data. The resulting hydrometeorological parameters are presented on a regular grid as consistent data fields based on a long period of observations. Reanalysis data can be used to obtain statistics on the intensity and frequency of extreme weather events in the past. This information is very valuable and could be used, for example, to update the standard values (considered as extreme) for the selected atmospheric parameters.
Depending on the requirements for spatial resolution, both global and regional reanalyses are applied. The use of global reanalyses for applied studies of regional climate has a number of limitations associated with the insufficient spatial resolution of modern global models. On a global scale, reanalyses have a spatial resolution of no more than 25 km, but the scope of economic activity may require taking into account weather and climate factors on a much smaller scale: several kilometers or less.