English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In the present study, methods of reproducing mesoscale features of air temperature distribution in the Sevastopol region are assessed. The task of reproducing the meteorological fields is usually solved by applying methods of statistical analysis and spatial interpolation of data of standard meteorological observations, the data of reanalysis of meteorological fields or climate models taking into account the existing scenarios of future climate change, as well as using geospatial statistical modeling and data mining.    Methods of spatial data interpolation, including thin plate splines, inverse distance weighting, the bilinear interpolation and nearest-neighbor method are considered. The sources of information are observational data from meteorological stations in the Sevastopol region and the surrounding area, as well as reanalysis data on air temperature in the Azov-Black Sea region (ERA5). The location of the Orlinoye station was chosen as the main location for validation of the interpolation methods.    As a result of comparative analysis, it is shown that the ERA5 reanalysis data reflect, to a greater extent, the thermal conditions of air masses over the Black Sea in the vicinity of the Crimean Peninsula and, to a lesser extent, the mesoclimatic features of the region. It is concluded that the existing climate monitoring network is not enough to reproduce mesoscale features of Sevastopol region and there is a need for its expansion. This can be done at the expense of non-commercial network of sensors measuring environmental parameters.

Comparison of methods to reconstruct mesoscale features of air temperature distribution in the Sevastopol region