Machine-learning-based downscaling of hourly ERA5-Land air temperature over mountainous regions. Atmosphere 14 ( 4), 610. Google Scholar Crossref Sun L., Lan Y. & Jiang R. 2023 Using CNN framework to improve multi-GCM ensemble predictions of monthly precipitation at local areas: An ...
Land is a global land reanalysis dataset produced by ECMWF based on ERA5, specifically targeting land surfaces. It provides high-spatial- and high-temporal-resolution data (0.1 degrees monthly/hourly) for over 50 variables [17]. This dataset offers valuable resources for studying land surface ...
It includes the evolution of greenhouse gases, volcanic eruptions, sea surface temperature, wind waves, and sea ice (quality-assured monthly updates of ERA5 are published within three months of real-time). For storage issues, data have been gridded to a regular lat-lon grid of 0.25°. At ...
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Finally, at the monthly scale, September was identified as the month of the year with the highest percentage of grid points with positive trends mainly located in central, southern, and north-eastern Italy. Keywords: ERA5-Land; rainfall; trend; Italy ...
Complementarity analysis showed a good complementarity between resources on the monthly timescale, whereas for daily and hourly scales some negative correlation exists, but at significantly lower levels (less than −0.35). On the country level, the solar and wind resources tend to complement each ...
To verify the results obtained from the SVD analysis, we further apply the standard empirical orthogonal function (EOF) decomposition to the symmetric and antisymmetric TST fields and then apply the linear regression method onto the TLH field, i.e., by regressing the monthly TLH field upon the ...