https://github.com/adilurrahim/globaltemperaturetrend_era5

https://github.com/adilurrahim/globaltemperaturetrend_era5

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https://github.com/adilurrahim/GlobalTemperatureTrend_ERA5/blob/main/

# Historical Global and Regional Spatiotemporal Patterns in Daily Temperature using ERA5 hourly data from 1981 to 2020

It is widely reported that surface air temperatures have increased over the last few decades.  However, less attention has focused on the spatial and seasonal features of the warming trend, using state-of-the-art model output based on historical temperature observations.  This research uses such model output to identify the geographic and temporal features of the trends in daily mean surface air temperature, defined both as the mean of the maximum and minimum temperatures over the calendar day ("meanmaxmin") and as the mean of the 24 hourly observations per day ("meanhourly"), across the terrestrial Earth.  Results reveal several significant "hot spots" of significantly increasing temperature trends, including in spring and autumn in the Arctic, in July in the Northern Hemisphere mid-latitudes, and in Eurasia in spring, Europe and the lower latitudes in summer, and the tropics in autumn.  Although cooling is also observed, rates are often statistically insignificantLatin America, Southeast Asia, and the Maritime Continent, and, to some extent, Australia.  Elsewhere, strong concentrations of grid points with warming signals are found in some times of the year but not as much in others.  All of these trends are nearly identical regardless of whether calculated as "meanmaxmin" or "meanhourly. "  These results will help scientists and citizens to understand more fully the warming signal experienced to date, so that observed agricultural, commercial, ecological, economic, and recreational trends might be understood more fully in light of climate change considerations.

The indexed R and python scripts are stored in Scripts folder. The maps preapred for the study is available in the Figures folder. The ERA5 hourly data can be downloaded from this website: https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.e2161bac

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