Global Trends in Hydroclimatic Variables (1979–2023) from ERA5 at 0.25° Resolution

This dataset provides global gridded trend estimates (Z-values) for key hydroclimatic variables over the period 1979–2023, derived from the ERA5 reanalysis dataset. The analysis was performed to detect long-term changes in climate and water cycle drivers at a spatial resolution of 0.25° (~25 km).

Variables included (all in .mat format):





Z_air_temperature.mat – near-surface at 2m air temperature trends




Z_cloud_cover.mat – total cloud cover trends




Z_ETo.mat – reference evapotranspiration (FAO-56 Penman-Monteith) trends




Z_long_radiation.mat – net longwave radiation trends




Z_net_radiation.mat – net radiation trends




Z_PET.mat – potential evapotranspiration (Priestley–Taylor) trends




Z_precipitation.mat – total precipitation trends




Z_short_radiation.mat – net shortwave radiation trends




Z_soil_moisture.mat – volumetric soil moisture trends




Z_soil_temperature.mat – soil temperature trends




Z_solar_radiation.mat – incoming solar radiation trends




Z_VPD.mat – vapor pressure deficit trends




Z_wind_speed.mat – near-surface at 2m wind speed trends



Methodology:





Long-term trends were calculated using the Mann-Kendall test for trend detection.




Significance levels were evaluated at α = 0.05.




Trend magnitudes are expressed as Z-values (normalized test statistics).



Spatial and Temporal Coverage:





Time span: 1979–2023 (45 years)




Spatial resolution: 0.25° × 0.25° global grid




Dataset source: ERA5 reanalysis (ECMWF)



Applications:This dataset can be used for:





Hydroclimatic and environmental change assessments




Attribution studies on drivers of evaporative demand and water cycle intensification




Regional and global climate modeling validation




Agricultural and hydrological impact studies



File format:All files are provided as MATLAB .mat files containing 2D gridded arrays corresponding to the global extent.

Note: All figures presented in the dataset description can be reproduced using the accompanying MATLAB script plot_global_trends_ERA5_Zmaps.m, which loads the .mat files and generates the global Z-value maps for each variable.

 

Contact:For questions or collaboration opportunities, please contact:

Saeed Karimzadeh, PhDUniversity of California Davis [email protected]; [email protected]