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 [e-mail]; [e-mail]