Dataset: Turbulence flux-variance scaling and anisotropy parameters from a mountain observatory for evaluating Monin-Obukhov Similarity Theory (MOST)

This dataset contains high-temporal-resolution atmospheric turbulence and flux measurements collected during the ABLES-MOST (Atmospheric Boundary Layer Experimental Study – Micrometeorological Observational and Scaling Techniques) field campaign. The data span a continuous observational period from April 2024 to March 2025, with a temporal resolution of 30 minutes. All measurements were obtained at a constant height of 7.3 m above ground level using eddy-covariance instrumentation, including a sonic anemometer and gas analyzers (IRGASON, Campbell Scientific Inc., USA). Key measured and derived variables include:- Steady State tests: momentum flux (SST_uw) , sensible heat flux (SST_wTs), latent heat flux (SST_wH2O), and CO₂ flux (SST_wCO2)- Turbulence statistics: standard deviations of three-dimensional wind components (u_std, v_std, w_std), sonic temperature (Ts_std), specific humidity (q_std), and CO₂ concentration (c_std)- Scaling parameters: friction velocity (ustar), temperature scale (tstar), humidity scale (qstar), CO₂ scale (cstar), and Obukhov length (L)- Meteorological conditions: mean horizontal wind speed (U_mean) and wind direction (WD)- Additional diagnostic variables: anisotropy parameter (aniso_beta, xB and yB) The dataset is structured in comma-separated format with clear column headers and consistent timestamp formatting. It is suitable for investigating surface-layer similarity theory, validating flux–variance scaling relationships, assessing turbulence characteristics under varying stability conditions, and supporting boundary-layer parameterization in numerical models. Potential applications include micrometeorological research, land–atmosphere interaction studies, carbon cycle analysis, and environmental monitoring. Users are advised to perform appropriate quality control (e.g., stationarity tests, outlier filtering) .