Data from: Comparison of turbulent transport dissimilarity and the role of coherent structures in the unstable surface layer between urban and rural areas

The dataset was collected from the 325-m meteorological tower in Beijing (39.97°N, 116.37°E, 140 m level) and the 102-m tower in Xianghe (39.75°N, 116.96°E, 32 m level) during July 2017. Each site was equipped with a Gill WindMaster Pro sonic anemometer and a LI-COR LI-7500A open-path gas analyzer to measure wind components, air temperature, H₂O, and CO₂ concentrations at 10 Hz. At the urban site, surface radiation components were additionally measured using a CNR1 radiometer. After quality control, valid 30-min flux segments were archived for use. # Description of the data and file structure 1. FIG2_timeseries_urban_rural_2017-07.mat contains half-hourly time series of air temperature, relative humidity, wind speed, TKE, and net radiation (urban only). Columns correspond to different variables, time is a datetime vector, and units are provided in units. 2. FIG3_windrose_urban_rural_2017-07.mat contains half-hourly wind direction (degrees) and wind speed (m/s) time series for wind-rose plotting. Columns correspond to urban wind direction, urban wind speed, rural wind direction, and rural wind speed; time is a datetime vector, and units are provided in units. 3. FIG4_diurnal_fluxes_urban_rural_2017-07.mat includes the full half-hourly July flux time series (8 columns: momentum, sensible heat, latent heat, CO₂ for urban and rural) plus a diurnal block with 48-bin local-time averages (and per-day values for boxplots); variable names and units are provided in columns and units. 4. FIG5_transport_efficiency_scatter.mat contains scatter data of turbulent transport efficiencies versus -z/L. The file is organized into two groups, urban and rural, each including zeta (-z/L) and four efficiency series for momentum, heat, water vapor, and CO₂. All variables are dimensionless. 5. FIG6_footprint_Urban_2017-07.mat contains 1-D footprint distances as a function of –z/L at the urban site, including peak contribution distance and 90% cumulative distance. The file provides raw data with timestamps and binned statistics (log-spaced means and standard deviations) for error bars. 6. FIG7_TSI_vs_instability_Urban_Rural_2017-07.mat includes the Turbulent Transport Similarity Index between heat and momentum, heat and water vapor, and heat and CO₂ under varying instability. The dataset is organized by site and provides raw values, binned means, standard deviations, and sample counts for each bin. 7. FIG8_quadrant_contrib_timefraction_vs_instability_Urban_Rural_2017-07.mat includes quadrant absolute-flux contributions and time fractions of heat and momentum as a function of –z/L, with columns corresponding to Q1–Q4 for both urban and rural sites. 8. FIG9_wavelet_20170712_0830.mat includes continuous wavelet transform coefficients of θ′, u′, and w′ for the urban and rural sites, along with time and scale axes, processing parameters, and the corresponding 1 Hz input series. 9. FIG10_wavelet_20170712_1230.mat contains wavelet transform results of θ′, u′, and w′ at the urban and rural sites, with the same structure as FIG9 but for the 12:30 case. 10. FIG11_EBR_closure_bins_Urban_2017-07.mat includes paired H+LE and Rn data for the urban site, grouped into three stability ranges (−0.5<z/L<0, −1.5<z/L<−0.5, z/L<−1.5), with robust fitted slopes (initial/final) and the validity flags and axis settings used to reproduce Figure 11.