[1] Analysis is presented of airborne lidar measurements of water vapor, covering a height range from 1.5 to 10.4 km, from three field campaigns (midlatitude summer, polar winter, and subtropical summer). The lidar instrument provides two-dimensional cross sections of absolute humidity, with high accuracy (errors less than 5-7%) and high vertical ( 200 m) and horizontal ( 2 km) resolution. Structure functions, i.e., statistical moments up to the fifth-order of absolute increments over a range of scales, are investigated, and power law scaling or statistical-scale invariance was found over horizontal distances from 5 to 100 km. The scaling exponents are found to take different values, depending on whether or not the observations were taken in an air mass where convective clouds were present. The exponent of the first-order structure function in nonconvective regions, H = 0.63˙0.10, is large indicating a smooth series with long-range correlations, in contrast to the lower value H = 0.35˙0.11 found in convective air masses. Correspondingly, the moisture field in the convective regime was found to be more intermittent than for the nonconvective regime, i.e., water vapor structures in convectively influenced air mass show more jump discontinuities, which could be explained by the moistening and drying effects of updrafts and downdrafts in convective air mass. Within each regime (convective or nonconvective), the values appear to be universal, with no significant dependence on the season, latitude, or height where the observations were made. Furthermore, some evidence is found that vertical correlation lengths are longer in convective air masses.Citation: Fischer, L., G. C. Craig, and C. Kiemle (2013), Horizontal structure function and vertical correlation analysis of mesoscale water vapor variability observed by airborne lidar,

Free tropospheric water vapor variability, measured by airborne lidar over Europe during summertime, is analyzed at altitudes from 2 km to 10 km. Horizontal structure functions of specific humidity were computed and show power‐law scaling between about 10 km to 100 km in range. The second‐order structure function shows scaling exponents equivalent to spectral slopes that vary from around 5/3 in the lower troposphere to 2 at upper levels. More specifically humidity smoothness typically increases with height, while intermittency decreases. A classification of the data according to whether the series occurred above or below the level of nearby convective cloud tops gives a separation of the scaling exponents in the two air masses. The results are consistent with a water vapor distribution determined at upper levels by a downscale cascade of variance by advective mixing, but increasingly influenced at lower levels by local injection of humidity by moist convection.

The spatial scale dependence of midlatitude water vapor variability in the high-resolution limited-area model COSMO is evaluated using diagnostics of scaling behavior. Past analysis of airborne lidar measurements showed that structure function scaling exponents depend on the corresponding airmass characteristics, and that a classification of the troposphere into convective and nonconvective layers led to significantly different power-law behaviors for each of these two regimes. In particular, scaling properties in the convective air mass were characterized by rough and highly intermittent data series, whereas the nonconvective regime was dominated by smoother structures with weaker small-scale variability. This study finds similar results in a model simulation with an even more pronounced distinction between the two air masses. Quantitative scaling diagnostics agree well with measurements in the nonconvective air mass, whereas in the convective air mass the simulation shows a much higher intermittency. Sensitivity analyses were performed using the model data to assess the impact of limitations of the observational dataset, which indicate that analyses of lidar data most likely underestimated the intermittency in convective air masses due to the small samples from single flight tracks, which led to a bias when data with poor fits were rejected. Though the quantitative estimation of intermittency remains uncertain for convective air masses, the ability of the model to capture the dominant weather regime dependence of water vapor scaling properties is encouraging.

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