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The new far‐field low‐frequency electromagnetic method used the electromagnetic ground wave from distant radio transmitters at low frequencies to estimate temporal variations of factors affecting subsurface electrical conductivity averaged along the propagation path between either a transmitter and a receiver or two receivers that are in line with a transmitter. Phase and phase difference between two receivers depend on three factors that influence the changes in electrical conductivity: soil moisture, depth to the groundwater table and soil temperature. This dependence was investigated by simulations and evaluated by an experiment. The measurement layout was based on simulating ground wave propagation over a layered subsurface using the surface impedance method and the Sommerfeld ground wave attenuation function. A three‐layer model for the subsurface was used, which includes a soil layer, an unsaturated vadose zone and a saturated groundwater zone. The results of simulations at a frequency of 77.5 kHz showed that the phase of the ground wave is strongly influenced by natural variation of the above‐mentioned three factors; 77.5 kHz is the carrier frequency of the Normal Time Service Germany (DCF77) in Mainflingen/Germany, that was chosen as a source of the low‐frequency radio waves used in the experiment. Over a 2‐year measurement period, the amplitude and phase of the ground wave were recorded with two receivers, one 70 km and the other 110 km away from the transmitter. Additionally, phase difference between the two receivers was calculated. In situ observations of soil moisture, depth to the groundwater table, and soil temperature along the transects under investigation were used to estimate phase and phase difference dependencies. Multiple regression analysis of the measured phase and phase difference revealed a strong dependence on the depth to the groundwater table and on soil temperature, whereas the impact of soil moisture on the phase and phase difference was found to be very low. Conversely, the relations obtained can be used to estimate the variation of the depth to the groundwater table, if the phase at a given frequency and the soil temperature information are available.

During the Convective Storm Initiation Project experiment, which was conducted in summer 2005 in southern England, vertical velocity in the convective boundary layer (CBL) was measured simultaneously with a research aircraft and a wind lidar. The aircraft performed horizontal flight legs approximately parallel to the prevailing wind direction and centered over the lidar. This measurement setup allows for the comparing of CBL characteristics (CBL depth z i, integral length scale l w, spectral peak wavelength λ m, and vertical velocity variance [Formula: see text]) from temporal (lidar) and spatial (aircraft) measurements. For this, the lidar time series are transferred into space using the mean wind. While the statistics of the aircraft data are all based on the 34-km flight legs, the averaging interval for the lidar is either 1 h or a longer period that corresponds to the 34-km leg. Although the l w and λ m values from aircraft and lidar measurements are in the same range (100–200 and 500–2000 m) and agree well on the average, the correlation for individual legs is very low ( R2 < 0.17). One possible explanation is the large uncertainty that arises from the transfer of the lidar time series to space. For [Formula: see text], the agreement between aircraft and lidar is better for individual legs ( R2 ≥ 0.63), but the mean absolute difference in [Formula: see text] is about 2.5 times as large as the statistical error. We examine the nonstationarity and heterogeneity for the lidar and aircraft samples and can exclude these as the major sources for the large differences between lidar and aircraft data.