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Abstract. Knowledge about the spatio-temporal variability of soil moisture is essential to understand and predict processes in climate science and hydrology. A significant body of literature exists on the characterization of the spatial variability and the rank stability (also called temporal stability) of absolute soil moisture. Yet previous studies were generally based on short-term measurement campaigns and did not distinguish the respective contributions of time-varying and time-invariant components to these quantities. In this study, we investigate this issue using measurements from 14 grassland sites of the SwissSMEX soil moisture network (spatial extent of approx. 150 × 210 km) over the time period May 2010 to July 2011. We thereby decompose the spatial variance of absolute soil moisture over time in contributions from the spatial variance of the mean soil moisture at all sites (which is time-invariant), and components that vary over time and are related to soil moisture dynamics. These include the spatial variance of the temporal soil moisture anomalies at all sites and the covariance between the site anomalies to the spatial mean at a given time step and those for the temporal mean values. The analysis demonstrates that the timeinvariant term contributes 50-160 % (on average 94 %) of the spatial soil moisture variance at any point in time, while the covariance term generally contributes negatively to the spatial variance. On the other hand, the spatial variance of the temporal anomalies, which is overall most relevant for climate and hydrological applications because it is related to soil moisture dynamics, is relatively limited and constitutes at most 2-30 % (on average 9 %) of the total variance. Nonetheless, this term is not negligible compared to the temporal anomalies of the spatial mean. These results suggest that a large fraction of the spatial variability of soil moisture assessed from short-term campaign may be time-invariant if other regions present a similar behavior. Moreover, we find that the rank (or temporal) stability concept, when applied to absolute soil moisture at the sites, mostly characterizes the time-invariant patterns. Indeed, sites that best represent the mean soil moisture dynamics of the network are not the same as those that best reflect mean soil moisture at any point in time. Overall, this study shows that conclusions derived from the analysis of the spatio-temporal variability of absolute soil moisture need not generally apply to temporal soil moisture anomalies, and hence to soil moisture dynamics.

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[1] Soil moisture measurements are essential to understand land surface-atmosphere interactions. In this paper we evaluate the performance of the low-cost 10HS capacitance sensor (Decagon Devices, United States) using laboratory and field measurements. Measurements with 10HS sensors of volumetric water content (VWC, Vol.%), integrated absolute soil moisture (millimeters) over the measured soil column, and the loss of soil moisture (millimeters) for rainless days are compared with corresponding measurements from gravimetric samples and time domain reflectometry (TDR) sensors. The field measurements were performed at two sites with different soil texture in Switzerland, and they cover more than a year of parallel measurements in several depths down to 120 cm. For low VWC, both sensor types present good agreement for laboratory and field measurements. Nevertheless, the measurement accuracy of the 10HS sensor reading (millivolts) considerably decreases with increasing VWC: the 10HS sensors tend to become insensitive to variations of VWC above 40 Vol.%. The field measurements reveal a soil type dependency of the 10HS sensor performance, and thus limited applicability of laboratory calibrations. However, with site-specific exponential calibration functions derived from parallel 10HS and TDR measurements, the error of the 10HS compared to the TDR measurements can be decreased for soil moisture contents up to 30 Vol.%, and the day-to-day variability of soil moisture is captured. We conclude that the 10HS sensor is appropriate for setting up dense soil moisture networks when focusing on medium to low VWC and using an established site-specific calibration function. This measurement range is appropriate for several applications in climate research, but the identified performance limitations should be considered in investigations focusing on humid conditions and absolute soil moisture.

The analysis of the spatial-temporal variability of soil moisture can be carried out considering the absolute (original) soil moisture values or relative values, such as the percent of saturation or temporal anomalies. Over large areas, soil moisture data measured at different sites can be characterized by large differences in their minimum, mean, and maximum absolute values, even though in relative terms their temporal patterns are very similar. In these cases, the analysis considering absolute compared with percent of saturation or temporal anomaly soil moisture values can provide very different results with significant consequences for their use in hydrological applications and climate science. In this study, in situ observations from six soil moisture networks in Italy, Spain, France, Switzerland, Australia, and United States are collected and analyzed to investigate the spatial soil moisture variability over large areas (250-150,000 km 2 ). Specifically, the statistical and temporal stability analyses of soil moisture have been carried out for absolute, temporal anomaly, and percent of saturation values (using two different formulations for temporal anomalies). The results highlight that the spatial variability of the soil moisture dynamic (i.e., temporal anomalies) is significantly lower than that of the absolute soil moisture values. The spatial variance of the time-invariant component (temporal mean of each site) is the predominant contribution to the total spatial variance of absolute soil moisture data. Moreover, half of the networks show a minimum in the spatial variability for intermediate conditions when the temporal anomalies are considered, in contrast with the widely recognized behavior of absolute soil moisture data. The analyses with percent saturation data show qualitatively similar results as those for the temporal anomalies because of the applied normalization which reduces spatial variability induced by differences in mean absolute soil moisture only. Overall, we find that the analysis of the spatial-temporal variability of absolute soil moisture does not apply to temporal anomalies or percent of saturation values.

This study investigates the spatial representativeness of the temporal dynamics of absolute soil moisture and its temporal anomalies over North America based on a range of data sets. We use three main data sources: in situ observations, the remote-sensing-based data set of the European Space Agency Climate Change Initiative on the Essential Climate Variable soil moisture (ECV-SM), and land surface model estimates from European Centre for Medium-Range Weather Forecasts's ERA-Land. The intercomparisons of the three soil moisture data sources are performed at the in situ locations as well as for the full-gridded products. The applied method allows us to quantify the spatial footprint of soil moisture. At the in situ locations it is shown that for absolute soil moisture the ECV-SM and ERA-Land products perform similarly, while for the temporal anomalies the ECV-SM product shows more similarity in spatial representativeness with the in situ data. When taking into account all grid cells of the ECV-SM and ERA-Land products to calculate spatial representativeness, we find the largest differences in spatial representativeness for the absolute values. The differences in spatial representativeness between the single products can be related to some of their intrinsic characteristics, i.e., for ECV-SM low similarities are found in topographically complex terrain and areas with dense vegetation, while for ERA-Land the smoothed model topography and surface properties affect soil moisture and its spatial representativeness. Additionally, we show that the applied method is robust and can be used to analyze existing networks to provide insight into the locations in which higher station density would be of most benefit.

No abstract

Knowledge about the spatio-temporal variability of soil moisture is essential to understand and predict processes in climate science and hydrology. A significant body of literature exists on the characterization of the spatial variability and the ranks stability (also called temporal stability) of absolute soil moisture. Yet previous studies were generally based on short-term measurement campaigns and did not distinguish the respective contributions of time varying and time invariant components to these quantities. In this study, we investigate this issue using measurements from 14 grassland sites of the SwissSMEX soil moisture network (spatial extent of approx. 150 × 210 km) over the time period May 2010 to July 2011. We thereby decompose the spatial variance of absolute soil moisture over time in contributions from the spatial variance of the mean soil moisture at all sites (which is time invariant), and components that vary over time and are related to soil moisture dynamics. These include the spatial variance of the temporal soil moisture anomalies at all sites and the covariance between the sites' anomalies to the spatial mean at a given time step and those for the temporal mean values. The analysis demonstrates that the time invariant term contributes 50–160% (on average 94%) of the spatial soil moisture variance at any point in time, while the covariance term generally contributes negatively to the spatial variance. On the other hand the spatial variance of the temporal anomalies, which is overall most relevant for climate and hydrological applications because it is directly related to soil moisture dynamics, is relatively limited and constitutes at most 2–30% (on average 9%) of the total variance. Nonetheless, this term is not negligible compared to the temporal anomalies of the spatial mean. These results suggest that a large fraction of the spatial variability of soil moisture assessed from short-term campaign is time invariant. Moreover, we find that the rank (or "temporal") stability concept when applied to absolute soil moisture, mostly characterizes the time-invariant patterns. Indeed, sites that best represent the mean soil moisture dynamics of the network are not the same as those that best reflect mean soil moisture at any point in time. Overall this study shows that conclusions derived from the analysis of the spatio-temporal variability of absolute soil moisture do generally not apply to temporal soil moisture anomalies, and hence to soil moisture dynamics