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Summary In the context of evaluating the occurrence of drought events over Europe, soil moisture maps provide an invaluable resource to quantify the effects of rainfall deficits on vegetated lands. Spatially distributed models represent one of the main options, alongside satellite remote sensing, to successfully monitor this quantity over large areas in a cost effective way. This work has the double aim of: (i) intercomparing three soil moisture outputs obtained by different land-surface models (LISFOOD, CLM and TESSEL) through long (at least 6 years of data between 2001 and 2011) in-situ measured datastreams, and (ii) quantifying the added value of combining the estimates of these three models by means of a simple ensemble approach. Generally, the three models return similar soil moisture anomalies over most of Europe, with few notable exceptions during summer in Mediterranean regions. The comparison with in-situ data suggests no substantial differences among the models, with LISFLOOD slightly outperforming the other two in terms of correlation as also supported by a pairwise comparison. The combined soil moisture anomalies obtained via the ensemble-mean approach are characterized by an increase of both the correlation and the accuracy in retrieving extreme events compared to the single models; however, the number of observed extreme events actually captured by the ensemble model does not increase significantly if compared to the single models. Overall, the ensemble model results are skillful, with an all site average skill score of about 0.4. [ABSTRACT FROM AUTHOR]

Abstract: The two-source energy balance (TSEB) model uses remotely sensed maps of land–surface temperature (LST) along with local air temperature estimates at a nominal blending height to model heat and water fluxes across a landscape, partitioned between dual sources of canopy and soil. For operational implementation of TSEB, however, it is often difficult to obtain representative air temperature data that are compatible with the LST retrievals, which may themselves have residual errors due to atmospheric and emissivity corrections. To address this issue, two different strategies in applying the TSEB model without requiring local air temperature data were tested over a typical Mediterranean agricultural area using a set of high-resolution multispectral airborne remote sensing images. Alleviating the need for accurate local air temperature data as input, these two approaches estimate the surface-to-air temperature gradient that drives the sensible heat flux by directly exploiting the information available in the image. The two approaches include: 1) a scene-based internal calibration (TSEB-IC) procedure that estimates air temperature over a well-watered and fully vegetated pixel in the LST image, and 2) a disaggregation scheme (DisALEXI) that uses air temperature estimates from a time-differential coupled TSEB-atmospheric boundary layer model of atmosphere–land exchange (ALEXI). A comparison of the air temperatures modeled by TSEB-IC and DisALEXI with in situ weather station observations shows good agreement, with average differences on the order of 1K, comparable with the uncertainties in the remotely sensed surface temperature maps. Surface fluxes estimated by each method agree well with micro-meteorological measurements acquired over an olive orchard within the aircraft imaging domain. In comparison with fluxes generated with TSEB using local measurements of air temperature, instantaneous fluxes from these alternative methods show good spatial agreement, with differences of less than 10Wm−2 across the domain. Finally, a sensitivity analysis of the three models, performed by introducing artificial errors into the model inputs, demonstrates that the DisALEXI and TSEB-IC approaches are relatively insensitive to errors in absolute surface temperature calibration, while turbulent fluxes from TSEB applications using local air temperature measurements show sensitivity of approximately 30Wm−2 per degree temperature perturbation. This highlights the value of both internal calibration and time-differential estimation of the surface-to-air temperature gradient within a surface energy balance framework. [Copyright &y& Elsevier]

The article presents a study which examines the statistical analysis of inter-arrival time series of rainfall events for Mediterranean and Italian Sub-Alpine areas. The study uses the discrete probability polylog-series distribution as well as applied a simple qualitative trend analysis to some quantiles of inter-arrival times and to the average extent of rain clusters. The study reveals that the duration of dry periods for both environments increased.