With the aim of developing a fully coupled atmosphere-hydrology model system, the Weather Research and Forecasting (WRF) model was enhanced by integrating a new set of hydrologic physics parameterizations accounting for lateral water flow occurring at the land surface. The WRF-Hydro modeling system was applied for a 3 year long simulation in the Crati River Basin (Southern Italy), where output from the fully coupled WRF/WRF-Hydro was compared to that provided by original WRF model. Prior to performing coupled land-atmosphere simulations, the stand-alone hydrological model (''uncoupled'' WRF-Hydro) was calibrated through an automated procedure and validated using observed meteorological forcing and streamflow data, achieving a Nash-Sutcliffe Efficiency value of 0.80 for 1 year of simulation. Precipitation, runoff, soil moisture, deep drainage, and land surface heat fluxes were compared between WRF-only and WRF/WRF-Hydro simulations and validated additionally with ground-based observations, a FLUXNET site, and MODIS-derived LST. Since the main rain events in the study area are mostly dependent on the interactions between the atmosphere and the surrounding Mediterranean Sea, changes in precipitation between modeling experiments were modest. However, redistribution and reinfiltration of local infiltration excess produced higher soil moisture content, lower overall surface runoff, and higher drainage in the fully coupled model. Higher soil moisture values in WRF/WRF-Hydro slightly influenced precipitation and also increased latent heat fluxes. Overall, the fully coupled model tended to show better performance with respect to observed precipitation while allowing more water to circulate in the modeled regional water cycle thus, ultimately, modifying long-term hydrological processes at the land surface.

Simulations from 13 highly resolved regional climate models run within the Coordinated Downscaling Experiment initiative at 0.11 ∘ resolution with boundary forcings from five different Coupled Model Intercomparison Project Phase 5 global models are employed to derive future climate change signal for the Greater Alpine Region (GAR) and four smaller investigation areas. Evaluation statistics include mean temperature and precipitation, frequency of days with precipitation over 1 mm and over 15 mm, 90% quantile of the frequency distribution, and maximum number of consecutive dry days. The evaluation for the period from 1971 to 2000 indicates that the models reproduce spatial seasonal precipitation patterns. In general, the simulations underestimate the seasonal mean temperature and overestimate the mean precipitation values. In GAR the ensemble seasonal mean temperature bias ranges from −0.8 to −1.9 ∘ C. The bias in precipitation varies between +14.8% in summer and +41.6% in the winter season. Larger errors are found for other statistics and in the investigated regions. In general, no significant gains in the quality of reproduction of the observed precipitation and temperature statistics compared to previous experiments can be identified. The temperature calculations for 2071-2100 related to the period from 1971 to 2000 in the GAR area show ensemble mean increases in the seasonal mean 2 m temperature of 2.5 ∘ C in fall and winter, 2.4 ∘ C in summer, and 1.9 ∘ C in spring. In the same area, precipitation is simulated to increase up to 12.3% in winter and 5.7% in spring. Only minor changes of the ensemble mean are predicted with +2.3% in fall and −1.7% in summer.

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ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.