Abstract
Land-atmosphere interactions at different temporal and spatial scales are important for our understanding of the Earth system and its modeling. The Landscape Evolution Observatory (LEO) at Biosphere 2, managed by the University of Arizona, hosts three nearly identical artificial bare-soil hillslopes with dimensions of 11 × 30 m2 (1 m depth) in a controlled and highly monitored environment within three large greenhouses. These facilities provide a unique opportunity to explore these interactions. The dataset presented here is a subset of the measurements in each LEO’s hillslopes, from 1 July 2015 to 30 June 2019 every 15 minutes, consisting of temperature, water content and heat flux of the soil (at 5 cm depth) for 12 co-located points; temperature, relative humidity and wind speed above ground at 5 locations and 5 different heights ranging from 0.25 m to 9–10 m; 3D wind at 1 location; the four components of radiation at 2 locations; spatially aggregated precipitation rates, total subsurface discharge, and relative water storage; and the measurements from a weather station outside the greenhouses.
Highlights
Background & SummaryThe understanding of land-atmosphere interactions is important for improvements in Earth System Modelling[1,2,3] for climate assessment, weather prediction, and subseasonal-to-seasonal forecasts[4]
The enclosed atmosphere could be highly controlled, it has been most of the time naturally driven except for precipitation during the experiments and temperature with the purpose of keeping the bays at temperatures allowing the work of the scientists
Quality control, and sharing of other data, including that from more than 3,000 sensors buried deeper in the soil, are left to future efforts. This dataset[30] compiles part of the Landscape Evolution Observatory (LEO) measurements in the three individual hillslopes of (1) meteorological variables above the hillslopes’ surface, (2) soil moisture, heat flux and temperature of the soil near the surface, (3) precipitation, discharge and water storage aggregated for the entire hillslope, and (4) meteorological variables outside LEO from an automatic weather station
Summary
The understanding of land-atmosphere interactions is important for improvements in Earth System Modelling[1,2,3] for climate assessment, weather prediction, and subseasonal-to-seasonal forecasts[4]. The impact of some of these interactions occur at large spatiotemporal scales affecting regional climates[5,6] through, e.g. soil moisture - precipitation feedbacks[7,8] and mesoscale circulations, they are primarily driven by local interactions between the land-surface and the atmospheric boundary layer[9,10] Studies of these interactions face three major challenges[11,12,13]: (1) lack of observations with the adequate spatiotemporal resolution and precision[14], (2) uncertainties due to the large number of processes and feedbacks involved, and (3) the difficulty of controlled and replicated experimentation. Science questions that could be addressed with this dataset include, but are not limited to, what is the microscale spatial variability of atmospheric and land surface states in a controlled environment? how does this microscale variability change diurnally, from day to day, and seasonally? What is the temporal relationship between the atmospheric and land surface microscale variabilities? How do atmospheric variables vary with height? What are the surface turbulent fluxes over bare soil[26,27] through the closure of water[21] and energy balances? what is the relationship of these turbulent fluxes with atmospheric and land surface states (e.g., the vertical gradient of atmospheric variables, the horizontal variance of near-surface atmospheric and soil variables)? It is further expected that the analysis of the existing data set can lead to new hypotheses about the interactions between the land surface and the atmosphere, and that these hypotheses can be tested through experimentation involving manipulation of environmental variables, such as rainfall and wind speed
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