Every second, an extraordinary number and variety of organisms on land leverage the resources of soil, water, and air to function, grow, and reproduce. These individual actions by plants, fungi, microorganisms, animals, and humans across the Earth’s surface have wide ramifications on Earth system processes. Among those are the transfer of heat, water vapor, and momentum between surface and atmosphere, hydrologic flows in rivers, streams, and groundwater, and mineral transformations in the lithosphere. However, observing and predicting how these processes evolve continues to be challenging.
In particular, the exchange of heat, momentum, carbon, and water with the overlying atmosphere occurs at a multitude of space and time scales. For the biosphere, these processes generally scale up from genes to cells to organisms to ecosystems to landscapes and biomes (Desai et al, 2010). For the atmosphere, the processes mostly scale down, from global gradients in net radiation to planetary climate dynamics and waves to synoptic weather systems to mesoscale and microscale turbulence (Ahrens, 2019).
This intersection of scales promotes emergent function and heterogeneity, thus driving the nonlinearity we observe in interactions among processes such as evapotranspiration, landscape resilience, and land-atmosphere feedbacks.
As a result, substantial uncertainty arises when applying non-linear parameterizations of these processes for atmospheric modeling, land surface remote sensing (e.g., Ershadi et al., 2013), landscape and urban ecology (e.g., Grimmond, et al., 2011), or watershed hydrology (e.g., Wang and Dickinson, 2012). Recently, several field experiments have set out to creatively address the scaling challenges.
The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was one such study that sought to intensively sample scales of land-atmosphere interaction across a typical “grid cell” of numerical weather or regional climate models (Butterworth et al., 2020). A dense array of eddy-covariance flux towers and aircraft were deployed alongside atmospheric boundary-layer profiling over four months in a forested landscape. These were further accompanied by airborne land surface temperature, hyperspectral and LIDAR remote sensing, as well as vegetation phenology, inventory, and ecophysiology plots. In this system, ecosystem heterogeneity is thought to drive mesoscale atmospheric motions that contribute to the lack of energy balance closure often observed at flux towers.
Other recent field experiments have also sought to investigate the role of scale in various land-atmosphere interactions, including CloudRoots (Vilà-Guerau de Arellano et al., 2020), FESSTVaL, SCALE-X (Wolf et al., 2017), LAFE (Wulfmeyer et al., 2018), and HiWater-MUSOEXE (Xu et al., 2013). A number of synthesis and high-resolution modeling studies that integrate both short-term and long-term observations, such as those made by Ameriflux, Fluxnet, LTER, CZO, or NEON, to test a variety of scale-dependency and scale-invariance hypotheses, are also ongoing
A new cross-journal special collection has just been launched to showcase such work. We are soliciting papers highlighting recent investigations from these and other land-atmosphere field campaigns, including observational analyses, tests of theoretical approaches to scaling or modeling these processes, and model-based evaluation and diagnostic studies. Papers can be submitted to JGR: Biogeosciences, JGR: Atmospheres, Journal of Advances in Modeling the Earth System (JAMES), or Earth and Space Sciences as appropriate.
—Ankur Desai (firstname.lastname@example.org,
Desai, A. R.,,, and (2021), Advances in scaling and modeling of land-atmosphere interactions, Eos, 102, https://doi.org/10.1029/2021EO155255. Published on 04 March 2021.
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