In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.@en

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. It is difficult to partition ecosystem-scale evapotranspiration (ET) measurements into E and T, which makes it difficult to validate satellite data and land surface models. Here, we review current progress in partitioning E and T and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques create new opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. For example, many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but more analysis is necessary to determine the conditions for which this assumption holds. Another critical assumption for many partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T can exceed 95 % of ET from certain ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon-water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water fluxes and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.@en

Trees play a crucial role in the water, carbon and nitrogen cycle on local, regional and global scales. Understanding the exchange of momentum, heat, water, and CO 2 between trees and the atmosphere is important to assess the impact of drought, deforestation and climate change. Unfortunately, ground measurements of tree properties such as mass and canopy interception of precipitation are often expensive or difficult due to challenging environments. This paper aims to demonstrate the concept of using robust and affordable accelerometers to measure tree properties and responses. Tree sway is dependent on mass, canopy structure, drag coefficient, and wind forcing. By measuring tree acceleration, we can relate the tree motion to external forcing (e.g., wind, precipitation and related canopy interception) and tree physical properties (e.g., mass, elasticity). Using five months of acceleration data of 19 trees in the Brazilian Amazon, we show that the frequency spectrum of tree sway is related to mass, canopy interception of precipitation, and canopy–atmosphere turbulent exchange.@en

Land–atmosphere interactions depend on momentum transfer from the atmosphere to the canopy, which in turn depends on the tree drag coefficient. It is known that the drag coefficient, and thus tree–atmosphere momentum transfer, can vary strongly within a canopy. Yet, only few measurements are available to study the variation of tree–atmosphere momentum transfer in time and space, and in response to tree water deficit. In this paper we use accelerometers to estimate tree–atmosphere momentum transfer for 19 individual trees of 7 different species in the Brazilian Amazon. The 5-month monitoring period included the transition from wet to dry months. Here, we demonstrate that, under field conditions, tree–atmosphere momentum transfer can vary considerably in time and space (up to a factor of 2.5). Increased water-related stem variations during the dry months are related to observed changes in tree–atmosphere momentum transfer, which is hypothesized to be caused by tree-water-deficit-induced changes in tree mass.@en

The mass of trees is influenced by physiological processes within the tree (e.g. transpiration and root water uptake), as well as external loads (e.g. intercepted precipitation). Recent studies have found diurnal variations in radar backscatter over vegetated areas, which might be attributed to mass changes of the vegetation layer. Field measurements are required to study the driving processes. This study aims to use measured three-dimensional displacement and acceleration of trees, to detect and quantify their diurnal (bio)mass variations. Accelerometers and dendrometers were installed on seven different tree species in the Amazon rainforest. Trees were selected to cover a broad range of wood density. Using spectral analysis, the governing frequencies in the acceleration time series were found. The governing frequencies showed a diurnal pattern, as well as a change during precipitation events. Our results suggest that we can separate and potentially quantify tree mass changes due to (1) internal water redistribution and (2) intercepted precipitation. This will allow further investigation of the effect of precipitation and water stress on tree dynamics in forest canopies. @en

Trees play a crucial role in the water, carbon and nitrogen cycle on local, regional and global scales. Understanding the exchange of heat, water, and CO2 between trees and the atmosphere is important to assess the impact of drought, deforestation and climate change. Unfortunately, ground measurements of tree dynamics are often expensive, or difficult due to challenging environments. We demonstrate the potential of measuring (bio)physical properties of trees using robust and affordable acceleration sensors. Tree sway is dependent on e.g. mass and wind energy absorption of the tree. By measuring tree acceleration we can relate the tree motion to external loads (e.g. precipitation), and tree (bio)physical properties (e.g. mass). Using five months of acceleration data of 19 trees in the Brazilian Amazon, we show that the frequency spectrum of tree sway is related to mass, precipitation, and canopy drag. This presentation aims to show the concept of using ccelerometers to measure tree dynamics, and we acknowledge that the presented example applications is not an exhaustive list. Further analyses are the scope of current research, and we hope to inspire others to explore additional applications.@en