Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling

Abstract

Abstract. Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

Significant stream chemistry response to temperature variations in a high-elevation mountain watershed

“…The availability of longterm, consistent observations that reflect the functioning of earth's surface (e.g., water chemistry), however, remains to be the bottleneck for understanding earth system response to environmental perturbations. Large collaborative research networks have galvanized to collect consistent data for cross-site comparison 61,62 . Most of the available data however are still in easy-to-access places.…”

Hillslope Hydrology in Global Change Research and Earth System Modeling

“…Over the past six decades or so, hillslope and catchment research has produced prodigious field observations, theories, and models, at individual research sites and across organized research networks including the long‐term ecological research network and the US Department of Agriculture Agricultural Research Service and Forest Service experimental watersheds (e.g., Stringer et al, ). The nascent international network of Critical Zone Observatories (CZOs) is laying the foundation for cross‐site syntheses (e.g., Baatz et al, ; Brantley, McDowell, et al, ; Paola et al, ), making possible a global assessment of the most salient structures and functions of hillslope processes that may matter to large‐scale fluxes in ESMs. Thus, catchment and CZ scientists, as a community, can offer deep insights into the lay of the land, and we hope to tap into their collective wisdom so that we can identify the most critical processes to implement in ESMs.…”

Representing the function and sensitivity of coastal interfaces in Earth system models

“…Large scale environmental network programs exist that inherently encompass such heterogeneity of observations in coastal ecosystems (e.g., in the USA, the Long Term Ecological Research Network (LTER), the National Ecological Observatory Network (NEON), the National Oceanic and Atmospheric Administration's Sentinel Site Program, and the Coastal Carbon Research Coordination Network), and such efforts should be further leveraged and expanded to address data needs for model incorporations as many areas of the world remain unmonitored 106,108 . Efforts are needed to increase synergy among existing observational data streams to cohesively span larger spatiotemporal scales, allowing for predictive understanding 108 . Synthesis of observational data is one way to address continental-scale patterns and differences among ecoregions 109 , and can further identify controlling factors to include into ESM process representation 110 .…”