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  • Copernicus  (2)
  • 2020-2022  (2)
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  • 1
    Publication Date: 2021-08-20
    Description: Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
    Publication Date: 2020-12-09
    Description: Multiple lines of evidence have demonstrated the persistence of global land carbon (C) sink during the past several decades. However, both annual net ecosystem productivity (NEP) and its inter-annual variation (IAVNEP) keep varying over space. Thus, identifying local indicators for the spatially varying NEP and IAVNEP is critical for locating the major and sustainable C sinks on land. Here, based on daily NEP observations from FLUXNET sites and large-scale estimates from an atmospheric-inversion product, we found a robust logarithmic correlation between annual NEP and seasonal carbon uptake–release ratio (i.e. U ∕ R). The cross-site variation in mean annual NEP could be logarithmically indicated by U ∕ R, while the spatial distribution of IAVNEP was associated with the slope (i.e. β) of the logarithmic correlation between annual NEP and U ∕ R. Among biomes, for example, forests and croplands had the largest U ∕ R ratio (1.06 ± 0.83) and β (473 ± 112 g C m−2 yr−1), indicating the highest NEP and IAVNEP in forests and croplands, respectively. We further showed that these two simple indicators could directly infer the spatial variations in NEP and IAVNEP in global gridded NEP products. Overall, this study provides two simple local indicators for the intricate spatial variations in the strength and stability of land C sinks. These indicators could be helpful for locating the persistent terrestrial C sinks and provide valuable constraints for improving the simulation of land–atmospheric C exchanges.
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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