Item talk:Q266505
From geokb
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"name": "Characterizing performance of freshwater wetland methane models across time scales at FLUXNET-CH4 sites using wavelet analyses",
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"value": "10.1029/2022JG007259",
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"name": "JGR Biogeosciences",
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"datePublished": "2023",
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"abstract": "Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4\u00a0fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15\u00a0days); (b) most of the models can capture the CH4\u00a0variability at monthly and seasonal time scales (>32\u00a0days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5\u00a0days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4\u00a0production). Our evaluation suggests the need to accurately replicate FCH4\u00a0variability, especially at short time scales, in future wetland CH4\u00a0model developments.",
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