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Poster TitleEvaluating the E3SM land model using litter decomposition observations
AuthorsDaniel RicciutoXiaojuan YangPeter Thornton
Session TypeE3SM session
Session IDE2
Submission Typeposter
GroupLand, BGC
ExperimentBGC
Poster Link




Abstract

Litter decomposition plays a critically important role in carbon and nutrient cycling within terrestrial ecosystems.  Rates of litter decomposition are highly sensitive to soil temperature and moisture, litter quality and nutrient availability.  As the climate changes, all of these environmental factors are likely to respond and affect the rates of litter and soil organic matter (SOM) decomposition.  This will impact both heterotrophic respiration, a large source of COto the atmosphere, and vegetation productivity through nutrient feedbacks. Developing a predictive understanding of these processes is critical to determining terrestrial carbon-climate feedbacks that play a key role in the evolution of the climate system.  Our capability to predict future climate change depends to a large extent on a well-constrained representation of soil carbon dynamics in ESMs.  Here we evaluate two decomposition schemes - converging trophic cascade (CTC) and Century - in the E3SM Land Model (ELM) using data from the long-term intersite decomposition experiment team (LIDET).  For the evaluation against LIDET, we develop a new functional unit testing framework to evaluate the decomposition schemes at 21 unique sites for 6 leaf litter types.  The functional unit test evaluates the decomposition submodel with boundary conditions derived from full ELM simulations at the same sites, including seasonal variability in nitrogen limitation and environmental scalars (temperature, moisture, O2), in order to represent LIDET experiment in a realistic way.  We find overall similar performance of the two decomposition schemes despite very different base litter turnover times, indicating that nutrient limitation is the primary limiting factor for litter decomposition at most sites. The proper design of model experiments is crucial to model evaluation using data from field experiments such as LIDET.