A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications assimilation ecology restricted highly technical requirements such as model-dependent coding. To alleviate this burden, we developed a model-independent (MIDA) module. MIDA works in three steps including preparation, execution assimilation, and visualization. The first step prepares prior ranges parameter values, defined number iterations, directory paths access files observations models. calibrates values best fit the estimates posterior distributions. final automatically visualizes calibration performance is independent, modelers use for efficient simple interactive way without modification their original We applied four types ecological models: linked ecosystem carbon (DALEC) model, surrogate-based energy exascale earth model: land component (ELM), nine phenological models stand-alone biome strategy simulator (BiomeE). indicate that effectively solve problems different Additionally, easy implementation feature breaks barrier data–model fusion ecology. facilitates various into uncertainty reduction modeling forecasting.