Ensemble modelling is combining the outputs of multiple models that are all working on the same question. This allows researchers to analyze the different vulnerabilities of each individual model, and weigh the impact of particular inputs. Aggregating all the outputs and then using the outputs with the highest frequency across the models minimizes the error in the projection.
Ensemble modelling is generally difficult because of the variety of possible inputs and outputs, which makes it challenging to run different models on the same data and compare results. The FishMIP protocols standardize input variables, as well as the names of files and data stores. The inputs are collected from simplified fishing scenarios, models of the climate and how much greenhouse gas will be in the atmosphere. These standardized inputs and scenarios can then be used to drive multiple ecosystem models, and the outputs are then combined through an ensemble modelling approach. The FishMIP standardizing protocol allow for these diverse inputs to be collated, thus minimizing projection error.
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