These are some great project ideas, which I think are quite useful for those of us who are working on the ocean biogeochemistry fields of the various CMIP6 models. Here are some follow-up questions I think are worth considering, under two broad categories:
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In addition to, as Yassir suggests, comparing simulated ecosystem drivers to available observations, can we also identify the drivers of the biases themselves? For example, are biases in NPP and nutrients related to biases in physical properties (temperature, mixed layer depth), parameterization of processes such as growth rate and remineralization, or structural uncertainty? Can we determine causal relationships between biases of different biogeochemical properties which are interactive? For example, biases in surface nutrient fields will lead to biases in NPP, but NPP, along with advection and mixing, affects the nutrient fields themselves. And how do the relationships between biases change in different oceanic environments? These questions are perhaps even more important for ocean carbon uptake, which is affected by NPP but also wind speed, T/S, and the air-sea pCO2 gradient.
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What does the seasonal cycle of productivity and carbon uptake look like across the CMIP6 models. Can we identify ocean biogeochemical provinces with unique seasonal cycles (e.g., Henson et al., 2010;2013, Biogeosciences)? In each of these regions, what are the driving factors of the seasonal cycles in uptake and productivity? How and what differences are there in the predicted changes of the seasonal cycle (changes in amplitude + phase) of the CMIP6 models? Moreover, alluding to point (3) of Yassir, are changes in annual mean NPP systematic across the seasonal cycle, or are there seasonal variations in the sign and amplitude of the long-term changes?