Ichio Asanuma

TL;DR: The third primary production algorithm round robin (PPARR3) as discussed by the authors compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models.

TL;DR: The authors compare satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) to a tropical Pacific primary productivity (PP) database consisting of ∼ 1000 14C measurements spanning more than a decade (1983-1996).

TL;DR: The authors assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ 14 C measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast and coastal Northeast.

TL;DR: The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades as discussed by the authors.

TL;DR: In this paper, the authors investigated 32 net primary productivity (NPP) models by assessing skills to reproduce inte-grated NPP in the Arctic Ocean and found that most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias.