MERCATOR OCEAN JOURNA: 
SEPTEMBER 2021 
1.4 Biogeochemistry timeseries 
Since 2015, the catalogue of global biogeochemical multi- 
year products has been greatly enriched: 
1 From a 19-years (1998-2016) span, the 
biogeochemical multi-year timeseries BIORYS 
(based on the NEMO-PISCES model, capturing the 
first trophic levels) now covers almost 30 years 
(1993-2020) with high-frequency daily outputs, 
In 2019, a new primary production together with 
the zooplankton and the micronekton at 1/4° were 
produced and delivered. These essential ecosystem 
varlables are based on the Lower and Mid-Trophic 
Levels (LMTL) module of the SEAPODYM mode: 
(Lehodey et al, 2015) and have been developec 
during GREENUP service evolution CMEMS project, 
3.In 2021, a major upgrade of the system was 
implemented witha 1/12° resolution product covering 
1998 to 2020. Figure 3 illustrates this improvement 
with small scale features in the zooplankton fields in 
the north Atlantic. A better match to the horizontal 
resolution of the global physical system (GLO12v3, 
section 2.1) is observed and especially the mesoscale 
features, meanders and eddies as illustrated in the 
Gulf Stream area. 
mass concentration of zooplankton expressed as wet weicht in sea water 
biomass surface concentration g/m 2 
1.3 
Yo 
180 
260 
SM 
‚gure 3: Sample of a 1/12° daily north Atlantic Ocean simulation of the biomass concentration of zooplankton with SEAPODYM-LMTL. 
1.5 Multi system ensemble reanalysis 
As reviewed by Storto (20196)(a), global ocean model 
reanalyseis have the capacity to capture the ocean 
variability and trends accurately, and are used as oceanic 
initialconditions by seasonal forecasting systems. However, 
biases and errors appear where and when observations are 
sparse. For instance, errors which appear in the southern 
oceans or on the continental shelves may propagate, and 
biases tend to accumulate at depth. In this context, the 
Slobal Reanalysis Ensemble Product (GREP) (Storto et al, 
2019) was developed, based on four reanalyses: 
- GLORYS2V4 (Garric et al., 2018), 
GLOSEA5v13 (MacLachlan et al 2015), 
C-GLORS (Storto et al, 2016), 
- ORASS5 (Zuo et al, 2019). 
Those are comparable to global NEMO ORCA025 
configurations but differ by their data assimilation