TY - JOUR
T1 - Towards a multi-platform assimilative system for North Sea biogeochemistry
AU - Skákala, Jozef
AU - Ford, David
AU - Bruggeman, Jorn
AU - Hull, Tom
AU - Kaiser, Jan
AU - King, Robert R.
AU - Loveday, Benjamin
AU - Palmer, Matthew R.
AU - Smyth, Tim
AU - Williams, Charlotte A. J.
AU - Ciavatta, Stefano
PY - 2021/4
Y1 - 2021/4
N2 - Oceanography has entered an era of new observing platforms, such as biogeochemical-Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centers will use multi-platform assimilation to integrate those valuable data into ecosystem reanalysis and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation (DA) and introduce multi-platform DA in a preoperational model of the NWE Shelf sea ecosystem. We test the impact of the different multi-platform system components (glider vs. satellite, physical vs. biogeochemical) on the simulated biogeochemical variables. To characterize the model performance, we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical DA, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.
AB - Oceanography has entered an era of new observing platforms, such as biogeochemical-Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centers will use multi-platform assimilation to integrate those valuable data into ecosystem reanalysis and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation (DA) and introduce multi-platform DA in a preoperational model of the NWE Shelf sea ecosystem. We test the impact of the different multi-platform system components (glider vs. satellite, physical vs. biogeochemical) on the simulated biogeochemical variables. To characterize the model performance, we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical DA, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.
KW - Shelf seas
KW - glider observations
KW - marine ecosystems
KW - multi-platform data assimilation
UR - http://www.scopus.com/inward/record.url?scp=85105020048&partnerID=8YFLogxK
U2 - 10.1029/2020JC016649
DO - 10.1029/2020JC016649
M3 - Article
VL - 126
JO - Journal of Geophysical Research - Oceans
JF - Journal of Geophysical Research - Oceans
SN - 2169-9275
IS - 4
M1 - e2020JC016649
ER -