Data assimilation in a coupled physical-biogeochemical model of the California Current System using an incremental lognormal 4-dimensional variational approach: Part 2—Joint physical and biological data assimilation twin experiments

2016 ◽  
Vol 106 ◽  
pp. 146-158 ◽  
Author(s):  
Hajoon Song ◽  
Christopher A. Edwards ◽  
Andrew M. Moore ◽  
Jerome Fiechter
Keyword(s):  
Data Assimilation ◽  
Variational Approach ◽  
Current System ◽  
California Current ◽  
Biological Data ◽  
Biogeochemical Model ◽  
California Current System

Data assimilation of physical and chlorophyll a observations in the California Current System using two biogeochemical models

2017 ◽  
Vol 109 ◽  
pp. 55-71 ◽  
Author(s):  
Jann Paul Mattern ◽  
Hajoon Song ◽  
Christopher A. Edwards ◽  
Andrew M. Moore ◽  
Jerome Fiechter
Keyword(s):  
Data Assimilation ◽  
Chlorophyll A ◽  
Current System ◽  
California Current ◽  
California Current System ◽  
Biogeochemical Models

Application of 4D-Variational data assimilation to the California Current System

2009 ◽  
Vol 48 (1-3) ◽  
pp. 69-92 ◽  
Author(s):  
G. Broquet ◽  
C.A. Edwards ◽  
A.M. Moore ◽  
B.S. Powell ◽  
M. Veneziani ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Current System ◽  
California Current ◽  
Variational Data Assimilation ◽  
California Current System

scholarly journals Weak constraint four-dimensional variational data assimilation in a model of the California Current System

2016 ◽  
Vol 2 (2) ◽  
pp. 171-192 ◽  
Author(s):  
William J. Crawford ◽  
Polly J. Smith ◽  
Ralph F. Milliff ◽  
Jerome Fiechter ◽  
Christopher K. Wikle ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Ocean Circulation ◽  
Hierarchical Modeling ◽  
Current System ◽  
California Current ◽  
Model Errors ◽  
Strong Constraint ◽  
California Current System ◽  
Twin Model ◽  
Error Covariance

Abstract. A new approach is explored for computing estimates of the error covariance associated with the intrinsic errors of a numerical forecast model in regions characterized by upwelling and downwelling. The approach used is based on a combination of strong constraint data assimilation, twin model experiments, linear inverse modeling, and Bayesian hierarchical modeling. The resulting model error covariance estimates Q are applied to a model of the California Current System using weak constraint four-dimensional variational (4D-Var) data assimilation to compute estimates of the ocean circulation. The results of this study show that the estimates of Q derived following our approach lead to demonstrable improvements in the model circulation estimates and isolate regions where model errors are likely to be important and that have been independently identified in the same model in previously published work.

scholarly journals A Dynamically Downscaled Ensemble of Future Projections for the California Current System

2021 ◽  
Vol 8 ◽  
Author(s):  
Mercedes Pozo Buil ◽  
Michael G. Jacox ◽  
Jerome Fiechter ◽  
Michael A. Alexander ◽  
Steven J. Bograd ◽  
...  
Keyword(s):  
Current System ◽  
California Current ◽  
Nitrate Content ◽  
Biogeochemical Model ◽  
Climate Projections ◽  
Surface Mixed Layer ◽  
California Current System ◽  
The Future ◽  
The Mean ◽  
Source Waters

Given the ecological and economic importance of eastern boundary upwelling systems like the California Current System (CCS), their evolution under climate change is of considerable interest for resource management. However, the spatial resolution of global earth system models (ESMs) is typically too coarse to properly resolve coastal winds and upwelling dynamics that are key to structuring these ecosystems. Here we use a high-resolution (0.1°) regional ocean circulation model coupled with a biogeochemical model to dynamically downscale ESMs and produce climate projections for the CCS under the high emission scenario, Representative Concentration Pathway 8.5. To capture model uncertainty in the projections, we downscale three ESMs: GFDL-ESM2M, HadGEM2-ES, and IPSL-CM5A-MR, which span the CMIP5 range for future changes in both the mean and variance of physical and biogeochemical CCS properties. The forcing of the regional ocean model is constructed with a “time-varying delta” method, which removes the mean bias of the ESM forcing and resolves the full transient ocean response from 1980 to 2100. We found that all models agree in the direction of the future change in offshore waters: an intensification of upwelling favorable winds in the northern CCS, an overall surface warming, and an enrichment of nitrate and corresponding decrease in dissolved oxygen below the surface mixed layer. However, differences in projections of these properties arise in the coastal region, producing different responses of the future biogeochemical variables. Two of the models display an increase of surface chlorophyll in the northern CCS, consistent with a combination of higher nitrate content in source waters and an intensification of upwelling favorable winds. All three models display a decrease of chlorophyll in the southern CCS, which appears to be driven by decreased upwelling favorable winds and enhanced stratification, and, for the HadGEM2-ES forced run, decreased nitrate content in upwelling source waters in nearshore regions. While trends in the downscaled models reflect those in the ESMs that force them, the ESM and downscaled solutions differ more for biogeochemical than for physical variables.

scholarly journals The Physical Structure and Behavior of the California Current System

2020 ◽  
Author(s):  
Lionel Renault ◽  
James C. McWilliams ◽  
Alexandre Jousse ◽  
Curtis Deutsch ◽  
Hartmut Frenzel ◽  
...  
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Current System ◽  
Mesoscale Eddy ◽  
California Current ◽  
Open Boundary ◽  
Biogeochemical Model ◽  
California Current System ◽  
Synoptic Wind ◽  
The Impact

AbstractThis paper is the first of two that present a 16-year reanalysis solution from a coupled physical and biogeochemical model of the California Current System (CCS) along the U. S. West Coast and validate the solution with respect to mean and seasonal fields and, to a lesser degree, eddy variability. Its companion paper is Deutsch et al. (2019a). The intent is to construct and demonstrate a modeling tool that will be used for mechanistic explanations, attributive causal assessments, and forecasts of future evolution for circulation and biogeochemistry, with particular attention to the increasing oceanic stratification, deoxygenation, and acidification. A well-resolved mesoscale (dx = 4 km) simulation of the CCS circulation is made with the Regional Oceanic Modeling System over a reanalysis period of 16 years from 1995 to 2010. The oceanic solution is forced by a high-resolution (dx = 6 km) regional configuration of the Weather and Research Forecast (WRF) atmospheric model. Both of these high-resolution regional oceanic and atmospheric simulations are forced by lateral open boundary conditions taken from larger-domain, coarser-resolution parent simulations that themselves have boundary conditions from the Mercator and Climate Forecast System reanalyses, respectively. We first show good agreement between the simulated atmospheric forcing of the ocean and satellite observations for the spatial patterns and seasonal variability of the cloud cover and for the surface fluxes of momentum, heat, and freshwater. The simulated oceanic physical fields are then evaluated with satellite and in situ observations. The simulation reproduces the main structure of the climatological upwelling front and cross-shore isopycnal slopes, the mean current patterns (including the California Undercurrent), and the seasonal and interannual variability. It also shows agreement between the mesoscale eddy activity and the wind-work energy exchange between the ocean and atmosphere modulated by influences of surface current on surface stress. Finally, the impact of using a high frequency wind forcing is assessed for the importance of synoptic wind variability to realistically represent oceanic mesoscale activity and ageostrophic inertial currents.

scholarly journals Biogeochemical variability in the California Current System

2020 ◽  
Author(s):  
Curtis Deutsch ◽  
Hartmut Frenzel ◽  
James C. McWilliams ◽  
Lionel Renault ◽  
Faycal Kessouri ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Net Primary Productivity ◽  
Current System ◽  
California Current ◽  
Light Limitation ◽  
Biogeochemical Model ◽  
Past Century ◽  
Physical Analysis ◽  
California Current System ◽  
Mean State

AbstractThe biological productivity and diversity of the California Current System (CCS) is at the leading edge of major emerging climate trends, including hypoxia and acidification. We present results from a hindcast simulation (reanalysis) of an eddy-resolving oceanic physical-biogeochemical model of the CCS, to characterize its mean state and its patterns and drivers of variability in marine biogeochemical and ecosystem processes from 1995-2010. This is a companion paper to a physical analysis in Renault et al. (2019). The model reproduces long-term mean distributions of key ecosystem metrics, including surface nutrients and productivity and subsurface O2 and carbonate undersaturation. The spatial patterns of Net Primary Productivity (NPP) are broadly consistent with measured and remotely sensed rates, and they reflect a predominant limitation by nitrogen, with seasonal and episodic limitation by Fe nearshore in the central CCS, and in the open ocean northern CCS. The vertical distribution of NPP is governed by the trade-off between nutrient and light limitation, a balance that reproduces and explains the observed spatial variations in the depth of the deep Chl maximum. The seasonal to interannual variability of biogeochemical properties and rates is also well captured by model simulations. Because of the prevailing nutrient limitation, fluctuations in the depth of the pycnocline and associated nutricline are the leading single factor explaining interannual variability in the interior biogeochemical state, and the relationships between density and biogeochemical rates and tracers are consistent between model and observations. The magnitude and relationship between density structure and biogeochemical processes is illustrated by the 1997-98 El Niño event, which faithfully reproduces the single largest deviation from the mean state in the simulated period. A slower decadal shoaling of the pycnocline also accounts for the concomitant trends in hypoxic and corrosive conditions on the shelf. The resulting variability is key to understanding the vulnerability of marine species to oceanic change, and to the detection of such changes, soon projected to exceed the range of conditions in the past century.

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