Improved state estimations of lower trophic ecosystems in the global ocean based on a Green’s function approach

Toyoda, Takahiro; Awaji, Toshiyuki; Masuda, Shuhei; Sugiura, Nozomi; Igarashi, Hiromichi; Sasaki, Yuta; Hiyoshi, Yoshihisa; Ishikawa, Yoichi; Saitoh, Sei–Ichi; Yoon, Seok–Jin; In, Teiji; Kishi, Michio J.

doi:10.1016/j.pocean.2013.08.008

Cited by 23 publications

(22 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Applying empirical efficiencies and/or considering the electric charges due to radioactive decay will certainly improve the underestimation of 137 Cs deposition. There could be another solution to improve deposition modeling: a statistical approach. As performed by Toyoda et al (), optimizing the four types of deposition efficiencies using a Greens' function approach toward the observed 137 Cs deposition with the current sets of the meteorological ensembles can help identify the cause of underestimation in the deposition modeling of 137 Cs. Discrepancy in the deposition schemes can be assessed by using the Cs/Xe ratio. Xe is a noble gas so the Cs/Xe ratio in atmospheric concentrations only changes due to dry and wet removal of Cs during the transport, except radioactive decay.…”

Section: Discussionmentioning

confidence: 99%

Deposition and Dispersion of Radio‐Cesium Released Due to the Fukushima Nuclear Accident: Sensitivity to Meteorological Models and Physical Modules

et al. 2019

View full text Add to dashboard Cite

To assess the uncertainty of meteorological simulations in the transport and deposition of radio‐Cs release associated with the Fukushima Daiichi Nuclear Power Station accident in Japan, a multiple meteorological model and module ensemble analysis with a single chemical transport model (CTM) was conducted. Although several multimodel ensemble studies have previously been performed, the current type (i.e., one CTM with several meteorological fields) was applied for the first time and represents a useful way to evaluate the uncertainty of each component of CTM. The current analysis concluded that the underestimation of the deposition efficiency of CTM was the reason for the underestimation of simulated radio‐Cs deposition, whereas the simulated dispersion and precipitation and estimated source term were all reasonable: all of the simulations underestimated the deposition amount, whereas some underestimated but others overestimated the simulated precipitation and radio‐Cs concentrations. The CTM simulation performed using the meteorological ensemble mean field was successful in reducing variance, and they gave reasonable results. The simulated deposition using the meteorological ensemble was better than others because the ensemble mean enlarged the light precipitation areas and because the land contamination was mainly caused by light precipitation. The current ensemble study indicated that in‐cloud scavenging was the most dominant mechanism of radio‐Cs deposition, followed by dry deposition and fog deposition over the entire land area. In some deposition regions, fog deposition was dominant, exceeding 80%, depending on the simulations. The simulated concentrations and depositions varied by more than twofold, depending on the selection of the meteorological field.

show abstract

Section: Discussionmentioning

confidence: 99%

Deposition and Dispersion of Radio‐Cesium Released Due to the Fukushima Nuclear Accident: Sensitivity to Meteorological Models and Physical Modules

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Kuroda and Kishi, 2004;Fiechter et al, 2013;Toyoda et al, 2013;Xiao and Friedrichs, 2014). Shigemitsu et al (2012) applied a unique assimilative approach to an LTL marine ecosystem model, using a micro-genetic algorithm (µ-GA) (Krishnakumar, 1990).…”

Section: Introductionmentioning

confidence: 99%

“…1b) using the following province map instead of maps divided by latitude-longitude lines as in previous studies (e.g. Longhurst, 1995;Toyoda et al, 2013). The province map is based on the dominant phyto-374 Y.…”

Section: Introductionmentioning

confidence: 99%

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

et al. 2018

View full text Add to dashboard Cite

Abstract. Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a onedimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

show abstract

“…Toyoda et al (2013) take an important step in that direction by describing a Green's function optimization approach that improves simulations of seasonal and interannual variability in the lower trophic levels using NEMURO (Ecosystem Model for Understanding Regional Oceanography, Kishi et al, 2007). Although impacts of global warming are still poorly defined in terms of detailed impacts on circulation and stratification, such approaches provide some hope that relevant biology, including parameterizations for organisms/strategies that may be selected for by enhanced stratification, can be implemented into models to evaluate their potential impacts on future ocean scenarios.…”

Section: Prefacementioning

confidence: 99%

Introduction: Sensitivities of marine food webs and biogeochemical cycles to enhanced ocean stratification

Landry¹,

Kishi²

2013

Progress in Oceanography

View full text Add to dashboard Cite

Improved state estimations of lower trophic ecosystems in the global ocean based on a Green’s function approach

Cited by 23 publications

References 60 publications

Deposition and Dispersion of Radio‐Cesium Released Due to the Fukushima Nuclear Accident: Sensitivity to Meteorological Models and Physical Modules

Deposition and Dispersion of Radio‐Cesium Released Due to the Fukushima Nuclear Accident: Sensitivity to Meteorological Models and Physical Modules

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

Introduction: Sensitivities of marine food webs and biogeochemical cycles to enhanced ocean stratification

Contact Info

Product

Resources

About