Ryohei Yamaguchi
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ryamaguchi.bsky.social
Ryohei Yamaguchi
@ryamaguchi.bsky.social
440 followers 130 following 6 posts
Sea-going oceanographer @JAMSTEC ⚽️
Ocean carbon cycle & climate change

https://scholar.google.co.jp/citations?user=HEtB4eMAAAAJ&hl=en&authuser=1
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ryamaguchi.bsky.social
Thank you for adding me to the BGC pack! I was surprised by the sudden increase in followers in the past few days 😂 i would appreciate if you could add me to the physical oceanography pack too! Thank you!
November 13, 2024 at 10:55 AM
Reposted by Ryohei Yamaguchi
jens-d-mueller.bsky.social
[6/10]

Yasunaka et al. unravelled the exceptional role of climate change for the CO₂ sink in the Arctic Ocean. Here, the accelerated CO₂ uptake is primarily caused by sea ice loss, whereas rising atmospheric CO₂ dominates the trends in all other #RECCAP2 regions.

doi.org/10.1029/2023...
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Trend over 1985−2018 for ensemble mean CO2 flux, pCO2w, and SIC from the pCO2 products, the ocean biogeochemical hindcast and data assimilation models, and the atmospheric inversions. Negative values indicate increasing CO2 flux into the ocean in panels (a) and (b). Darker hatched areas represent values in grids where less than two third of the estimates show the same sign of the trend. Ensemble means are calculated across the estimates, which cover the full period of 1985–2018. Time series of the decomposition of the net CO2 flux (Fnet; black line) into the natural steady-state flux (Fnat,ss; aqua ribbon), the CO2 effect (Fant,ss; yellow ribbon), and the climate effect (Fnat,ns + Fant,ns; blue hatch and ribbon). Negative values (or widths of the ribbons) indicate the CO2 influx to the ocean, and positive values (or widths of the hatches) indicate CO2 outflux from the ocean.
November 4, 2024 at 12:25 PM
Reposted by Ryohei Yamaguchi
jens-d-mueller.bsky.social
[4/10]

Pérez et al. assessed the important CO₂ sink in the Atlantic Ocean. A major fraction of this CO₂ uptake is realised in the subpolar North Atlantic, where models and observation-based estimates still differ substantially with respect to trends and seasonality.

doi.org/10.1029/2023...
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(a) RECCAP2 biomes in the Atlantic including the Mediterranean Sea. (b) Latitudinal variation of CO2 flux densities displayed for the ensemble mean of the pCO2 products, the GOBM ensemble mean, the UOEX data product that corrects for skin temperature effects, the regional hindcast model (ROBM), and the inverse model OCIMv2021. Average CO2 flux density from 1985 to 2018, illustrated on maps for the ensemble means of (c) nine pCO2 products and (d) 11 GOBMs. Negative values indicate oceanic uptake of CO2. The biomes are the seasonally stratified North Atlantic subpolar gyre (NA SPSS), the seasonally and permanently stratified regions of the North Atlantic subtropical gyre (NA STSS and NA STPS), the Atlantic equatorial upwelling region (AEQU), the seasonally stratified South Atlantic subtropical gyre (SA STPS), and the Mediterranean Sea (MED). Note that the GOBMs do not adequately represent the RCO (Riverine CO2 outgassing) fluxes and thus we did not adjust those with other available estimates. Seasonal cycle of the sea-air CO2-fluxes for each Atlantic biome as estimated by pCO2 products (blue) and GOBMs (green), both shown as the ensemble mean (thick lines) and 1σ spread (shadings) (1985–2018 average). Additional lines represent UOEX, OCIM and one ROBM. OCIM is an abiotic model and thus does not include the effect of the seasonality of net community production.
October 31, 2024 at 2:50 PM
Reposted by Ryohei Yamaguchi
jens-d-mueller.bsky.social
[3/10]

Rodgers et al. found that the seasonal amplitude of air-sea CO₂ fluxes increased over the past decades. We also show that the surface ocean DIC seasonality in biogeochemical ocean models is lower than in observation-based products. Something to improve…

doi.org/10.1029/2023...
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Central panel showing biomes used for this study: North Atlantic subpolar seasonally stratified (NA-SPSS), North Pacific subpolar seasonally stratified (NP-SPSS), Northern Hemisphere subtropical seasonally stratified (NH-STSS), Northern Hemisphere subtropical permanently stratified (NH-STPS), Southern Hemisphere subtropical permanently stratified (SH-STPS), and Southern Hemisphere seasonally stratified, incorporating the subpolar and subtropical components (SH-SS). Surrounding panels show time series plots of biome-integrated sea-air CO2 fluxes (annual maximum and minimum values irrespective of the month of occurrence). pCO2 products (blue) and GOBMs (green) are shown for both the ensemble mean (bold) and for one standard deviation (shaded). Positive (negative) values indicate outgassing (ingassing) of CO2. In each panel, winter is designated by W, and summer by S, in order to distinguish the seasonal phasing between the subtropical and subpolar/Southern Ocean biomes. Seasonal evolution of the relationship between MLD and anomalies of nDIC over the six biomes for a climatology over 2014–2018 for observation-based products (blue) and GOBMs (green). The horizontal axis represents MLD, and the vertical axis represents seasonal anomalies in nDIC concentrations relative to the annual mean. The stars indicate January, and the subsequent months of March, June, September, and December are marked with 3, 6, 9, and 12, respectively. The pCO2 products that include DIC and TA, namely JMAMLR, OceanSODA-ETHZ, and CMEMS-LSCE-FFNN, are considered along with the full suite of 11 GOBMs. Observationally based MLDs have been derived for this study from the gridded Argo-derived temperature and salinity product of Roemmich and Gilson (2009) using a density threshold criterion (Holte & Talley, 2009) using the years 2014–2018, for consistency with the nDIC fields.
October 30, 2024 at 12:41 PM
ryamaguchi.bsky.social
Cool!!! I would like to join if it is held at the next OSM.
October 30, 2024 at 2:02 AM
Reposted by Ryohei Yamaguchi
jens-d-mueller.bsky.social
[2/10]

Hauck et al. found that the Southern Ocean takes up 50% less CO₂ than reported in RECCAP1!

Still, most of the global CO₂ uptake occurs here, calling for a better understanding of trends, seasonality and interior transport of anthropogenic CO₂.

doi.org/10.1029/2023...
@jhauck.bsky.social
Temporal average of the Southern Ocean CO2 net flux (FCO2). A positive flux denotes outgassing from ocean to atmosphere. The temporal average is calculated over the period 1985 to 2018 for the global ocean biogeochemistry models (GOBMs) and pCO2-products. (a) The green and blue bar plots show the ensemble mean of the GOBMs and pCO2-based data-products, and open circles indicate the individual GOBMs and pCO2-products. The ensemble standard deviation (1σ) is shown by the error bars. The river flux adjustment added to the GOBMs is small (0.04 PgC yr−1). (b) Zonal mean flux density of the different data sets. Thick green and blue lines show the ensemble means, and thin green and blue lines show the individual GOBMs and pCO2-products. Approximate boundaries for biomes are marked with black points on the x-axis. (c, d) Maps of spatial distribution of net CO2 flux for ensemble means of GOBMs, and pCO2-products. Zonal integrals of ΔCant yearly accumulation rate from 1994 to 2007 and of air-sea Cant fluxes (positive downwards) averaged between 1994 and 2007 for (a, d) eMLR(C*), (b, e) OCIM-v2021, and (c, f) global ocean biogeochemistry models (GOBMs). (a–c) (black line) ΔCant column inventory (0–3,000 m) and (gray line) air-sea Cant fluxes; for the GOBMs, the distinction is made between “GOBMs high” (full lines) and “GOBMs low” (dashed lines). (g–i) Anomalies of ΔCant accumulation rates in (g) OCIM-v2021 with respect to eMLR(C*), (h) GOBMs with respect to eMLR(C*), and (i) GOBMs with respect to OCIM-v2021. In all sections, contours show mean potential density (with a 0.03 kg m−3 spacing) referenced to the surface in World Ocean Atlas 2018 (Boyer et al., 2018), where thick lines indicate the 1,026.9 and 1,027.5 kg m−3 isopycnals.
October 29, 2024 at 3:22 PM
Reposted by Ryohei Yamaguchi
jens-d-mueller.bsky.social
[1/10]

DeVries et al. assessed the Global Ocean Carbon Sink and found that models and fCO2 products agree on the long-term mean uptake of CO2, but recent trends differ by almost a factor of 2, indicating a need to better understand the impact of climate variability.

doi.org/10.1029/2023...

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Global mean sea-air CO2 flux for 1985–2018 for the (a) mean of the global ocean biogeochemical models (GOBMs) (simulation A), and (b) mean of the core pCO2 products (excluding the UOEX and Takahashi update products). The global average sea-air CO2 flux is given in the title of each figure. Zonally integrated sea-air CO2 fluxes are shown in the right-hand panels in each figure, with shading representing the ensemble standard deviation. (c) The difference between the sea-air CO2 flux in the pCO2 products and the GOBMs. Stippling indicates regions where the mean sea-air CO2 flux difference is greater than the cross-ensemble standard deviation. Zonally integrated differences in sea-air CO2 fluxes are shown in the right-hand panel, with shading representing the cross-ensemble standard deviation. (a) Components of the contemporary net sea-air CO2 flux in global ocean biogeochemical models (GOBMs), using simulations A–D to partition fluxes into the anthropogenic CO2-driven flux (Fant,CO2), the climate-driven anthropogenic CO2 flux (Fant, climate), and the climate-driven natural CO2 flux (Fnat, climate). Solid curve is the ensemble mean and shading is the ensemble standard deviation. An estimate of Fant,CO2 from the ocean circulation inverse model (OCIM) is also given by the red dashed curve. (b) The climate-driven sea-air CO2 flux (Fclimate) in the GOBMs, compared with the sum of Fclimate and the net land-sea carbon flux (Fland-sea,ss) in the pCO2 products. Dark curve is the multi-product mean and light shading is the cross-ensemble standard deviation. (c) Summary statistics for Fant,CO2 from the GOBMs (dark red) and the OCIM (light red), Fclimate from the GOBMs (light blue) and Fclimate + Fland-sea,ss from the pCO2 products (dark blue). Bar heights represent the mean estimates for the period 1985–2018 and error bars the respective ensemble standard deviation. Numbers above each graph represent the trend over 1985–2018 (upward trending line, top), with superscripts and subscripts the trend for 2001–2018 and 1985–2000, respectively; the magnitude of the interannual variability (IAV, squiggly line, middle) and the 5-years smoothed IAV (smooth squiggle, bottom).
October 28, 2024 at 1:03 PM