Weiwei Fu

Dr. Weiwei Fu

Department of Earth System Sciences, University of California, 240E, Rowland Hall, Irvine, CA 92697, USA
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Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 March 2018 in Science
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Journal Article
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JMJ. Keith Moore
J. Keith Moore
Weiwei FuWeiwei Fu
Weiwei Fu
FPFrancois Primeau
Francois Primeau
GBGregory L Britten
Gregory L Britten
KLKeith Lindsay
Keith Lindsay
JRJames T. Randerson
James T. Randerson
Starving ocean productivity: Projected increases in greenhouse gas emissions could suppress marine biological productivity for a thousand years or more. As the climate warms, westerly winds in the Southern Hemisphere will strengthen and shift poleward, surface waters will warm, and sea ice will disappear. Moore et al. suggest that one effect of these changes will be a dramatic decrease in marine biological productivity (see the Perspective by Laufkötter and Gruber). This decrease will result from a global-scale redistribution of nutrients, with a net transfer to the deep ocean. By 2300, this could drive declines in fisheries yields by more than 20% globally and by nearly 60% in the North Atlantic. Science , this issue p. 1139 ; see also p. 1103

16 September 2016 in Biogeosciences
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Weiwei FuWeiwei Fu
Weiwei Fu
JRJames T. Randerson
James T. Randerson
JMJ. Keith Moore
J. Keith Moore
We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16 % and EP by 7–18 %. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positive biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. Community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.

2 August 2019 in Science Advances
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AMAdam Martiny
Adam Martiny
Michael W. LomasMichael W. Lomas
Michael W. Lomas
Weiwei FuWeiwei Fu
Weiwei Fu
PBPhilip W. Boyd
Philip W. Boyd
YCYuh-Ling L. Chen
Yuh-Ling L. Chen
JMJ. Keith Moore
J. Keith Moore
High-sensitivity measurements reveal variation in surface ocean phosphate, leading to a new model for ocean nutrient cycles.

6 December 2023 in Nature
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WWWei-Lei Wang
Wei-Lei Wang
Weiwei FuWeiwei Fu
Weiwei Fu
FMFrédéric A. C. Le Moigne
Frédéric A. C. Le Moigne
RLRobert T. Letscher
Robert T. Letscher
YLYi Liu
Yi Liu
FPFrançois W. Primeau
François W. Primeau
The transfer of photosynthetically produced organic carbon from surface to mesopelagic waters draws carbon dioxide from the atmosphere1. However, current observation-based estimates disagree on the strength of this biological carbon pump (BCP)2. Earth system models (ESMs) also exhibit a large spread of BCP estimates, indicating limited representations of the known carbon export pathways3. Here we use several decades of hydrographic observations to produce a top-down estimate of the strength of the BCP with an inverse biogeochemical model that implicitly accounts for all known export pathways. Our estimate of total organic carbon (TOC) export at 73.4 m (model euphotic zone depth) is 15.00 ± 1.12 Pg C year−1, with only two-thirds reaching 100 m depth owing to rapid remineralization of organic matter in the upper water column. Partitioned by sequestration time below the euphotic zone, τ, the globally integrated organic carbon production rate with τ > 3 months is 11.09 ± 1.02 Pg C year−1, dropping to 8.25 ± 0.30 Pg C year−1 for τ > 1 year, with 81% contributed by the non-advective-diffusive vertical flux owing to sinking particles and vertically migrating zooplankton. Nevertheless, export of organic carbon by mixing and other fluid transport of dissolved matter and suspended particles remains regionally important for meeting the respiratory carbon demand. Furthermore, the temperature dependence of the sequestration efficiency inferred from our inversion suggests that future global warming may intensify the recycling of organic matter in the upper ocean, potentially weakening the BCP.

2 October 2022 in Journal of Geophysical Research: Oceans
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Journal Article
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Weiwei FuWeiwei Fu
Weiwei Fu
JMJ. Keith Moore
J. Keith Moore
FPFrancois Primeau
Francois Primeau
NCNathan Collier
Nathan Collier
OOOluwaseun O. Ogunro
Oluwaseun O. Ogunro
JRJames T. Randerson
James T. Randerson
The International Ocean Model Benchmarking (IOMB) software package is a new community resource that we use here to evaluate surface and upper ocean biogeochemical variables and integrated anthropogenic carbon uptake from earth system models (ESMs) contributing to the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). IOMB generates graphics and tables for systematically comparing model predictions against multiple datasets. Our analysis reveals some improvement in the multi‐model mean from CMIP5 to CMIP6 for most of the variables we examined. Compared to data‐constrained estimates of ocean anthropogenic carbon uptake for the 1994–2007 period, negative biases exist for many models between 30 and 50°S. Global model estimates of anthropogenic carbon uptake for the same period do not change significantly from CMIP5 to CMIP6, with the combined ensemble mean estimate of 27.8 ± 0.5 Pg C lower than a data‐constrained estimate of 33.0 ± 4.0 Pg C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of 0.7 ± 0.3 Pg C, which is considerably smaller in magnitude than a data‐constrained estimate of 5.0 ± 3.0 Pg C. With chlorofluorocarbon (CFC) predictions available for several models, we demonstrate that negative anthropogenic dissolved inorganic carbon biases coincide with negative biases in CFC concentration, highlighting the importance of weak exchange between the surface and interior ocean in regulating rates of anthropogenic carbon uptake. To examine the robustness of this attribution across the CMIP models, we calculate the global vertical temperature gradient between 200 and 1,000 m as a metric for global stratification and exchange between the surface and deeper waters. We find a linear relationship between the bias of the vertical temperature gradients and the bias in global anthropogenic carbon uptake, consistent with the hypothesis that model biases in anthropogenic carbon uptake are related to biases in surface‐to‐interior exchange by physical processes.

13 April 2018 in Global Biogeochemical Cycles
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Weiwei FuWeiwei Fu
Weiwei Fu
FPFrancois Primeau
Francois Primeau
JMJ. Keith Moore
J. Keith Moore
KLKeith Lindsay
Keith Lindsay
JRJames T. Randerson
James T. Randerson