The ocean has absorbed about 25% of the carbon emitted by humans to date. To better predict how much climate will change, it is critical to understand how this ocean carbon sink will respond to future emissions. Here, we examine the ocean carbon sink response to low emission (SSP1-1.9, SSP1-2.6), intermediate emission (SSP2-4.5, SSP5-3.4-OS), and high emission (SSP5-8.5) scenarios in CMIP6 Earth System Models and in MAGICC7, a reduced-complexity climate carbon system model. From 2020–2100, the trajectory of the global-mean sink approximately parallels the trajectory of anthropogenic emissions. With increasing cumulative emissions during this century (SSP5-8.5 and SSP2-4.5), the cumulative ocean carbon sink absorbs 20%–30% of cumulative emissions since 2015. In scenarios where emissions decline, the ocean absorbs an increasingly large proportion of emissions (up to 120% of cumulative emissions since 2015). Despite similar responses in all models, there remains substantial quantitative spread in estimates of the cumulative sink through 2100 within each scenario, up to 50 PgC in CMIP6 and 120 PgC in the MAGICC7 ensemble. We demonstrate that for all but SSP1-2.6, approximately half of this future spread can be eliminated if model results are adjusted to agree with modern observation-based estimates. Considering the spatial distribution of air-sea CO2fluxes in CMIP6, we find significant zonal-mean divergence from the suite of newly-available observation-based constraints. We conclude that a significant portion of future ocean carbon sink uncertainty is attributable to modern-day errors in the mean state of air-sea CO2fluxes, which in turn are associated with model representations of ocean physics and biogeochemistry. Bringing models into agreement with modern observation-based estimates at regional to global scales can substantially reduce uncertainty in future role of the ocean in absorbing anthropogenic CO2from the atmosphere and mitigating climate change.
Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.
more » « less- Award ID(s):
- 1936222
- NSF-PAR ID:
- 10375686
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Global Biogeochemical Cycles
- Volume:
- 34
- Issue:
- 8
- ISSN:
- 0886-6236
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen. MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational data sets. The model simulates present‐day air‐sea CO2flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO2is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger‐than‐observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth. Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally integrated net primary production (NPP) of 48 Pg C yr−1and particulate export flux at 100 m of 7.1 Pg C yr−1. The impacts of climate change include an increase in globally integrated NPP, but substantial declines in the North Atlantic. Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.
-
more » « less
Abstract In August 2022, Death Valley, the driest place in North America, experienced record flooding from summertime rainfall associated with the North American monsoon (NAM). Given the socioeconomic cost of these type of events, there is a dire need to understand their drivers and future statistics. Existing theory predicts that increases in the intensity of precipitation is a robust response to anthropogenic warming. Paleoclimatic evidence suggests that northeast Pacific (NEP) sea surface temperature (SST) variability could further intensify summertime NAM rainfall over the desert southwest. Drawing on this paleoclimatic evidence, we use historical observations and reanalyzes to test the hypothesis that warm SSTs on the southern California margin are linked to more frequent extreme precipitation events in the NAM domain. We find that summers with above-average coastal SSTs are more favorable to moist convection in the northern edge of the NAM domain (southern California, Arizona, New Mexico, and the southern Great Basin). This is because warmer SSTs drive circulation changes that increase moisture flux into the desert southwest, driving more frequent precipitation extremes and increases in seasonal rainfall totals. These results, which are robust across observational products, establish a linkage between marine and terrestrial extremes, since summers with anomalously warm SSTs on the California margin have been linked to seasonal or multi-year NEP marine heatwaves. However, current generation earth system models (ESMs) struggle to reproduce the observed relationship between coastal SSTs and NAM precipitation. Across models, there is a strong negative relationship between the magnitude of an ESM’s warm SST bias on the California margin and its skill at reproducing the correlation with desert southwest rainfall. Given persistent NEP SST biases in ESMs, our results suggest that efforts to improve representation of climatological SSTs are crucial for accurately predicting future changes in hydroclimate extremes in the desert southwest.
-
Abstract. Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018).more » « less
-
more » « less
Abstract We use a modern Earth system model to approximate the relative importance of ice versus temperature on Arctic marine ecosystem dynamics. We show that while the model adequately simulates ice volume, water temperature, air‐sea CO2flux, and annual primary production in the Arctic, itunderestimates upper water column nitrate across the region. This nitrate bias is likely responsible for the apparent underestimation of ice algae production. Despite this shortcoming, the model appears to be a useful tool for exploring the impacts of environmental change on phytoplankton production and carbon dynamics over the Arctic Ocean. Our experiments indicate that under a warmer climate scenario, the percentage of ocean warming that could be apportioned to a reduction in ice area ranged from 11% to 100%, while decreasing ice area could account for 22–100% of the increase in annual ocean primary production. The change to CO2air‐sea flux in response to ice and temperature changes averaged an Arctic‐wide 5.5 Tg C yr−1(3.5%) increase, into the ocean. This increased carbon sink may be short‐lived, as ice cover continues to decrease and the ocean warms. The change in carbon fixation from phytoplankton in response to increased temperatures and reduced ice was generally more than a magnitude larger than the changes to CO2flux, highlighting the importance of fully considering changes to the marine ecosystem when assessing Arctic carbon cycle dynamics. Our work demonstrates the importance of ice dynamics in controlling ocean warming and production and thus the need for well‐behaved ice and BGC models within Earth system models if we hope to accurately predict Arctic changes.
