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Abstract We use a statistical emulation technique to construct synthetic ensembles of global and regional sea‐air carbon dioxide (CO2) flux from four observation‐based products over 1985–2014. Much like ensembles of Earth system models that are constructed by perturbing their initial conditions, our synthetic ensemble members exhibit different phasing of internal variability and a common externally forced signal. Our synthetic ensembles illustrate an important role for internal variability in the temporal evolution of global and regional CO2flux and produce a wide range of possible trends over 1990–1999 and 2000–2009. We assume a specific externally forced signal and calculate the rank of the observed trends within the distribution of statistically modeled synthetic trends during these periods. Over the decade 1990–1999, three of four observation‐based products exhibit small negative trends in globally integrated sea‐air CO2flux (i.e., enhanced ocean CO2absorption with time) that are within one standard deviation of the mean in their respective synthetic ensembles. Over the decade 2000–2009, however, three products show large negative trends in globally integrated sea‐air CO2flux that have a low rate of occurrence in their synthetic ensembles. The largest positive trends in global and Southern Ocean flux over 1990–1999 and the largest negative trends over 2000–2009 fall nearly two standard deviations away from the mean in their ensembles. Our approach provides a new perspective on the important role of internal variability in sea‐air CO2flux trends, and furthers understanding of the role of internal and external processes in driving observed sea‐air CO2flux variability.
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Alternate History: A Synthetic Ensemble of Ocean Chlorophyll Concentrations
Abstract Internal climate variability plays an important role in the abundance and distribution of phytoplankton in the global ocean. Previous studies using large ensembles of Earth system models (ESMs) have demonstrated their utility in the study of marine phytoplankton variability. These ESM large ensembles simulate the evolution of multiple alternate realities, each with a different phasing of internal climate variability. However, ESMs may not accurately represent real world variability as recorded via satellite and in situ observations of ocean chlorophyll over the past few decades. Observational records of surface ocean chlorophyll equate to a single ensemble member in the large ensemble framework, and this can cloud the interpretation of long‐term trends: are they externally forced, caused by the phasing of internal variability, or both? Here, we use a novel statistical emulation technique to place the observational record of surface ocean chlorophyll into the large ensemble framework. Much like a large initial condition ensemble generated with an ESM, the resulting synthetic ensemble represents multiple possible evolutions of ocean chlorophyll concentration, each with a different sampling of internal climate variability. We further demonstrate the validity of our statistical approach by recreating an ESM ensemble of chlorophyll using only a single ESM ensemble member. We use the synthetic ensemble to explore the interpretation of long‐term trends in the presence of internal variability and find a wider range of possible trends in chlorophyll due to the sampling of internal variability in subpolar regions than in subtropical regions.
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- Award ID(s):
- 1752724
- PAR ID:
- 10360073
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Global Biogeochemical Cycles
- Volume:
- 35
- Issue:
- 9
- ISSN:
- 0886-6236
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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