Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage

Humphrey, Vincent; Zscheischler, Jakob; Ciais, Philippe; Gudmundsson, Lukas; Sitch, Stephen; Seneviratne, Sonia I.

doi:10.1038/s41586-018-0424-4

Cited by 382 publications

(357 citation statements)

References 49 publications

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“…The sensitivity of soil moisture from DGVMs to ONI in the regions with significant effects (NSA, BRA, SAF, and SEAS, negative and CAS, MIDE, and SAS, positive) is generally consistent with that of TWS from the GRACE reconstruction (Humphrey et al, ), although slightly underestimated for NSA and BRA (Figure S4). In SAF and SEAS the sensitivity of SM from DGVMs to ONI is close to that of TWS, but in the former DGVMs show a large range.…”

Section: Resultssupporting

confidence: 68%

“…Sensitivity of NBP to annual temperature (CRU‐JRA, top panel) and to soil moisture for inversions (GRACE reconstruction from (Humphrey et al, )) and DGVMs (with simulated soil moisture) (bottom panel). The bars indicate the range of sensitivities from each set of data, and the crosses show the ensemble mean.…”

Section: Resultsmentioning

confidence: 99%

“…Several studies have shown that variability in tropical CO

_{2}

fluxes (mainly driven by ENSO) is better explained by variations in soil water storage than by temperature alone (Bastos et al, ; Humphrey et al, ; Poulter et al, ). The regions with stronger negative coefficients for ONI (NSA, BRA, SAF, and SEAS, Figure ) are those where El Niño events impose strong warm and dry conditions, and those with positive coefficients (CAS, MIDE, and SAS) are associated with cool and wet conditions during El Niño (Bastos et al, ; Mason & Goddard, ).…”

Section: Discussionmentioning

confidence: 99%

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Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Bastos

O’Sullivan

Ciais

et al. 2020

Global Biogeochemical Cycles

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The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO 2 growth rate, fossil fuel emissions, and modeled (bottom‐up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom‐up and top‐down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO 2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high‐resolution remote‐sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.

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Section: Resultssupporting

confidence: 68%

Section: Resultsmentioning

confidence: 99%

“…Several studies have shown that variability in tropical CO

_{2}

Section: Discussionmentioning

confidence: 99%

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Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Bastos

O’Sullivan

Ciais

et al. 2020

Global Biogeochemical Cycles

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“…Many studies have described the impacts of drought on the carbon cycle (Ciais et al, ; Humphrey et al, ; J. Liu et al, ; Sun et al, ; Wolf et al, ); however, the impacts of extreme wetness (i.e., floods) have been less well documented. Floods are among the major climate‐related disasters that are projected to increase in a warmer climate (Hirabayashi et al, ); quantifying their impact on the terrestrial carbon cycle is critical for the assessment of future climate change impacts.…”

Section: Introductionmentioning

confidence: 99%

Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods

et al. 2020

Self Cite

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While large‐scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO2 offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration. Widespread flooding during spring and early summer 2019 induced conditions that delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar‐induced chlorophyll fluorescence from TROPOspheric Monitoring Instrument and Orbiting Carbon Observatory reveal a 16‐day shift in the seasonal cycle of photosynthesis relative to 2018, along with a 15% lower peak value. We estimate a reduction of 0.21 PgC in cropland gross primary productivity in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late‐season temperature. Ultimately, this change is predicted to reduce the crop productivity in the Midwest Corn/Soy belt by ~15% compared to 2018. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO2 enhancements of up to 10 ppm in the midday boundary layer from Atmospheric Carbon and Transport‐America aircraft and over 3 ppm in column‐averaged dry‐air mole fractions from Orbiting Carbon Observatory. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining solar‐induced chlorophyll fluorescence with atmospheric CO2 observations to monitor regional carbon flux anomalies.

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“…Forests provide a wide range of ecosystem functions and services from global to local scale (Brockerhoff et al, ). It is therefore essential to understand how forest ecosystem productivity responds to climate extremes across environmental gradients (Ciais et al, ; Cramer et al, ; Reichstein et al, ) and how those responses feed back to the climate system (Humphrey et al, ). Climate change can affect forests on various levels, for example, by modifying the balance and interactions between direct abiotic constraints on tree growth (Cuny et al, ), shifting the timing of the growing season (Bigler & Bugmann, ), or altering disturbance regimes (Senf et al, ; Sommerfeld et al, ).…”

Section: Introductionmentioning

confidence: 99%

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

Trotsiuk

Härtig

Cailleret

et al. 2020

Global Change Biology

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The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha−1 year−1 km−1 for P. abies and 0.93 ± 0.010 Mg C ha−1 year−1 km−1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.

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Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage

Cited by 382 publications

References 49 publications

Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

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Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage

Cited by 382 publications

References 49 publications

Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates

Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates

Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

Contact Info

Product

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Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates

Sources of Uncertainty in Regional and Global Terrestrial CO₂ Exchange Estimates