How summertime temperature variability will change with warming has important implications for climate adaptation and mitigation. CMIP5 simulations indicate a compound risk of extreme hot temperatures in western Europe from both warming and increasing temperature variance. CMIP6 simulations, however, indicate only a moderate increase in temperature variance that does not covary with warming. To explore this intergenerational discrepancy in CMIP results, we decompose changes in monthly temperature variance into those arising from changes in sensitivity to forcing and changes in forcing variance. Across models, sensitivity increases with local warming in both CMIP5 and CMIP6 at an average rate of 5.7 ([3.7, 7.9]; 95% c.i.) × 10−3°C per W m−2per °C warming. We use a simple model of moist surface energetics to explain increased sensitivity as a consequence of greater atmospheric demand (∼70%) and drier soil (∼40%) that is partially offset by the Planck feedback (∼−10%). Conversely, forcing variance is stable in CMIP5 but decreases with warming in CMIP6 at an average rate of −21 ([−28, −15]; 95% c.i.) W2 m−4per °C warming. We examine scaling relationships with mean cloud fraction and find that mean forcing variance decreases with decreasing cloud fraction at twice the rate in CMIP6 than CMIP5. The stability of CMIP6 temperature variance is, thus, a consequence of offsetting changes in sensitivity and forcing variance. Further work to determine which models and generations of CMIP simulations better represent changes in cloud radiative forcing is important for assessing risks associated with increased temperature variance.
This content will become publicly available on March 1, 2025
Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO2levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.
more » « less- Award ID(s):
- 2129235
- NSF-PAR ID:
- 10541496
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- AGU Advances
- Volume:
- 5
- Issue:
- 2
- ISSN:
- 2576-604X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Soil is the largest terrestrial carbon (C) reservoir and a large potential source or sink of atmospheric CO₂. Soil C models have usually focused on refining representations of microbe‐mediated C turnover, whereas lateral hydrologic C fluxes have largely been ignored at regional and global scales. Here, we provide large‐scale estimates of hydrologic export of soil organic carbon (SOC) and its effects on bulk soil C turnover rates. Hydrologic export of SOC ranged from nearly 0 to 12 g C m−2yr−1amongst catchments across the conterminous United States, and total export across this region was 14 (95% CI 4‐41) Tg C/yr. The proportion of soil C turnover attributed to hydrologic export ranged from <1% to 20%, and averaged 0.97% (weighted by catchment area; 95% CI 0.3%–2.6%), with the lowest values in arid catchments. Ignoring hydrologic export in C cycle models might lead to overestimation of SOC stocks by 0.3–2.6 Pg C for the conterminous United States. High uncertainty in hydrologic C export fluxes and potentially substantial effects on soil C turnover illustrate the need for research aimed at improving our mechanistic understanding of the processes regulating hydrologic C export.
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Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycleAbstract The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean $${149}_{-23}^{+29}$$ 149 − 23 + 29 Pg C yr −1 ) are significantly higher than most GPP estimates reported in the literature ( $${113}_{-18}^{+18}$$ 113 − 18 + 18 Pg C yr −1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of $${68}_{-8}^{+10}$$ 68 − 8 + 10 Pg C yr −1 ) statistically inconsistent with most published R S values ( $${87}_{-8}^{+9}$$ 87 − 8 + 9 Pg C yr −1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.more » « less
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Abstract Aim C4grasses are distinct from C3grasses, because C4grasses respond in a different manner to light, temperature, CO2and nitrogen and often have higher resource‐use efficiencies. C3and C4grasses are typically represented in earth system models (ESMs) by different plant functional types (PFTs). The ability of ESMs to capture C4grass biogeography and ecology across differing time periods is important to assess, given the crucial role they play in ecosystems and their divergent responses to global change.
Location North America.
Time periods Last Glacial Maximum (LGM), historical modern period (
ca . 1850) and end of this century.Major taxa studied C4grasses.
Methods Proxy data representing relative cover and productivity of C4grasses were collated, including carbon isotope ratios of soil carbon and animal grazer tissue, and vegetation plot data in undisturbed grasslands. We selected available model predictions of C4PFT percentage cover. Models were compared against one another and assessed against proxy data at key time points: the LGM, the historical modern period before widespread grassland conversion to agriculture, and the end of this century.
Results We highlight large differences among model predictions of percentage C4grass cover across North America: all pairwise combinations have correlations < .5, and most are < .2. Models also do not capture spatial patterns of the percentage C4grass cover from proxy data, during either the LGM or the historical modern period. Models generally under‐predict percentage C4grass cover, particularly during the historical modern period.
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Abstract Background China’s terrestrial ecosystems play a pronounced role in the global carbon cycle. Here we combine spatially-explicit information on vegetation, soil, topography, climate and land use change with a process-based biogeochemistry model to quantify the responses of terrestrial carbon cycle in China during the 20th century.
Results At a century scale, China’s terrestrial ecosystems have acted as a carbon sink averaging at 96 Tg C yr− 1, with large inter-annual and decadal variabilities. The regional sink has been enhanced due to the rising temperature and CO2concentration, with a slight increase trend in carbon sink strength along with the enhanced net primary production in the century. The areas characterized by C source are simulated to extend in the west and north of the Hu Huanyong line, while the eastern and southern regions increase their area and intensity of C sink, particularly in the late 20th century. Forest ecosystems dominate the C sink in China and are responsible for about 64% of the total sink. On the century scale, the increase in carbon sinks in China’s terrestrial ecosystems is mainly contributed by rising CO2. Afforestation and reforestation promote an increase in terrestrial carbon uptake in China from 1950s. Although climate change has generally contributed to the increase of carbon sinks in terrestrial ecosystems in China, the positive effect of climate change has been diminishing in the last decades of the 20th century.
Conclusion This study focuses on the impacts of climate, CO2and land use change on the carbon cycle, and presents the potential trends of terrestrial ecosystem carbon balance in China at a century scale. While a slight increase in carbon sink strength benefits from the enhanced vegetation carbon uptake in China’s terrestrial ecosystems during the 20th century, the increase trend may diminish or even change to a decrease trend under future climate change.
