Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks

Ran Feng; Tripti Bhattacharya; Bette L. Otto-Bliesner; Esther C. Brady; Alan M. Haywood; Julia C. Tindall; Stephen J. Hunter; Ayako Abe-Ouchi; Wing Le Chan; Masa Kageyama; Camille Contoux; Chuncheng Guo; Xiangyu Li; Gerrit Lohmann; Christian Stepanek; Ning Tan; Qiong Zhang; Zhongshi Zhang; Zixuan Han; Charles J.R. Williams; Daniel J. Lunt; Harry J. Dowsett; Deepak Chandan; W. Richard Peltier

doi:10.1038/s41467-022-28814-7

Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks

Ran Feng^*, Tripti Bhattacharya, Bette L. Otto-Bliesner, Esther C. Brady, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Ayako Abe-Ouchi, Wing Le Chan, Masa Kageyama, Camille Contoux, Chuncheng Guo, Xiangyu Li, Gerrit Lohmann, Christian Stepanek, Ning Tan, Qiong Zhang, Zhongshi Zhang, Zixuan Han, Charles J.R. WilliamsDaniel J. Lunt, Harry J. Dowsett, Deepak Chandan, W. Richard Peltier

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

Despite tectonic conditions and atmospheric CO₂ levels (pCO₂) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO₂ radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO₂. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO₂ forcing.

Original language	English
Article number	1306
Journal	Nature Communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-28814-7
Publication status	Published - 14 Mar 2022

Bibliographical note

Funding Information:
The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsrådet) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute’s research programme PACES2. C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Très Grande Infrastructure de Calcul (TGCC) at Commissariat à l’Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF’s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer. COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute – Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer.

Funding Information:
The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsr?det) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute?s research programme PACES2.?C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR?s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Tr?s Grande Infrastructure de Calcul (TGCC) at Commissariat ? l?Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF?s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer.?COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute ? Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer.

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Feng, R., Bhattacharya, T., Otto-Bliesner, B. L., Brady, E. C., Haywood, A. M., Tindall, J. C., Hunter, S. J., Abe-Ouchi, A., Chan, W. L., Kageyama, M., Contoux, C., Guo, C., Li, X., Lohmann, G., Stepanek, C., Tan, N., Zhang, Q., Zhang, Z., Han, Z., ... Peltier, W. R. (2022). Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks. Nature Communications, 13(1), Article 1306. https://doi.org/10.1038/s41467-022-28814-7

@article{be965df8770c4242ae2d4ffb989e187b,

title = "Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks",

abstract = "Despite tectonic conditions and atmospheric CO2 levels (pCO2) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO2 radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO2. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO2 forcing.",

author = "Ran Feng and Tripti Bhattacharya and Otto-Bliesner, {Bette L.} and Brady, {Esther C.} and Haywood, {Alan M.} and Tindall, {Julia C.} and Hunter, {Stephen J.} and Ayako Abe-Ouchi and Chan, {Wing Le} and Masa Kageyama and Camille Contoux and Chuncheng Guo and Xiangyu Li and Gerrit Lohmann and Christian Stepanek and Ning Tan and Qiong Zhang and Zhongshi Zhang and Zixuan Han and Williams, {Charles J.R.} and Lunt, {Daniel J.} and Dowsett, {Harry J.} and Deepak Chandan and Peltier, {W. Richard}",

note = "Funding Information: The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsr{\aa}det) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute{\textquoteright}s research programme PACES2. C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR{\textquoteright}s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Tr{\`e}s Grande Infrastructure de Calcul (TGCC) at Commissariat {\`a} l{\textquoteright}Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF{\textquoteright}s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer. COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute – Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer. Funding Information: The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsr?det) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute?s research programme PACES2.?C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR?s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Tr?s Grande Infrastructure de Calcul (TGCC) at Commissariat ? l?Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF?s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer.?COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute ? Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

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doi = "10.1038/s41467-022-28814-7",

language = "English",

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Feng, R, Bhattacharya, T, Otto-Bliesner, BL, Brady, EC, Haywood, AM, Tindall, JC, Hunter, SJ, Abe-Ouchi, A, Chan, WL, Kageyama, M, Contoux, C, Guo, C, Li, X, Lohmann, G, Stepanek, C, Tan, N, Zhang, Q, Zhang, Z, Han, Z, Williams, CJR , Lunt, DJ, Dowsett, HJ, Chandan, D & Peltier, WR 2022, 'Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks', Nature Communications, vol. 13, no. 1, 1306. https://doi.org/10.1038/s41467-022-28814-7

TY - JOUR

T1 - Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks

AU - Feng, Ran

AU - Bhattacharya, Tripti

AU - Otto-Bliesner, Bette L.

AU - Brady, Esther C.

AU - Haywood, Alan M.

AU - Tindall, Julia C.

AU - Hunter, Stephen J.

AU - Abe-Ouchi, Ayako

AU - Chan, Wing Le

AU - Kageyama, Masa

AU - Contoux, Camille

AU - Guo, Chuncheng

AU - Li, Xiangyu

AU - Lohmann, Gerrit

AU - Stepanek, Christian

AU - Tan, Ning

AU - Zhang, Qiong

AU - Zhang, Zhongshi

AU - Han, Zixuan

AU - Williams, Charles J.R.

AU - Lunt, Daniel J.

AU - Dowsett, Harry J.

AU - Chandan, Deepak

AU - Peltier, W. Richard

N1 - Funding Information: The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsrådet) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute’s research programme PACES2. C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Très Grande Infrastructure de Calcul (TGCC) at Commissariat à l’Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF’s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer. COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute – Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer. Funding Information: The authors would like to thank all modeling groups who provided PMIP4 outputs for this analysis, WCRP, CMIP panel, PCMDI, ESGF infrastructures for sharing data, WCRP, and CLIVAR for supporting the PMIP project. R.F., T.B., B.L.O., and E.C.B acknowledge support from U.S. National Science Foundation grant numbers 1814029 and 1903650 (R.F.), 1903148 and 2103015 (T.B.) and 1852977 (B.L.O. and E.C.B.). X.L. and N.T. acknowledge support from the National Science Foundation of China grant numbers 42005042 (X.L.) and 41888101 (N.T.). D.L. acknowledges support from NERC (Natural Environment Research Council), SWEET Large Grant number NE/P01903X/1. C.C. acknowledges support from France ANR HADoC grant number ANR-17-CE31-0010. Q.Z. acknowledge support from Swedish Research Council (Vetenskapsr?det) grant numbers. 2013-06476 and 2017-04232. W.L.C. and A.A.O. acknowledge support from Japanese JSPS Kakenhi grant 17H06104 and NEXT Kakenhi grant 17H06323. H.D. acknowledges support from USGS Paleoclimate Research and Development Program. C.S. and G.L. acknowledge funding via the Alfred Wegener Institute?s research programme PACES2.?C.S. received funding via the Helmholtz Climate Initiative REKLIM. The PRISM4 reconstruction and boundary conditions used in the presented simulations were funded by the U.S. Geological Survey Climate and Land Use Change Research and Development Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The CESM2 simulations are performed with high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR?s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. The IPSL-CM6A-LR simulation was run on the Tr?s Grande Infrastructure de Calcul (TGCC) at Commissariat ? l?Energie Atomique (gencmip6 project) under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (project gencmip6) provided by GENCI (Grand Equipement National de Calcul Intensif). The model simulations with EC-Earth3 and the data analysis were performed using resources provided by ECMWF?s computing and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), which is partially funded by the Swedish Research Council through grant agreement no. 2018-05973. A.A.O. and W.L.C. acknowledge JAMSTEC for use of the Earth Simulator supercomputer.?COSMOS simulations have been conducted at the Computing and Data Centre of the Alfred Wegener Institute ? Helmholtz Centre for Polar and Marine Research on a NEC SX-ACE high-performance vector computer. Publisher Copyright: © 2022, The Author(s).

PY - 2022/3/14

Y1 - 2022/3/14

N2 - Despite tectonic conditions and atmospheric CO2 levels (pCO2) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO2 radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO2. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO2 forcing.

AB - Despite tectonic conditions and atmospheric CO2 levels (pCO2) similar to those of present-day, geological reconstructions from the mid-Pliocene (3.3-3.0 Ma) document high lake levels in the Sahel and mesic conditions in subtropical Eurasia, suggesting drastic reorganizations of subtropical terrestrial hydroclimate during this interval. Here, using a compilation of proxy data and multi-model paleoclimate simulations, we show that the mid-Pliocene hydroclimate state is not driven by direct CO2 radiative forcing but by a loss of northern high-latitude ice sheets and continental greening. These ice sheet and vegetation changes are long-term Earth system feedbacks to elevated pCO2. Further, the moist conditions in the Sahel and subtropical Eurasia during the mid-Pliocene are a product of enhanced tropospheric humidity and a stationary wave response to the surface warming pattern, which varies strongly with land cover changes. These findings highlight the potential for amplified terrestrial hydroclimate responses over long timescales to a sustained CO2 forcing.

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U2 - 10.1038/s41467-022-28814-7

DO - 10.1038/s41467-022-28814-7

M3 - Article (Academic Journal)

C2 - 35288559

AN - SCOPUS:85126671955

SN - 2041-1723

VL - 13

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 1306

ER -

Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks

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Past terrestrial hydroclimate sensitivity controlled by Earth system feedbacks

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