Remotely sensing potential climate change tipping points across scales.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
06 Jan 2024
06 Jan 2024
Historique:
received:
15
09
2023
accepted:
18
12
2023
medline:
7
1
2024
pubmed:
7
1
2024
entrez:
6
1
2024
Statut:
epublish
Résumé
Potential climate tipping points pose a growing risk for societies, and policy is calling for improved anticipation of them. Satellite remote sensing can play a unique role in identifying and anticipating tipping phenomena across scales. Where satellite records are too short for temporal early warning of tipping points, complementary spatial indicators can leverage the exceptional spatial-temporal coverage of remotely sensed data to detect changing resilience of vulnerable systems. Combining Earth observation with Earth system models can improve process-based understanding of tipping points, their interactions, and potential tipping cascades. Such fine-resolution sensing can support climate tipping point risk management across scales.
Identifiants
pubmed: 38184618
doi: 10.1038/s41467-023-44609-w
pii: 10.1038/s41467-023-44609-w
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
343Subventions
Organisme : Leverhulme Trust
ID : RPG-2018-046
Organisme : Leverhulme Trust
ID : RPG-2018-046
Organisme : Leverhulme Trust
ID : RPG-2018-046
Organisme : European Space Agency (ESA)
ID : 4000123681/18/INB
Organisme : EC | EC Seventh Framework Programm | FP7 Ideas: European Research Council (FP7-IDEAS-ERC - Specific Programme: "Ideas" Implementing the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities (2007 to 2013))
ID : 951288
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 820970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 820970
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 01LS2001A
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 01LS2001A
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions)
ID : 956170
Informations de copyright
© 2024. The Author(s).
Références
Lenton, T. M. et al. Tipping elements in the Earth’s climate system. Proc. Natl Acad. Sci. USA 105, 1786–1793 (2008). Defines climate tipping points, identifies a shortlist of ‘tipping elements’ and their temperature thresholds, and highlights the potential for early warning signals of them.
pubmed: 18258748
pmcid: 2538841
doi: 10.1073/pnas.0705414105
Armstrong McKay, D. I. et al. Exceeding 1.5 C global warming could trigger multiple climate tipping points. Science 377, eabn7950 (2022).
pubmed: 36074831
doi: 10.1126/science.abn7950
Rocha, J. C., Peterson, G., Bodin, Ö. & Levin, S. Cascading regime shifts within and across scales. Science 362, 1379–1383 (2018).
pubmed: 30573623
doi: 10.1126/science.aat7850
Scheffer, M. et al. Early warning signals for critical transitions. Nature 461, 53–59 (2009). Shows how generic early warning signals can precede tipping points in many complex systems, raising the possibility of resilience monitoring of the Earth system.
pubmed: 19727193
doi: 10.1038/nature08227
Gasser, T. et al. Path-dependent reductions in CO
doi: 10.1038/s41561-018-0227-0
Wunderling, N., Willeit, M., Donges, J. F. & Winkelmann, R. Global warming due to loss of large ice masses and Arctic summer sea ice. Nat. Commun. 11, 5177 (2020).
pubmed: 33110092
pmcid: 7591863
doi: 10.1038/s41467-020-18934-3
Liu, W., Fedorov, A. V., Xie, S.-P. & Hu, S. Climate impacts of a weakened Atlantic Meridional Overturning Circulation in a warming climate. Sci. Adv. 6, eaaz4876 (2020).
pubmed: 32637596
pmcid: 7319730
doi: 10.1126/sciadv.aaz4876
Brovkin, V. et al. Past abrupt changes, tipping points and cascading impacts in the Earth system. Nat. Geosci. 14, 550–558 (2021).
doi: 10.1038/s41561-021-00790-5
Wunderling, N., Donges, J. F., Kurths, J. & Winkelmann, R. Interacting tipping elements increase risk of climate domino effects under global warming. Earth Syst. Dynam. 12, 601–619 (2021).
doi: 10.5194/esd-12-601-2021
Klose, A. K., Karle, V., Winkelmann, R. & Donges, J. F. Emergence of cascading dynamics in interacting tipping elements of ecology and climate. R. Soc. Open Sci. 7, 200599 (2020).
pubmed: 32742700
pmcid: 7353982
doi: 10.1098/rsos.200599
Comiso, J. C., Parkinson, C. L., Gersten, R. & Stock, L. Accelerated decline in the Arctic sea ice cover. Geophys. Res. Lett. 35, L01703 (2008).
Cook, A. J. & Vaughan, D. G. Overview of areal changes of the ice shelves on the Antarctic Peninsula over the past 50 years. Cryosphere 4, 77–98 (2010). A comprehensive review of ice shelf collapse events that have occurred in Antarctica during the satellite era.
doi: 10.5194/tc-4-77-2010
Velicogna, I. & Wahr, J. Measurements of time-variable gravity show mass loss in Antarctica. Science 311, 1754–1756 (2006).
pubmed: 16513944
doi: 10.1126/science.1123785
Rignot, E. & Kanagaratnam, P. Changes in the velocity structure of the Greenland ice sheet. Science 311, 986–990 (2006).
pubmed: 16484490
doi: 10.1126/science.1121381
Thomas, R. et al. Accelerated sea-level rise from West Antarctica. Science 306, 255–258 (2004).
pubmed: 15388895
doi: 10.1126/science.1099650
Rignot, E., Mouginot, J., Morlighem, M., Seroussi, H. & Scheuchl, B. Widespread, rapid grounding line retreat of Pine Island, Thwaites, Smith, and Kohler glaciers, West Antarctica, from 1992 to 2011. Geophys. Res. Lett. 41, 3502–3509 (2014).
doi: 10.1002/2014GL060140
Joughin, I., Smith, B. E. & Medley, B. Marine ice sheet collapse potentially under way for the Thwaites Glacier Basin, West Antarctica. Science 344, 735–738 (2014).
pubmed: 24821948
doi: 10.1126/science.1249055
Rignot, E. et al. Four decades of Antarctic ice sheet mass balance from 1979–2017. Proc. Natl Acad. Sci. USA 116, 1095–1103 (2019).
pubmed: 30642972
pmcid: 6347714
doi: 10.1073/pnas.1812883116
Shepherd, A. et al. Trends in Antarctic ice sheet elevation and mass. Geophys. Res. Lett. 46, 8174–8183 (2019).
pubmed: 35866175
pmcid: 9285922
doi: 10.1029/2019GL082182
Konrad, H. et al. Net retreat of Antarctic glacier grounding lines. Nat. Geosci. 11, 258–262 (2018). The first complete picture of grounding line retreat in Antarctica, an indicator of marine ice shelf instability.
doi: 10.1038/s41561-018-0082-z
Mouginot, J., Rignot, E. & Scheuchl, B. Sustained increase in ice discharge from the Amundsen Sea Embayment, West Antarctica, from 1973 to 2013. Geophys. Res. Lett. 41, 1576–1584 (2014).
doi: 10.1002/2013GL059069
Bjordal, J., Storelvmo, T., Alterskjær, K. & Carlsen, T. Equilibrium climate sensitivity above 5 °C plausible due to state-dependent cloud feedback. Nat. Geosci. 13, 718–721 (2020).
doi: 10.1038/s41561-020-00649-1
Scheffer, M., Hirota, M., Holmgren, M., Van Nes, E. H. & Chapin, F. S. Thresholds for boreal biome transitions. Proc. Natl Acad. Sci. USA 109, 21384–21389 (2012).
pubmed: 23236159
pmcid: 3535627
doi: 10.1073/pnas.1219844110
Abis, B. & Brovkin, V. Environmental conditions for alternative tree-cover states in high latitudes. Biogeosciences 14, 511–527 (2017).
doi: 10.5194/bg-14-511-2017
Hirota, M., Holmgren, M., Van Nes, E. H. & Scheffer, M. Global resilience of tropical forest and savanna to critical transitions. Science 334, 232–235 (2011).
pubmed: 21998390
doi: 10.1126/science.1210657
Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of Savanna and forest as alternative biome states. Science 334, 230–232 (2011).
pubmed: 21998389
doi: 10.1126/science.1210465
Wuyts, B., Champneys, A. R. & House, J. I. Amazonian forest-savanna bistability and human impact. Nat. Commun. 8, 15519 (2017).
pubmed: 28555627
pmcid: 5459990
doi: 10.1038/ncomms15519
Verbesselt, J. et al. Remotely sensed resilience of tropical forests. Nat. Clim. Change 6, 1028–1031 (2016). Uses remotely sensed vegetation data to demonstrate that as mean annual precipitation declines, temporal autocorrelation increases, indicating loss of resilience.
doi: 10.1038/nclimate3108
Boulton, C. A., Lenton, T. M. & Boers, N. Pronounced loss of Amazon rainforest resilience since the early 2000s. Nat. Clim. Change 12, 271–278 (2022).
doi: 10.1038/s41558-022-01287-8
Lenton, T. M. et al. A resilience sensing system for the biosphere. Philos. Trans. R. Soc. B: Biol. Sci. 377, 20210383 (2022).
doi: 10.1098/rstb.2021.0383
Kéfi, S., Dakos, V., Scheffer, M., Van Nes, E. H. & Rietkerk, M. Early warning signals also precede non-catastrophic transitions. Oikos 122, 641–648 (2012).
doi: 10.1111/j.1600-0706.2012.20838.x
Boers, N., Ghil, M. & Stocker, T. F. Theoretical and paleoclimatic evidence for abrupt transitions in the Earth system. Environ. Res. Lett. 17, 093006 (2022).
doi: 10.1088/1748-9326/ac8944
Robinson, A., Calov, R. & Ganopolski, A. Multistability and critical thresholds of the Greenland ice sheet. Nat. Clim. Change 2, 429–432 (2012).
doi: 10.1038/nclimate1449
Liu, W., Xie, S.-P., Liu, Z. & Zhu, J. Overlooked possibility of a collapsed Atlantic Meridional Overturning Circulation in warming climate. Sci. Adv. 3, e1601666 (2017).
Jackson, L. C. & Wood, R. A. Hysteresis and Resilience of the AMOC in an Eddy-Permitting GCM. Geophys. Res. Lett. 45, 8547–8556 (2018).
doi: 10.1029/2018GL078104
Boers, N. & Rypdal, M. Critical slowing down suggests that the western Greenland ice sheet is close to a tipping point. Proc. Natl Acad. Sci. USA 118, e2024192118 (2021).
pubmed: 34001613
pmcid: 8166178
doi: 10.1073/pnas.2024192118
Boers, N. Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation. Nat. Clim. Change 11, 680–688 (2021).
doi: 10.1038/s41558-021-01097-4
Moesinger, L. et al. The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA). Earth Syst. Sci. Data 12, 177–196 (2020).
doi: 10.5194/essd-12-177-2020
Boulton, C. A., Allison, L. C. & Lenton, T. M. Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model. Nat. Commun. 5, 5752 (2014).
pubmed: 25482065
doi: 10.1038/ncomms6752
Ciemer, C. et al. Higher resilience to climatic disturbances in tropical vegetation exposed to more variable rainfall. Nat. Geosci. 12, 174–179 (2019).
doi: 10.1038/s41561-019-0312-z
Dakos, V., van Nes, E., Donangelo, R., Fort, H. & Scheffer, M. Spatial correlation as leading indicator of catastrophic shifts. Theor. Ecol. 3, 163–174 (2010). Shows how spatially extended systems can show specific early warning signals of collapse, opening possibilities for applications to Earth observations.
doi: 10.1007/s12080-009-0060-6
Krishnamurthy R, P. K., Fisher, J. B., Schimel, D. S. & Kareiva, P. M. Applying tipping point theory to remote sensing science to improve early warning drought signals for food security. Earth’s Future 8, e2019EF001456 (2020).
doi: 10.1029/2019EF001456
Krishnamurthy R, P. K., Fisher, J. B., Choularton, R. J. & Kareiva, P. M. Anticipating drought-related food security changes. Nat. Sustain. 5, 956–964 (2022).
doi: 10.1038/s41893-022-00962-0
Thellmann, K. et al. Tipping points in the supply of ecosystem services of a mountainous watershed in Southeast Asia. Sustainability 10, 2418 (2018).
doi: 10.3390/su10072418
Mercer, J. H. West Antarctic ice sheet and CO
doi: 10.1038/271321a0
Lenton, T. M. et al. Climate tipping points—too risky to bet against. Nature 575, 592–595 (2019).
pubmed: 31776487
doi: 10.1038/d41586-019-03595-0
Hall, A., Cox, P., Huntingford, C. & Klein, S. Progressing emergent constraints on future climate change. Nat. Clim. Change 9, 269–278 (2019).
doi: 10.1038/s41558-019-0436-6
Cai, Y., Lenton, T. M. & Lontzek, T. S. Risk of multiple interacting tipping points should encourage rapid CO
doi: 10.1038/nclimate2964
Committee on Climate Change. Net Zero—The UK’s Contribution to Stopping Global Warming. (Committee on Climate Change, 2019).
Lenton, T. M. & Ciscar, J.-C. Integrating tipping points into climate impact assessments. Clim. Change 117, 585–597 (2013).
doi: 10.1007/s10584-012-0572-8
Collins, M. et al. in The Ocean and Cryosphere in a Changing Climate: Special Report of the Intergovernmental Panel on Climate Change (eds H.-O. Pörtner et al.) 589–656 (Cambridge University Press, 2019).
Sellers, P. J., Schimel, D. S., Moore, B., Liu, J. & Eldering, A. Observing carbon cycle-climate feedbacks from space. Proc. Natl Acad. Sci. USA 115, 7860–7868 (2018).
pubmed: 29987011
pmcid: 6077726
doi: 10.1073/pnas.1716613115
Berdugo, M., Gaitán, J. J., Delgado-Baquerizo, M., Crowther, T. W. & Dakos, V. Prevalence and drivers of abrupt vegetation shifts in global drylands. Proc. Natl Acad. Sci. USA 119, e2123393119 (2022).
pubmed: 36252001
pmcid: 9618119
doi: 10.1073/pnas.2123393119
Smith, T., Traxl, D. & Boers, N. Empirical evidence for recent global shifts in vegetation resilience. Nat. Clim. Change 12, 477–484 (2022). Uses remotely sensed vegetation data to confirm theory that resilience indicators based on continuous temporal statistics accurately capture recovery rate from perturbations.
doi: 10.1038/s41558-022-01352-2
Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).
pubmed: 11595939
doi: 10.1038/35098000
Biggs, R., Peterson, G. D. & Rocha, J. C. The Regime Shifts Database: a framework for analyzing regime shifts in social-ecological systems. Ecol. Soc. 23, 9 (2018).
Swingedouw, D. et al. On the risk of abrupt changes in the North Atlantic subpolar gyre in CMIP6 models. Ann. N. Y. Acad. Sci. 1504, 187–201 (2021).
pubmed: 34212391
doi: 10.1111/nyas.14659
Swingedouw, D. et al. Early warning from space for a few key tipping points in physical, biological, and social-ecological systems. Surv. Geophys. 41, 1237–1284 (2020). First review of the potential for remote sensing to provide early warning signals of some climate tipping points.
doi: 10.1007/s10712-020-09604-6
Kumar, P., Kishtawal, C. M. & Pal, P. K. Impact of satellite rainfall assimilation on Weather Research and Forecasting model predictions over the Indian region. J. Geophys. Res.: Atmos. 119, 2017–2031 (2014).
doi: 10.1002/2013JD020005
Pattyn, F. & Morlighem, M. The uncertain future of the Antarctic ice sheet. Science 367, 1331–1335 (2020).
pubmed: 32193321
doi: 10.1126/science.aaz5487
Rosier, S. H. R. et al. The tipping points and early warning indicators for Pine Island Glacier, West Antarctica. Cryosphere 15, 1501–1516 (2021).
doi: 10.5194/tc-15-1501-2021
Feldmann, J. & Levermann, A. Collapse of the West Antarctic ice sheet after local destabilization of the Amundsen Basin. Proc. Natl Acad. Sci. 112, 14191–14196 (2015).
pubmed: 26578762
pmcid: 4655561
doi: 10.1073/pnas.1512482112
Staal, A. et al. Forest-rainfall cascades buffer against drought across the Amazon. Nat. Clim. Change 8, 539–543 (2018).
doi: 10.1038/s41558-018-0177-y
Hansen, M. C. et al. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342, 850–853 (2013).
pubmed: 24233722
doi: 10.1126/science.1244693
Hansen, M. C. et al. The fate of tropical forest fragments. Sci. Adv. 6, eaax8574 (2020).
pubmed: 32195340
pmcid: 7065873
doi: 10.1126/sciadv.aax8574
Inderjit, Callaway, R. M. & Meron, E. Belowground feedbacks as drivers of spatial self-organization and community assembly. Phys. Life Rev. 38, 1–24 (2021).
pubmed: 34334324
doi: 10.1016/j.plrev.2021.07.002
Rietkerk, M. et al. Evasion of tipping in complex systems through spatial pattern formation. Science 374, eabj0359 (2021).
pubmed: 34618584
doi: 10.1126/science.abj0359
Buxton, J. E. et al. Quantitatively monitoring the resilience of patterned vegetation in the Sahel. Glob. Change Biol. 28, 571–587 (2021).
doi: 10.1111/gcb.15939
Druckenbrod, D. L. et al. Redefining temperate forest responses to climate and disturbance in the eastern United States: New insights at the mesoscale. Glob. Ecol. Biogeogr. 28, 557–575 (2019).
doi: 10.1111/geb.12876
Boulton, C. & Lenton, T. A new method for detecting abrupt shifts in time series. F1000Research 8, 746 (2019).
doi: 10.12688/f1000research.19310.1
Bernardino, P. N. et al. Global-scale characterization of turning points in arid and semi-arid ecosystem functioning. Glob. Ecol. Biogeogr. 29, 1230–1245 (2020).
doi: 10.1111/geb.13099
Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E. & Boike, J. Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nat. Commun. 9, 5423 (2018).
pubmed: 30575717
pmcid: 6303350
doi: 10.1038/s41467-018-07663-3
Kumar, S. S. et al. Alternative vegetation states in tropical forests and Savannas: the search for consistent signals in diverse remote sensing data. Remote Sens. 11, 815 (2019).
doi: 10.3390/rs11070815
Zeng, Y. et al. Towards a traceable climate service: assessment of quality and usability of essential climate variables. Remote Sens. 11, 1186 (2019).
doi: 10.3390/rs11101186
Duveiller, G. et al. Revealing the widespread potential of forests to increase low level cloud cover. Nat. Commun. 12, 4337 (2021).
pubmed: 34267204
pmcid: 8282670
doi: 10.1038/s41467-021-24551-5
Deng, Z. et al. Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions. Earth Syst. Sci. Data 14, 1639–1675 (2022).
doi: 10.5194/essd-14-1639-2022
Sorg, A., Bolch, T., Stoffel, M., Solomina, O. & Beniston, M. Climate change impacts on glaciers and runoff in Tien Shan (Central Asia). Nat. Clim. Change 2, 725–731 (2012).
doi: 10.1038/nclimate1592
Watson, S. C. L. et al. Does agricultural intensification cause tipping points in ecosystem services? Landsc. Ecol. 36, 3473–3491 (2021).
doi: 10.1007/s10980-021-01321-8
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C. & Vilà-Guerau de Arellano, J. Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci. 7, 345–349 (2014).
doi: 10.1038/ngeo2141
Reichstein, M. et al. Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis. Glob. Change Biol. 13, 634–651 (2007).
doi: 10.1111/j.1365-2486.2006.01224.x
Witte, J. C. et al. NASA A-Train and Terra observations of the 2010 Russian wildfires. Atmos. Chem. Phys. 11, 9287–9301 (2011).
doi: 10.5194/acp-11-9287-2011
Shaposhnikov, D. et al. Mortality related to air pollution with the Moscow heat wave and wildfire of 2010. Epidemiology 25, 359–364 (2014).
pubmed: 24598414
pmcid: 3984022
doi: 10.1097/EDE.0000000000000090
Hunt, E. et al. Agricultural and food security impacts from the 2010 Russia flash drought. Weather Clim. Extremes 34, 100383 (2021).
doi: 10.1016/j.wace.2021.100383
Kopp, R. E., Shwom, R. L., Wagner, G. & Yuan, J. Tipping elements and climate–economic shocks: Pathways toward integrated assessment. Earth’s Future 4, 346–372 (2016).
doi: 10.1002/2016EF000362
Milkoreit, M. Social tipping points everywhere?—Patterns and risks of overuse. WIREs Clim. Change 14, e813 (2022).
doi: 10.1002/wcc.813
Mortimer, C. et al. Benchmarking algorithm changes to the Snow CCI+ snow water equivalent product. Remote Sens. Environ. 274, 112988 (2022).
doi: 10.1016/j.rse.2022.112988
Paul, S., Hendricks, S., Ricker, R., Kern, S. & Rinne, E. Empirical parametrization of Envisat freeboard retrieval of Arctic and Antarctic sea ice based on CryoSat-2: progress in the ESA Climate Change Initiative. Cryosphere 12, 2437–2460 (2018).
doi: 10.5194/tc-12-2437-2018
Wissel, C. A universal law of the characteristic return time near thresholds. Oecologia 65, 101–107 (1984). Pioneering study of the relationship between linear stability and recovery rate, which is at the heart of the theory underlying resilience monitoring.
pubmed: 28312117
doi: 10.1007/BF00384470
De Keersmaecker, W. et al. Evaluating recovery metrics derived from optical time series over tropical forest ecosystems. Remote Sens. Environ. 274, 112991 (2022).
doi: 10.1016/j.rse.2022.112991
Kubo, R. The fluctuation-dissipation theorem. Rep. Prog. Phys. 29, 255–284 (1966).
doi: 10.1088/0034-4885/29/1/306
De Keersmaecker, W. et al. How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems. Glob. Change Biol. 20, 2149–2161 (2014). Rigorously examines how different remote sensing data quality issues affect different ecosystem stability metrics.
doi: 10.1111/gcb.12495
Forzieri, G., Dakos, V., McDowell, N. G., Ramdane, A. & Cescatti, A. Emerging signals of declining forest resilience under climate change. Nature 608, 534–539 (2022).
pubmed: 35831499
pmcid: 9385496
doi: 10.1038/s41586-022-04959-9
De Keersmaecker, W. et al. A model quantifying global vegetation resistance and resilience to short-term climate anomalies and their relationship with vegetation cover. Glob. Ecol. Biogeogr. 24, 539–548 (2015). Pioneering study of global vegetation resilience in response to drought and temperature anomalies utilising remotely sensed vegetation data.
doi: 10.1111/geb.12279
Liu, Y., Kumar, M., Katul, G. G. & Porporato, A. Reduced resilience as an early warning signal of forest mortality. Nat. Clim. Change 9, 880–885 (2019).
doi: 10.1038/s41558-019-0583-9
King, M. D. et al. Dynamic ice loss from the Greenland ice sheet driven by sustained glacier retreat. Commun. Earth Environ. 1, 1 (2020).
doi: 10.1038/s43247-020-0001-2
Khan, S. A. et al. Accelerating ice loss from peripheral glaciers in North Greenland. Geophys. Res. Lett. 49, e2022GL098915 (2022).
pubmed: 35865910
pmcid: 9286807
doi: 10.1029/2022GL098915
Michel, S. L. L. et al. Early warning signal for a tipping point suggested by a millennial Atlantic Multidecadal Variability reconstruction. Nat. Commun. 13, 5176 (2022).
pubmed: 36056010
pmcid: 9440003
doi: 10.1038/s41467-022-32704-3
Sgubin, G., Swingedouw, D., Drijfhout, S., Mary, Y. & Bennabi, A. Abrupt cooling over the North Atlantic in modern climate models. Nat. Commun. 8, 14375 (2017). Identifies a tipping point of deep convection collapse in the North Atlantic subpolar gyre occurring in several climate models at low levels of global warming.
Knudby, A., Jupiter, S., Roelfsema, C., Lyons, M. & Phinn, S. Mapping coral reef resilience indicators using field and remotely sensed data. Remote Sens. 5, 1311–1334 (2013).
doi: 10.3390/rs5031311
Tantet, A., van der Burgt, F. R. & Dijkstra, H. A. An early warning indicator for atmospheric blocking events using transfer operators. Chaos: Interdiscip. J. Nonlinear Sci. 25, 036406 (2015).
doi: 10.1063/1.4908174
Lenton, T. M. Early warning of climate tipping points. Nat. Clim. Change 1, 201–209 (2011).
doi: 10.1038/nclimate1143
Turner, M. G. et al. Climate change, ecosystems and abrupt change: science priorities. Philos. Trans. R. Soc. B: Biol. Sci. 375, 20190105 (2020).
doi: 10.1098/rstb.2019.0105
Arani, B. M. S., Carpenter, S. R., Lahti, L., Nes, E. H. V. & Scheffer, M. Exit time as a measure of ecological resilience. Science 372, eaay4895 (2021).
pubmed: 34112667
doi: 10.1126/science.aay4895
Hassanibesheli, F., Boers, N. & Kurths, J. Reconstructing complex system dynamics from time series: a method comparison. N. J. Phys. 22, 073053 (2020).
doi: 10.1088/1367-2630/ab9ce5
Gilarranz, L. J., Narwani, A., Odermatt, D., Siber, R. & Dakos, V. Regime shifts, trends, and variability of lake productivity at a global scale. Proc. Natl Acad. Sci. USA 119, e2116413119 (2022).
pubmed: 35994657
pmcid: 9436327
doi: 10.1073/pnas.2116413119
van Nes, E. H. & Scheffer, M. Implications of spatial heterogeneity for catastrophic regime shifts in ecosystems. Ecology 86, 1797–1807 (2005).
doi: 10.1890/04-0550
Bathiany, S., Claussen, M. & Fraedrich, K. Detecting hotspots of atmosphere-vegetation interaction via slowing down—Part 1: a stochastic approach. Earth Syst. Dynam. 4, 63–78 (2013).
doi: 10.5194/esd-4-63-2013
Boers, N., Marwan, N., Barbosa, H. M. J. & Kurths, J. A deforestation-induced tipping point for the South American monsoon system. Sci. Rep. 7, 41489 (2017).
pubmed: 28120928
pmcid: 5264177
doi: 10.1038/srep41489
Claussen, M., Bathiany, S., Brovkin, V. & Kleinen, T. Simulated climate–vegetation interaction in semi-arid regions affected by plant diversity. Nat. Geosci. 6, 954–958 (2013).
doi: 10.1038/ngeo1962
Guttal, V. & Jayaprakash, C. Spatial variance and spatial skewness: leading indicators of regime shifts in spatial ecological systems. Theor. Ecol. 2, 3–12 (2009). Uses a spatial ecological model to demonstrate the potential for spatial early warning indicators of an approaching tipping point.
doi: 10.1007/s12080-008-0033-1
Kéfi, S. et al. Early warning signals of ecological transitions: methods for spatial patterns. PLoS ONE 9, e92097 (2014).
pubmed: 24658137
pmcid: 3962379
doi: 10.1371/journal.pone.0092097
Nijp, J. J. et al. Spatial early warning signals for impending regime shifts: a practical framework for application in real-world landscapes. Glob. Change Biol. 25, 1905–1921 (2019).
doi: 10.1111/gcb.14591
Eby, S., Agrawal, A., Majumder, S., Dobson, A. P. & Guttal, V. Alternative stable states and spatial indicators of critical slowing down along a spatial gradient in a savanna ecosystem. Glob. Ecol. Biogeogr. 26, 638–649 (2017).
doi: 10.1111/geb.12570
Majumder, S., Tamma, K., Ramaswamy, S. & Guttal, V. Inferring critical thresholds of ecosystem transitions from spatial data. Ecology 100, e02722 (2019).
pubmed: 31051050
doi: 10.1002/ecy.2722
Hegerl, G. C. et al. Toward consistent observational constraints in climate predictions and projections. Front. Clim. 3, 678109 (2021).
Shiogama, H., Watanabe, M., Kim, H. & Hirota, N. Emergent constraints on future precipitation changes. Nature 602, 612–616 (2022).
pubmed: 35197617
doi: 10.1038/s41586-021-04310-8
Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).
pubmed: 23389447
doi: 10.1038/nature11882
Keenlyside, N. S., Latif, M., Jungclaus, J., Kornblueh, L. & Roeckner, E. Advancing decadal-scale climate prediction in the North Atlantic sector. Nature 453, 84–88 (2008).
pubmed: 18451859
doi: 10.1038/nature06921
Counillon, F., Sakov, P. & Bertino, L. Application of a hybrid EnKF-OI to ocean forecasting. Ocean Sci. 5, 389–401 (2009).
doi: 10.5194/os-5-389-2009
Smith, D. M. et al. North Atlantic climate far more predictable than models imply. Nature 583, 796–800 (2020).
pubmed: 32728237
doi: 10.1038/s41586-020-2525-0
Séférian, R. et al. Multiyear predictability of tropical marine productivity. Proc. Natl Acad. Sci. USA 111, 11646–11651 (2014).
pubmed: 25071174
pmcid: 4136572
doi: 10.1073/pnas.1315855111
Li, H., Ilyina, T., Müller, W. A. & Sienz, F. Decadal predictions of the North Atlantic CO2 uptake. Nat. Commun. 7, 11076 (2016).
pubmed: 27026490
pmcid: 4820896
doi: 10.1038/ncomms11076
Kriegler, E., Hall, J. W., Held, H., Dawson, R. & Schellnhuber, H. J. Imprecise probability assessment of tipping points in the climate system. Proc. Natl Acad. Sci. USA 106, 5041–5046 (2009).
pubmed: 19289827
pmcid: 2657590
doi: 10.1073/pnas.0809117106
Bakker, P. et al. Fate of the Atlantic meridional overturning circulation: strong decline under continued warming and Greenland melting. Geophys. Res. Lett. 43, 12,252–212,260 (2016).
doi: 10.1002/2016GL070457
Madsen, M. S. et al. The role of an interactive Greenland ice sheet in the coupled climate-ice sheet model EC-Earth-PISM. Clim. Dyn. 59, 1189–1211 (2022).
doi: 10.1007/s00382-022-06184-6
Stouffer, R. J. et al. Investigating the causes of the response of the thermohaline circulation to past and future climate changes. J. Clim. 19, 1365–1387 (2006).
doi: 10.1175/JCLI3689.1
Swingedouw, D. et al. Decadal fingerprints of freshwater discharge around Greenland in a multi-model ensemble. Clim. Dyn. 41, 695–720 (2013).
doi: 10.1007/s00382-012-1479-9
Swingedouw, D. et al. AMOC Recent and Future Trends: A crucial role for oceanic resolution and Greenland melting? Front. Clim. 4, (2022). Shows that Greenland ice sheet melt can significantly weaken deep convection in the North Atlantic subpolar gyre, but this is not captured in the latest coupled climate models.
Mosblech, N. A. S. et al. North Atlantic forcing of Amazonian precipitation during the last ice age. Nat. Geosci. 5, 817–820 (2012).
doi: 10.1038/ngeo1588
Jomelli, V. et al. In-phase millennial-scale glacier changes in the tropics and North Atlantic regions during the Holocene. Nat. Commun. 13, 1419 (2022).
pubmed: 35301286
pmcid: 8930989
doi: 10.1038/s41467-022-28939-9
Ciemer, C., Winkelmann, R., Kurths, J. & Boers, N. Impact of an AMOC weakening on the stability of the southern Amazon rainforest. Eur. Phys. J. Spec. Top. 230, 3065–3073 (2021).
doi: 10.1140/epjs/s11734-021-00186-x
Good, P., Boers, N., Boulton, C. A., Lowe, J. A. & Richter, I. How might a collapse in the Atlantic Meridional Overturning Circulation affect rainfall over tropical South America? Clim. Resil. Sustain. 1, e26 (2022).
Runge, J. Causal network reconstruction from time series: From theoretical assumptions to practical estimation. Chaos: Interdiscip. J. Nonlinear Sci. 28, 075310 (2018).
doi: 10.1063/1.5025050
Runge, J. et al. Inferring causation from time series in Earth system sciences. Nat. Commun. 10, 2553 (2019). Excellent introduction to methods of inferring causal interactions in the Earth system from time series data.
pubmed: 31201306
pmcid: 6572812
doi: 10.1038/s41467-019-10105-3
Reich, B. J. et al. A review of spatial causal inference methods for environmental and epidemiological applications. Int. Stat. Rev. 89, 605–634 (2021).
pubmed: 37197445
pmcid: 10187770
doi: 10.1111/insr.12452
Pérez-Suay, A. & Camps-Valls, G. Causal inference in geoscience and remote sensing from observational data. IEEE Trans. Geosci. Remote Sens. 57, 1502–1513 (2019).
doi: 10.1109/TGRS.2018.2867002
Kretschmer, M., Coumou, D., Donges, J. F. & Runge, J. Using causal effect networks to analyze different Arctic drivers of midlatitude winter circulation. J. Clim. 29, 4069–4081 (2016).
doi: 10.1175/JCLI-D-15-0654.1
Papagiannopoulou, C. et al. A non-linear Granger-causality framework to investigate climate–vegetation dynamics. Geosci. Model Dev. 10, 1945–1960 (2017).
doi: 10.5194/gmd-10-1945-2017
Reygadas, Y., Jensen, J. L. R., Moisen, G. G., Currit, N. & Chow, E. T. Assessing the relationship between vegetation greenness and surface temperature through Granger causality and Impulse-Response coefficients: a case study in Mexico. Int. J. Remote Sens. 41, 3761–3783 (2020).
doi: 10.1080/01431161.2019.1711241
Sugihara, G. et al. Detecting causality in complex ecosystems. Science 338, 496–500 (2012).
pubmed: 22997134
doi: 10.1126/science.1227079
Smith, T. et al. Reliability of resilience estimation based on multi-instrument time series. Earth Syst. Dyn. 14, 173–183 (2023).
doi: 10.5194/esd-14-173-2023
Bury, T. M. et al. Deep learning for early warning signals of regime shifts. Proc. Natl Acad. Sci. USA 118, e2106140118 (2021).
pubmed: 34544867
pmcid: 8488604
doi: 10.1073/pnas.2106140118
Dylewsky, D. et al. Universal early warning signals of phase transitions in climate systems. J. R. Soc. Interface 20, 20220562 (2023).
pubmed: 37015262
pmcid: 10072946
doi: 10.1098/rsif.2022.0562
Bathiany, S., Hidding, J. & Scheffer, M. Edge detection reveals abrupt and extreme climate events. J. Clim. 33, 6399–6421 (2020).
doi: 10.1175/JCLI-D-19-0449.1
Popp, T. et al. Consistency of satellite climate data records for Earth system monitoring. Bull. Am. Meteorol. Soc. 101, E1948–E1971 (2020).
doi: 10.1175/BAMS-D-19-0127.1
Plummer, S., Lecomte, P. & Doherty, M. The ESA Climate Change Initiative (CCI): a European contribution to the generation of the Global Climate Observing System. Remote Sens. Environ. 203, 2–8 (2017). Describes how satellite observations are used to document essential climate variables.
doi: 10.1016/j.rse.2017.07.014
White, H. J. et al. Quantifying large-scale ecosystem stability with remote sensing data. Remote Sens. Ecol. Conserv. 6, 354–365 (2020).
pubmed: 33133633
pmcid: 7582121
doi: 10.1002/rse2.148
Bousquet, E. et al. Influence of surface water variations on VOD and biomass estimates from passive microwave sensors. Remote Sens. Environ. 257, 112345 (2021).
doi: 10.1016/j.rse.2021.112345
Tao, S. et al. Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts. Proc. Natl Acad. Sci. USA 119, e2116626119 (2022).
pubmed: 36067321
pmcid: 9477241
doi: 10.1073/pnas.2116626119
Beaugrand, G. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Change 9, 237–243 (2019).
doi: 10.1038/s41558-019-0420-1
Green, H. L., Findlay, H. S., Shutler, J. D., Land, P. E. & Bellerby, R. G. J. Satellite Observations Are Needed to Understand Ocean Acidification and Multi-Stressor Impacts on Fish Stocks in a Changing Arctic Ocean. Front. Marine Sci. 8, 635797 (2021).
Melet, A. et al. Earth observations for monitoring marine coastal hazards and their drivers. Surv. Geophys. 41, 1489–1534 (2020).
doi: 10.1007/s10712-020-09594-5
Foo, S. A. & Asner, G. P. Scaling up coral reef restoration using remote sensing technology. Front. Marine Sci. 6, 79 (2019).
Staal, A., Dekker, S. C., Hirota, M. & van Nes, E. H. Synergistic effects of drought and deforestation on the resilience of the south-eastern Amazon rainforest. Ecol. Complex. 22, 65–75 (2015).
doi: 10.1016/j.ecocom.2015.01.003
Zemp, D. C. et al. Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks. Nat. Commun. 8, 14681 (2017).
pubmed: 28287104
pmcid: 5355804
doi: 10.1038/ncomms14681
van Belzen, J. et al. Vegetation recovery in tidal marshes reveals critical slowing down under increased inundation. Nat. Commun. 8, 15811 (2017).
pubmed: 28598430
pmcid: 5472773
doi: 10.1038/ncomms15811
Alibakhshi, S., Groen, T., Rautiainen, M. & Naimi, B. Remotely-sensed early warning signals of a critical transition in a wetland ecosystem. Remote Sens. 9, 352 (2017).
doi: 10.3390/rs9040352
Tehrani, N. A. & Janalipour, M. Predicting ecosystem shift in a Salt Lake by using remote sensing indicators and spatial statistics methods (case study: Lake Urmia basin). Environ. Eng. Res. 26, 200225–200220 (2021).
Lees, K. J. et al. Using remote sensing to assess peatland resilience by estimating soil surface moisture and drought recovery. Sci. Total Environ. 761, 143312 (2021).
pubmed: 33267996
doi: 10.1016/j.scitotenv.2020.143312
Lees, K. J., Buxton, J., Boulton, C. A., Abrams, J. F. & Lenton, T. M. Using satellite data to assess management frequency and rate of regeneration on heather moorlands in England as a resilience indicator. Environ. Res. Commun. 3, 085003 (2021).
doi: 10.1088/2515-7620/ac1a5f
Miner, K. R. et al. Permafrost carbon emissions in a changing Arctic. Nat. Rev. Earth Environ. 3, 55–67 (2022).
doi: 10.1038/s43017-021-00230-3
Talib, J. et al. The sensitivity of the West African monsoon circulation to intraseasonal soil moisture feedbacks. Q. J. R. Meteorol. Soc. 148, 1709–1730 (2022).
doi: 10.1002/qj.4274
IPCC. Global Warming of 1.5 °C. An IPCC Special Report on the Impacts of Global Warming of 1.5 °C above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. (IPCC, 2018).
IPCC. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. (IPCC, 2019).
IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. (Cambridge University Press, 2021).
Boulton, C. A. & Lenton, T. M. Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change. Proc. Natl Acad. Sci. USA 112, 11496–11501 (2015).
pubmed: 26324900
pmcid: 4577159
doi: 10.1073/pnas.1501781112