2024
Acceleration of daily land temperature extremes and correlations with surface energy fluxes, Huntingford, C et al, npj Climate and Atmospheric Science, 7, Art. Num. 84 (2024), https://doi.org/10.1038/s41612-024-00626-0
Vegetation greenness in 2023, Li, X. et al., Nature Reviews Earth & Environment, 5, 241-243 (2024), https://doi.org/10.1038/s43017-024-00543-z
Integrating ecosystem water demands into drought monitoring and assessment under climate change, Cui, J. et al., Nature Water, 2, 215-218 (2024), https://doi.org/10.1038/s44221-024-00217-6
2023
CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output, Robinson, E.L. et al., Earth System Science Data, 15, 5371-5401 (2023), https://doi.org/essd-15-5371-2023
Committed global warming risks triggered multiple climate tipping points, Abrams, J.F., Huntingford, C. et al, Earth's Future, 11, e2022EF003250, (2023), https://doi.org/10.1029/2022EF003250
Potential impacts of rapidly changing european use of fossil fuels on global warming, Huntingford et al., 5, 091002 Environmental Research Communications, (2023), https://doi.org/10.1088/2515-7620/acf3d7
CO2 fertilization contributed more than half of the observed forest biomass increase in northern extra-tropical land, He, Y. et al., Global Change Biology, (2023), https://doi.org/10.1111/gcb.16806
Autumn canopy senescence has slowed down with global warming since the 1980s in the Northern Hemisphere, Zhang, Y. et al., Communications Earth & Environment, 4, 173 (2023), https://doi.org/10.1038/s43247-023-00835-0
Emergent constraints for the climate system as effective parameters of bulk differential equations, Huntingford, C. et al., Earth System Dynamics, 433-442 (2023), https://doi.org/10.5194/esd-14-433-2023
Global variations in critical drought thresholds that impact vegetation, Li, X et al., National Science Review, (2023), https://doi.org/10.1093/nsr/nwad049
Drivers and impacts of Eastern African rainfall variability. Palmer, P.I. et al., Nature Reviews Earth & Environment, (2023), https://doi.org/10.1038/s43017-023-00397-x
Seeking more robust early warning signals for climate tipping points: the ratio of spectra method (ROSA). Clarke, J. ., Huntingford, C., Ritchie, P.D.L. and Cox, P.M., 18, Art Num: 035006, Environmental Research Letters, (2023), https://doi.org/10.1088/1748-9326/acbc8d
The detection and attribution of extreme reductions in vegetation growth across the global land surface. Yang, Y., Munson, S.M., Huntingford, C. et al, Global Change Biology, (2023), https://doi.org/10.111/gcb.16595
A new precipitation emulator (PREMU v1.0) for lower-complexity models. Liu, G., Peng, S., Huntingford, C. and Xi, Y, Geoscientific Model Development, (2023), https://doi.org/10.5194/gmd-16-1277-2023
2022
Global water availability boosted by vegetation-driven changes in atmospheric moisture transport. Cui, J., Lian, X., Huntingford, C., Gimeno, L., Wang, T., Ding, J., He, M., Xu, H., Chen, A., Gentine, P. and Piao, S., Nature Geoscience, (2022), https://doi.org/10.1038/s41561-022-01061-7
Resilience of UK crop yields to compound climate change. Slater, L.J., Huntingford, C., Pywell, R.F., Redhead, J.W. and Kendon, E.J., Earth System Dynamics, 13 1377-1396 (2022), https://doi.org/10.5194/esd-13-1377-2022
Increases in the temperature seasonal cycle indicate long-term drying trends in Amazonia. Ritchie, P.D.L. et al., Communications Earth & Environment, 3 199 (2022), https://doi.org/10.1038/s43247-022-00528-0
Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation. Oliver, R.J. et al., Geoscientific Model Development, 15 5567-5592 (2022), https://doi.org/10.5194/gmd-15-5567-2022
Amplified warming from physiological responses to carbon dioxide reduces the potential of vegetation for climate change mitigation. He, M., Piao, S., Huntingford, C. et al., Communications Earth & Environment, 3 160 (2022), https://doi.org/10.1038/s43247-022-00489-4
Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability. Wang, K. et al., Nature Communications, 13 3469 (2022), https://doi.org/10.1038/s41467-022-31175-w
Thawing permafrost as a nitrogen fertiliser: implications for climate feedbacks. Burke, E., Chadburn, S. and Huntingford, C. Nitrogen, 3, 353-375 (2022), https://doi.org/10.3390/nitrogen3020023
Reduced global fire activity due to human demography slows global warming by enhanced land carbon uptake. Wu, C., Sitch, S., Huntingford, C., Mercado, L.M. et al Proceedings of the National Academy of Sciences of the United States of America, 119, e2101186119 (2022), https://doi.org/10.1073/pnas/2101186119
The 2021 western North America heat wave among the most extreme events ever recorded globally. Thompson, V., Kennedy-Asser, A.T., Vosper, E., Lo, Y.T.E., Huntingford, C. et al Science Advances, 8, eabm6860 (2022), https://doi.org/10.1126/sciadv.abm6860
Nitrogen cycle impacts on CO2 fertilisation and climate forcing of land carbon stores. Huntingford, C., Burke, E.J., Jones, C.D., Jeffers, E.S. and Wiltshire, A.J. Environmental Research Letters, 17, 044072 (2022), https://doi.org/10.1088/1748-9326/ac6148
A New Modelling Approach to Adaptation-Mitigation in the Land System. Maire, J., Alexander, P., Anthoni, P., Huntingford, C., Pugh, T. A. M., Rabin, S., Rounsevell, M., & Arneth, A. (2022). In Climate Adaptation Modelling (Springer Climate (SPCL)). p133-140. Springer. https://doi.org/10.1007/978-3-030-86211-4_16
Impact of merging of historical and future climate data sets on land carbon cycle projections for South America. Huntingford, C., Sitch, S.A. and O'Sullivan, M., Climate Resilience and Sustainability, 1, e24 (2022), https://doi.org/10.1002/cli2.24
2021
Climate change and Lyme disease. Cox, P., Huntingford, C., Sparey, M. and Nuttall, P. (2021). In Climate, ticks and disease (CABI). p18-25. https://doi.org/10.1079/9781789249637.0003
Strong direct and indirect influences of climate change on water yield confirmed by the Budyko framework. Yang, H., Xu, H., Huntingford, C., Ciais, P. and Piao, S., Geography and Sustainability, 2, 281-287 (2021), https://doi.org/10.1016/j.geosus.2021.11.001
Constraints on estimating the CO2 fertilization effect emerge. Huntingford, C. and Oliver, R.J., Nature, 600, 224-225 (2021), https://doi.org/10.1038/d41586-021-03560-w (This is a News and Views document)
The Montreal Protocol protects the terrestrial carbon sink. Young, P.J., Harper, A.B., Huntingford, C. et al., Nature, 596, 384-388 (2021), https://doi.org/10.1038/s41586-021-03737-3
Optimal COVID-19 vaccine sharing between two nations that also have extensive travel exchanges. Huntingford, C., Rawson, T. and Bonsall, M.B., Frontiers in Public Health, 9: 633144 (2021), https://doi.org/10.3389/fpubh.2021.633144
Vegetation response to rising CO2 amplifies contrasts in water resources between global wet and dry land areas. Cui, J., Yang, H., Huntingford, C., Kooperman, G.J., Lian, X., He, M. and Piao, S, Geophysical Research Letters, 48, e2021GL094293 (2021), https://doi.org/10.1029/2021GL094293
Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements, Harper, A.B. et al., Geoscientific Model Development, 14, 3269-3294 (2021), https://doi.org/10.5194/gmd-14-3269-2021
Unusual characteristics of the carbon cycle during the 2015-2016 El Niño. Wang, K. et al., Global Change Biology, (2021), https://doi.org/10.1111/gcb.15669
Emergent constraints on climate sensitivities. Williamson, M.S. et al., Reviews of Modern Physics, 93, 025004 (2021), https://doi.org/10.1103/RevModPhys.93.025004
Regional variation in the effectiveness of methane-based and land-based climate mitigation options. Hayman, G.D. et al., Earth System Dynamics 12, 513-544 (2021), https://doi.org/10.5194/esd-12-513-2021
Overshooting tipping point thresholds in a changing climate. Ritchie, P.D.L., Clarke, J.J., Cox, P.M. and Huntingford, C., Nature 592, 517-523 (2021), https://doi.org/10.1038/s41586-021-03263-2
The compost bomb instability in the continuum limit. Clarke, J., Huntingford, C., Ritchie, P. and Cox, P., The European Physical Journal (2021), https://doi.org/10.1140/epjs/s11734-021-00013-3
Historical and future global burned area with changing climate and human demography. Wu, C., Venevsky, S., Sitch, S., Mercado, L.M., Huntingford, C. and Staver, A.C., One Earth 4, 517-530 (2021), https://doi.org/10.1016/j.oneear.2021.03.002
Multifaceted characteristics of dryland aridity changes in a warming world. Lian, X., Piao, S., Chen, A., Huntingford, C., et al., Nature Reviews Earth & Environment (2021), https://doi.org/10.1038/s43017-021-00144-0
Seasonal biological carryover dominates northern vegetation growth. Lian, X., Piao, S., Chen, A., Wang, K., Li, X., Buermann, W., Huntingford, C., Peñuelas, J., Xu, H. and Myneni, R.B., Nature Communications, 12, 983 (2021), https://doi.org/10.1038/s41467-021-21223-2
Technical note: Low meteorological influence found in 2019 Amazonia fires. Kelley, D.I. et al., Biogeosciences, 18, 787-804 (2021), https://doi.org/10.5194/bg-18-787-2021
Method uncertainty is essential for reliable confidence statements of precipitation projections. Uhe, P. et al., Journal of Climate, 34, 1227-1240 (2021), https://doi.org/10.1175/JCLI-D-20-0289.1
Converging towards a common representation of large-scale photosynthesis. Huntingford, C. and Oliver, R.J. Global Change Biology , 27, 716-718 (2021), https://doi.org/10.1111/gcb.15398
2020
Temporary "Circuit Breaker" Lockdowns could effectively delay a COVID-19 second wave infection peak to early spring. Rawson, T., Huntingford, C. and Bonsall, M.B., Frontiers in Public Health, (2020), https://doi.org/10.3389/fpubh.2020.614945
Vegetation forcing modulates global land monsoon and water resources in a CO2-enriched climate. Cui, J., Piao, S., Huntingford, C., Wang, X., Lian, X., Chevuturi, A., Turner, A.G. and Kooperman, G.J. Nature Communications, 11, 5184 (2020), https://doi.org/10.1038/s41467-020-18992-7
Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models. Argles, A.P.K. et al., Geoscientific Model Development, 13, 4067-4089 (2020), https://doi.org/10.5194/gmd-13-4067-2020
CMIP6 climate models imply high committed warming. Huntingford, C., Williamson, M.S. and Nijsse, F.J.M.M., Climatic Change, 162, 1515-1520 (2020), https://doi.org/10.1007/s10584-020-02849-5
How and when to end the COVID-19 lockdown: an optimization approach. Rawson, T., Brewer, T., Veltcheva, D., Huntingford, C. and Bonsall, M.B., Frontiers in Public Health, 8, (2020), https://doi.org/10.3389/fpubh.2020.00262
Quantifying the controls on evapotranspiration partitioning in the highest alpine meadow ecosystem. Cui, J. et al., Water Resources Research, 55, (2020), https://doi.org/10.1029/2019WR024815
Validation of demographic equilibrium theory against tree-size distributions and biomass density in Amazonia. Moore, J.R. et al., Biogeosciences, 17, 1013-1032 (2020), https://doi.org/10.5194/bg-17-1013-2020
Summer soil drying exacerbated by earlier spring greening of northern vegetation. Lian, X. et al., Science Advances, 6, eaax0255 (2020), https://doi.org/10.1126/sciadv.aax0255
2019
Compensatory climate effects link trends in global runoff to rising atmospheric CO2 concentration. Yang, H. et al., Environmental Research Letters, 14, 124075 (2019), https://doi.org/10.1088/1748-9326/ab5c6f
Machine learning and artificial intelligence to aid climate change research and preparedness. Huntingford, C. et al., Environmental Research Letters, 14, 124007 (2019), https://doi.org/10.1088/1748-9326/ab4e55
Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization. Liu, Y. et al., Nature Geoscience, 12, 809-814 (2019), https://doi.org/10.1038/s41561-019-0436-1
Significant feedbacks of wetland methane release on climate change and the causes of their uncertainty. Gedney, N. et al., Environmental Research Letters, 14, 084027 (2019), https://doi.org/10.1088/1748-9326/ab2726
How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0? Williams, K.E. et al., Geoscientific Model Development, 12, 3207-3240 (2019), https://doi.org/10.5194/gmd-12-3207-2019
Decadal global temperature variability increases strongly with climate sensitivity. Nijsse, F.J.M.M. et al., Nature Climate Change, 9, 598-601 (2019), https://doi.org/10.1038/s41558-019-0527-4
The day the 2003 European heatwave record was broken. Mitchell, D et al., The Lancet Planetary Health, 3, e290-e292 (2019), https://doi.org/10.1016/S2542-5196(19)30106-8
Assessing changes in risk of amplified planetary waves in a warming world. Huntingford, C et al., Atmospheric Science Letters, 20, e929 (2019), https://doi.org/10.1002/asl.929
Progressing emergent constraints on future climate change. Hall, A et al., Nature Climate Change, 9, 269-278 (2019), https://doi.org/10.1038/s41558-019-0436-6
Strong but intermittent spatial covariations in tropical land temperature. Yang, H. et al., Geophysical Research Letters, 46 (2019), https://doi.org/10.1029/2018GL080463
2018
A large committed long-term sink of carbon due to vegetation dynamics. Pugh, T.A.M. et al., Earth's Future, 6 (2018), https://doi.org/10.1029/2018EF000935
Changing the retention properties of catchments and their influence on runoff under climate change. Yang, H. et al., Environmental Research Letters, 13, 094019 (2018), https://doi.org/10.1088/1748-9326/aadd32
Technical note: A simple theoretical model framework to describe plant stomatal "sluggishness" in response to elevated ozone concentrations. Huntingford, C. et al., Biogeosciences, 15, 5415-5422 (2018), http://doi.org/10.5194/bg-15-5415-2018
Equilibrium forest demography explains the distribution of tree sizes across North America. Moore, J.R. et al., Environmental Research Letters, 13, 084019 (2018), http://doi.org/10.1088/1748-9326aad6d1
Land-use emissions play a critical role in land-based mitigation for Paris climate targets. Harper, A.B. et al., Nature Communications, 9, 2938 (2018), http://doi.org/10.1038/s41467-018-05340-z
Carbon budgets for 1.5 and 2°C targets lowered by natural wetland and permafrost feedbacks. Comyn-Platt, E et al., Nature Geoscience, 11, 568-573 (2018), http://doi.org/10.1038/s41561-018-0174-9
Partitioning global land evapotranspiration using CMIP5 models constrained by observations. Lian, X et al., Nature Climate Change 8, 640-646 (2018), http://doi.org/10.1038/s41558-018-0207-9
Increased importance of methane reduction for a 1.5 degree target. Collins, W.J. et al., Environmental Research Letters 13, 054003 (2018), https://doi.org/10.1088/1748-9326/aab89c
Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity. Mercado, L.M. et al., New Phytologist 218, 1462-1477 (2018), http://doi.org/10.1111/nph.15100
CO2 loss by permafrost thawing implies additional emissions reductions to limit warming to 1.5 or 2oC. Burke, E.J. et al., Environmental Research Letters 13, Art 024024 (2018), http://doi.org/10.1088/1748-9326/aaa138
Brief communication: Drought likelihood for East Africa. Yang, H. and Huntingford, C., Natural Hazards and Earth System Sciences 18, 491-497 (2018), http://doi.org/10.5194/nhess-18-491-2018
Climate pattern-scaling set for an ensemble of 22 GCMs - adding uncertainty to the IMOGEN version 2.0 impact system. Zelazowski, P. et al., Geoscientific Model Development 11, 541-560 (2018), https://doi.org/10.5194/gmd-11-541-2018
Emergent constraint on equilibrium climate sensitivity from global temperature variability. Cox, P.M. et al., Nature, 553, 319-322 (2018), https://doi.org/10.1038/nature25450
2017
Implications of improved representations of plant respiration in a changing climate. Huntingford, C. et al., Nature Communications 8 Art: 1602 (2017), https://doi.org/10.1038/s41467-017-01774-z
Climate variability: Picking apart climate models. Huntingford, C., Nature Climate Change (2017), https://doi.org/10.1038/nclimate3391
Flexible parameter-sparse global temperature time profiles that stabilise at 1.5 and 2.0ºC. Huntingford, C. et al., Earth System Dynamics 8, 617-626 (2017), https://doi.org/10.5194/esd-8-617-2017
Quantifying uncertainties of permafrost carbon-climate feedbacks. Burke, E.J. et al., Biogeosciences 14, 3051-3066 (2017), https://dx.doi.org/10.5194/bg-14-3051-2017
Compensatory water effects link yearly global land CO2 sink changes to temperature. Jung et al., Nature 541, 516-520 (2017), http://dx.doi.org/10.1038/nature20780
2016
Reply to Adams et al.: Empirical versus process-based approaches to modeling temperature responses of leaf respiration. Heskel et al., Proc Nat Academy Sciences 113, E5996-E5997 (2016), http://dx.doi.org/10.1073/pnas.1612904113
High chance that current atmospheric greenhouse concentrations commit to warmings greater than 1.5oC over land. Huntingford, C and Mercado, L.M., Scientific Reports 6, 30294, http://dx.doi.org/10.1038/srep30294
Attributing human mortality during extreme heat waves to anthropogenic climate change. Mitchell, D et al., Environmental Research Letters 11, Art Num 074006 (2016), http://iopscience.iop.org/article/10.1088/1748-9326/11/7/074006
Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations. Dekker, S.C. et al., Earth System Dynamics 7, 525-533 (2016), http://www.earth-syst-dynam.net/7/525/2016/
The dry season intensity as a key driver of NPP trends. Murray-Tortarolo, G et al., Geophysical Research Letters 43, 2632-2639 (2016), http://dx.doi.org/10.1002/2016GL068240
Convergence in the temperature response of leaf respiration across biomes and plant functional types. Heskel, M.A. et al., Proc Nat Academy Sciences 113, 3832-3837 (2016), http://dx.doi.org/10.1073/pnas.1520282113
Human influence on climate in the 2014 southern England winter floods and their impacts. Schaller, N. et al., Nature Climate Change, 6, 627-634 (2016), http://dx.doi.org/10.1038/nclimate2927
The impacts of climate change across the global: A multi-sectoral assessment. Arnell, N.W. et al., Climatic Change, 134, 457-474 (2016), http://dx.doi.org/10.1007/s10584-014-1281-2
Global-scale climate impact functions: the relationship between climate forcing and impact. Arnell, N.W. et al., Climatic Change, 134, 475-487 (2016), http://dx.doi.org/10.1007/s10584-013-1034-7
2015
More frequent moments in the climate change debate as emissions continue. Huntingford, C. and Friedlingstein, P. Environmental Research Letters 10 Art Num 121001 (2015) http://dx.doi.org/10.1088/1748-9326/10/12/121001
Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models. Drijfhout et al, Proc. Nat. Acad. Sciences (2015), http://www.pnas.org/content/early/2015/10/07/1511451112.abstract
Integrating effects of climate change and habitat fragmentation on drought-sensitive butterflies. Oliver et al., Nature Climate Change (2015), http://dx.doi.org/10.1038/nclimate2746
Multicriteria evaluation of discharge simulation in Dynamic Global Vegetation Models. Yang, H. et al., J Geophys. Res. Atmos, 120, (2015). http://dx.doi.org/10.1002/2015JD023129
The implications of carbon dioxide and methane exchange for the heavy mitigation RCP2.6 scenario under two metrics. Huntingford, C. et al,. Environmental Science and Policy, 51, p77-87, (2015). http://dx.doi.org/10.1016/j.envsci.2015.03.013
Reply to 'Driver of the 2013/14 winter floods in the UK'. Huntingford, C. et al. Nature Climate Change, 5, p491-492, (2015).
Water-use efficiency and transpiration across European forests during the anthropocene. Frank, D.C. et al., Nature Climate Change, 5, p579-583 (2015). http://dx.doi.org/10.1038/nclimate2614
Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. Atkin, O.K. et al., New Phytologist, 206, p614-636 (2015). http://dx.doi.org/10.1111/nph.13253
Combining the [ABA] and net photosynthesis-based model equations of stomatal conductance. Huntingford, C. et al., Ecological Modelling, 300, p81-88 (2015). http://dx.doi.org/10.1016/j.ecolmodel.2015.01.005
Recent trends and drivers of regional sources and sinks of carbon dioxide. Sitch, S. et al. Biogeosciences, 12, p653-679 (2015). http://dx.doi.org/10.5194/bg-12-653-2015
Benchmarking the seasonal cycle of CO2 fluxes simulated by terrestrial ecosystem models. Peng, S.S. et al. Global Biogeochemical Cycles, 29, p46-64 (2015). http://dx.doi.org/10.1002/2014GB004931
2014
Increasing the detectability of external influence on precipitation by correcting feature location in GCMs. Levy, A.A.L, Jenkinson, M., Ingram, W., Lambert, F.H., Huntingford, C. and Allen, M. J Geophysical Research - Atmospheres, 119, p12466-12478, (2014). http://dx.doi.org/10.1002/2014JD022358
Detection of solar dimming and brightening effects on Northern Hemisphere river flow. Gedney, N., Huntingford C., Weedon, G.P., Bellouin, N., Boucher, O. and Cox, P.M. Nature Geoscience, 7, p796-800, (2014). http://dx.doi.org/10.1038/NGEO2263
Evidence for a weakening relationship between interannual temperature variability and northern latitude vegetation activity. Piao, S.L. et al. Nature Communications, 5, (2014). http://dx.doi.org/10.1038/ncomms6018
Potential influences on the United Kingdom's floods of winter 2013/14. Huntingford, C. et al. Nature Climate Change, 4, p769-777 (2014). http://dx.doi.org/10.1038/NCLIMATE2314
Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration. Walker, A.P. et al., J Geophysical Research-Biogeosciences, 119, p937-964 (2014). http://dx.doi.org/10.1002/2013JG002553
Sensitivity of climate change detection and attribution to the characteriszation of internal climate variability. Imbers, J., Lopez, A., Huntingford, C. and Allen, M. J of Climate, 27, p3477-3491 (2014). http://dx.doi.org/10.1175/JCLI-D-12-00622.1
Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data. Hayman, G.D. et al,. Atmospheric Chemistry and Physics, 14, p13257-13280 (2014). http://dx.doi.org/10.5194/acp-14-13257-2014
Carbon cycle uncertainty in the Alaskan Arctic. Fisher, J.B. et al,. Biogeosciences, 11, p4271-4288 (2014). http://dx.doi.org/10.5194/bg-11-4271-2014
Complexity amd determining dangerous levels of climate impacts. Huntingford, C. Environmental Research Latters, 9, Art: 011001 (2014). http://dx.doi.org/10.1088/1748-9326/9/1/011001
2013
No increase in global temperature variability despite changing regional patterns. Chris Huntingford, Philip D Jones, Valerie N Livinia, Timothy M Lenton, Peter M Cox. Nature, 500, p327-+ (2013). http://dx.doi.org/10.1038/nature12310
Climate projection: Refining global warming projections. Chris Huntingford. Nature Climate Change, 8, p704-705 (2013). http://dx.doi.org/doi:10.1038/nclimate1964
Simulated resilience of tropical rainforests to CO2-induced climate change. Chris Huntingford et al, Nature Geoscience 6, p268-273. (2013). http://dx.doi.org/doi:10.1038/NGEO1741
Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Peter M Cox, David Pearson, Ben B Booth, Pierre Friedlingstein, Chris Huntingford, Chris D Jones & Catherine M Luke. Nature 494, p341-344 (2013). http://dx.doi.org/doi:10.1038/nature11882
The role of short-lived climate pollutants in meeting temperature goals. Bowerman, Niel H. A.; Frame, David J.; Huntingford, Chris; et al. Nature Climate Change 12, p1021-1024, (2013). http://dx.doi.org/10.1038/NCLIMATE2034
Earth Science: The timing of climate change. Huntingford. C., Mercado, L. and Post, E. Nature, 502, p174-175, (2013). http://dx.doi.org/10.1038/502174a
African tropical rainforest net carbon dioxide fluxes in the twentieth century. Fisher, J.B. et al. Phil Trans Roy Soc B, 368 (2013). http://dx.doi.org/10.1098/rstb.2012.0376
Explaining extreme events of 2012 from a climate perspective. Peterson, T.C. et al. Bulletin of the American Meteorological Society, 94, pS1-S74 (2013). http://dx.doi.org/10.1175/BAMS-D-13-00085.1
Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Piao et al., Global Change Biology, 19, p2117-2132 (2013). http://dx.doi.org/10.1111/gcb.12187
Testing the robustness of the anthropogenic climate change detection statements using different empirical models. Imbers, J., Lopez, A., Huntingford, C. and Allen, M.R. J Geophysical Research-Atmospheres, 118, p3192-3199 (2013). http://dx.doi.org/10.1002/jgrd.50296
Can correcting feature location in simulated mean climate improve agreement on projected changes? Levy, A.A.L et al. Geophysical Research Letters, 40, p354-358 (2013). http://dx.doi.org/10.1029/2012/GL053964
Allowable carbon emissions for medium-to-high mitigation scenarios. Tachiiri et al. Tellus Series B - Chemical and Physical Meteorology, 65, (2013). http://dx.doi.org/10.3402/tellusb.v65i0.20586
The global carbon budget 1959-2011. LeQuere et al. Earth System Science Data, 5, p165-185 (2013). http://dx.doi.org/10.5194/essd-5-165-2013
2012
Equivalence of greenhouse-gas emissions for peak temperature limits. Stephen M Smith, Jason A Lowe, Niel H A Bowerman, Laila K Gohar, Chris Huntingford & Myles R Allen. Nature Climate Change 2 p535-538 (2012). http://dx.doi.org/doi:10.1038/NCLIMATE1496
The link between a global 2°C warming threshold and emissions in years 2020, 2050 and beyond. Chris Huntingford, Jason A. Lowe, Laila K. Gohar, Niel H.A. Bowerman, Myles R. Allen, Sarah C.B. Raper and Stephen M. Smith. Environ. Res. Lett. 7 (2012) 014039 (8pp). http://dx.doi.org/doi:10.1088/1748-9326/7/1/014039.
High sensitivity of future global warming to land carbon cycle processes. Ben Booth, Chris D Jones, Mat Collins, Ian J Totterdell, Peter M Cox, Stephen Sitch, Chris Huntingford, Richard A Betts, Glen R Harris and Jon Lloyd. Environ. Res Lett. 7 (2012) 024002 (8pp). http://dx.doi.org/doi:10.1088/1748-9326/7/2/024002.
Model complexity versus ensemble size: allocating resources for climate prediction. Christopher A. T. Ferro, Tim E. Jupp, F. Hugo Lambert, Chris Huntingford and Peter M. Cox. Phil. Trans. R. Soc. A 370, p1087-1099 (2012). http://dx.doi.org/doi:10.1098/rsta.2011.0307
2011
The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics. D.B. Clark, L.M. Mercado, S.Sitch, C.D. Jones, N.Gedney, M.J. Best, M. Pryor, G.G. Rooney, R.L.H. Essery, E. Blyth, O. Boucher, R.J. Harding, C. Huntingford, and P.M. Cox. Geosci. Model Dev., 4, p701–722 (2011). http://dx.doi.org/10.5194/gmd-4-701-2011
Highly contrasting effects of different climate forcing agents on terrestrial ecosystem services.
C. Huntingford, P. M. Cox, L. M. Mercado, S. Sitch, N. Bellouin, O. Boucher and N. Gedney. Phil. Trans. R. Soc. A 369, 2026-2037 (2011). http://dx.doi.org/10.1098/rsta.2010.0314.
Cumulative carbon emissions, emissions floors and short-term rates of warming: implications for policy. Bowerman, N.H.A., Frame, D.J., Huntingford, C., Lowe, J.A. and Allen, M.R. Phil. Trans. R. Soc. A. 369, p45-66 (2010). http://dx.doi.org/10.1098/rsta.2010.0288
Trends in the sources and sinks of carbon dioxide. Le Quere, C., Raupach, M.R., Canadell, J.G. et al. Nature Geoscience, 2, p831-836 (Dec 2009) http://dx.doi.org/10.1038/ngeo689
Quantifying environmental drivers of future tropical forest extent. Good, Peter, Jones, Chris, Lowe, Jason, Betts, Richard, Booth, Ben, Huntingford, Chris. Journal of Climate, 24, Issue , p1337 -1349 (2011). http://dx.doi.org/10.1175/2010JCLI3865.1
Changes in the potential distribution of humid tropical forests. Zelazowski, P., Mahli, Y., Huntingford, C., Sitch, S. and Fisher, J.B. Phil. Trans. of the R. Soc. A. 369, p137-160 (2011). http://dx.doi.org/10.1098/rsta.2010.0238
2010
Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change. Galbraith, D., Levy, P.E., Sitch, S., Huntingford, C., Cox, P., Williams, M. and Meir, P. New Phytologist, 187, p647-665 (2010). http://dx.doi.org/10.1111/j.1469-8137.2010.03350.x
IMOGEN: an intermediate complexity model to evaluate terrestrial impacts of a changing climate. C. Huntingford, B. B. B. Booth, S. Sitch, N. Gedney, J. A. Lowe, S. K. Liddicoat, L. M. Mercado, M. J. Best, G. P.Weedon, R. A. Fisher, M. R. Lomas, P. Good, P. Zelazowski, A. C. Everitt, A. C. Spessa, and C. D. Jones. Geoscientific Model Development. 3, p679-687 (2010). http://dx.doi.org/10.5194/gmd-3-679-2010
Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations. Fisher, R., McDowell, N., Purves, D., Moorcroft, P., Sitch, S., Cox, P., Huntingford, C., Meir, P. and Woodward, F.I. New Phytologist, 187, 666-681 (2010). http://dx.doi.org/10.1111/j.1469-8137/2010.03340.x
Carbon cost of plant nitrogen acquisition: A mechanistic, globally applicable model of plant nitrogen uptake, retranslocation, and fixation. Fisher, J.B., Sitch, S., Malhi, Y., Fisher, R.A., Huntingford, C. and Tan, S.Y. Global Biogeochemical Cycles, 24, GB1014, (2010). http://dx.doi.org/10.1029/2009GB003621
Hughes, J.K., Lloyd, A.J., Huntingford, C. et al. The impact of extensive planting of Miscanthus as an energy crop on future CO2 atmospheric concentrations. Source: Global Change Biology Bioenergy, 2, p79-88 (2010). http://dx.doi.org/10.1111/j.1757-1707.2010.01042.x
2009
Warming caused by cumulative carbon emissions towards the trillionth tonne. Allen, M. R., Frame, D. J, Huntingford, C., Jones, C.D., Lowe, J.A., Meinshausen, M. and Meinschausen, N. Nature 458, p1163-1166 (2009) http://dx.doi.org/10.1038/nature08019
Contributions of carbon cycle uncertainty to future climate projection spread. Huntingford, C.., Lowe, J.A., Booth, B.B.B. et al. Tellus Series B - Chemical and Physical Meteorology, 61, p355-360 (2009). http://dx.doi.org/0.1111/j.1600-0889.2009.00414.x.
How difficult is it to recover from dangerous levels of global warming? Lowe, J.A., Huntingford, C., Raper, S.C.B., Jones, C.D., Liddicoat, S.K., Gohar, L.K. Environ. Res. Lett. 4 014012 (2009). http://dx.doi.org/10.1088/1748-9326/4/1/014012.
Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest. Malhi, Y., Aragao L.E.O.C., Galbraith, D., Huntingford, C., Fisher, R., Zelazowski, P., Sitch, S., McSweeney, C. and Meir, P. Proceedings of the National Academy of Sciences of the United States of America, 106, (2009). http://dx.doi.org/10.1073/pnas.0804619106
Impact of changes in diffuse radiation on the global land carbon sink. Mercado, L. M., Bellouin, N., Sitch, S. et al. Nature 458 (2009). http://dx.doi.org/10.1038/nature07949
2008
What do recent advances in quantifying climate and carbon cycle uncertainties mean for climate policy? House, J.I., Huntingford, C., Knorr, W. et al. Environmental Research Letters, 3, Art. 044002 (2008). http://www.iop.org/EJ/abstract/1748-9326/3/4/044002
Observed climate change constrains the likelihood of extreme future global warming. Stott, P.A., Huntingford, C., Jones, C.D. et al. Tellus Series B-Chemical and Physical Meteorology, 60, p76-81 (2008). http://dx/doi.org/10.1111/j.1600-0889.2007.00329.x.
Amazon Basin climate under global warming: the role of the sea surface temperature. Harris, P.P., Huntingford, C., Cox, P.M. Phil. Trans. of the R.l Soc. B-Biological Sciences, 363, p1753-1759 (2008). http://dx.doi.org/10.1098/rstb.2007.0037
Towards quantifying uncertainty in predictions of Amazon “dieback”. Huntingford , C., Fisher, R.A., Mercado, L. et al. Phil. Trans. of the R. Soc. B-Biological Sciences, Volume 363, Issue 1498, Pages 1857-1864 (2008). http://dx.doi.org/10.1098/rstb.2007.0028
Increasing risk of Amazonian drought due to decreasing aerosol pollution. Cox, P.M., Harris, P.P., Huntingford, C., et al. Nature, 453, p212-U7 (2008). http://dx.doi.org/10.1038/nature06960
Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Sitch, S., Huntingford, C., Gedney, N. et al. Global Change Biology, 14, p2015-2039 (2008). http://dx.doi.org/10.1111/j.1365-2486.2008.01626.x
Climate change: Seeking balance in media reports. Huntingford, C., Fowler, D. Environmental Research Letters, 3, (2008). http://dx.doi.org/10.1088/1748-9326/3/2/021001
2007
"Overshoot" scenarios and climate change.
Huntingford, C., Lowe, J. Science, 316, p829-829, (2007). http://dx.doi.org/10.1126/science.316.5826.829b
Climate-carbon cycle feedbacks under stabilization: uncertainty and observational constraints. Jones, C.D., Cox, P.M., Huntingford, C. Tellus Series B-Chemical and Physical Meteorology, 58, p603-613, (Nov 2006). http://dx.doi.org/10.1111/j.1600-0889.2006.00215.x.
Projected increase in continental runoff due to plant responses to increasing carbon dioxide. Betts, R.A., Boucher, O., Collins, M. et al. Nature, 448, p1037-U5 (2007). http://dx.doi.org/10.1038/nature06045
On the robustness of changes in extreme precipitation over Europe from two high resolution climate change simulations. Buonomo, E., Jones, R., Huntingford, C. et al. Quarterly Journal of the Royal Meteorological Society, 133, p65-81 (Jan 2007). http://dx.doi.org/10.1002/qj.13
Improving the representation of radiation interception and photosynthesis for climate model applications. Mercado, L.M., Huntingford, C., Gash, J.H.C. et al. Tellus Series B-Chemical and Physical Meteorological, 59, p553-565 (2007). http://dx.doi.org/10.1111/j.1600-0889.2007.00256.x.
Indirect radiative forcing of climate change through ozone effects on the land-carbon sink. Sitch, S., Cox, P.M., Collins, W.J. et al. Nature, 448, p791-U4 (2007). http://dx.doi.org/10.1038/nature06059
Impact of climate change on health: what is required of climate modellers? Huntingford, C., Hemming, D., Gash, J.H.C. et al. Trans. of the Roy. Soc. of Tropical Medicine and Hygiene, 101, p97-103 (Feb 2007). doi: 10.1016/j.trstmh.2006.11.001
2006
Incorporating model uncertainty into attribution of observed temperature change. Huntingford, C., Stott, P.A., Allen, M.R. et al. Geophysical Research Letters, 33, (2006). http://dx.doi.org/10.1029/2005GL024831
Detection of a direct carbon dioxide effect in continental river runoff records. Gedney, N., Cox, P.M., Betts, R.A. et al. Nature, 439, 835-838 (2006). http://dx.doi.org/10.1038/nature04504
Continental runoff - A quality-controlled global runoff data set - Reply. Gedney, N., Cox, P.M., Betts, R.A. et al. Nature, 444, pE14-E15 (2006). http://dx.doi.org/10.1038/nature05481
Evaluation of the rainfall component of a weather generator for climate impact studies. Elshamy, M.E., Wheater, H.S., Gedney, N. et al. Journal of Hydrology, 326, p1-24 (Jul 2006). http://dx.doi.org/10.1016/j.jhydrol.2005.09.017
Climate change and hydrology: next steps for climate models. Huntingford, C., Gash, J., Giacomello, A.M. Hydrological Processes, 20, p2085-2087 (Jun 2006). http://dx.doi.org/10.1002/hyp.6208
2005
Attribution studies of observed land precipitation changes with nine coupled models. Lambert, F.H., Gillett, N.P., Stone, D.A. et al. Geophysical Research Letters, 32, (2005). http://dx.doi.org/10.1029/2005GL023654
Aspects of climate change prediction relevant to crop productivity. Huntingford, C., Lambert, F.H., Gash, J.H.C. et al. Phil. Trans. of the Roy. Soc. B-Biological Sciences, 360, p1999-2009 (2005). http://dx.doi.org/10.1098/rstb.2005.1748
Climate equity for all. Author(s): Huntingford, C., Gash, J. Science, 309, p1789-1789 (2005). http://dx.doi.org/10.1126/science.1115898
Combining a regional climate model with a phytoplankton community model to predict future changes in phytoplankton in lakes. Elliott, J.A., Thackeray, S.J., Huntingford, C. et al. Freshwater Biology, 50, p1404-1411 (2005). http://dx.doi.org/10.1111/j.1365-2427.2005.01409.x
Modelling long-term transpiration measurements from grassland in southern England. Harding, R.J., Huntingford, C., Cox, P.M. Agricultural and Forest Meteorology, 100, p309-322 (2005). http://dx.doi.org/10.1016/S0168-1923(99)00152-5
2004
Preface. Gash, J.H.C., Marengo, J.A., Huntingford, C. Theoretical and Applied Climatology, 78, p3-3 (2004). http://dx.doi.org/10.1007/s00704-004-0040-0
Calibration of a land-surface model using data from primary forest sites in Amazonia. Harris, P.P., Huntingford, C., Gash, J.H.C. et al. Theoretical and Applied Climatology, 78, p27-45 (2004). http://dx.doi.org/10.1007/s00704-004-0042-y
Amazonian forest dieback under climate-carbon cycle projections for the 21st century. Cox, P.M., Betts, R.A., Collins, M. et al. Theoretical and Applied Climatology, 78, p137-156, (2004). http://dx.doi.org/10.1007/s00704-004-0049-4
The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Betts, R.A, COX, P.M., Collins, M. et al. Theoretical and Applied Climatology, 78, 157-175 (2004). http://dx.doi.org/10.1007/s00704-004-0050-y
Using a GCM analogue model to investigate the potential for Amazonian forest dieback. Huntingford, C., Harris, P.P., Gedney, N., et al. Theoretical and Applied Climatology, 78, p177-185 (2004). http://dx.doi.org/10.1007/s00704-004-0051-x
Amazonian climate: results and future research. Gash, J.H.C., Huntingford, C., Marengo, J.A. et al. Theoretical and Applied Climatology, 78, p187-193 (2004).
http://dx.doi.org/10.1007/s00704-004-0052-9
Effect of soil moisture on canopy conductance of Amazonian rainforest. Harris, P.P., Huntingford, C., Cox, P.M. et al. Agricultural and Forest Meteorology, 122, 215-227 (2004). http://dx.doi.org/10.1016/j.agrformet.2003.09.006
Climate feedback from wetland methane emissions. Gedney, N., Cox, P.M., Huntingford, C. Geophysical Research Letters, 31, (2004). http://dx.doi.org/10.1029/2004GL020919
2003
Regional climate-model predictions of extreme rainfall for a changing climate. Huntingford, C., Jones, R.G., Prudhomme, C. et al. Quarterly Journal of the Royal Meteorological Society, 129, 1607-1621 (2003). http://dx.doi.org/10.1256/qj.02.97
Extent of partial ice cover due to carbon cycle feedback in a zonal energy balance model. Huntingford, C., Hargreaves, J.C., Lenton, T.M. et al. Hydrology and Earth System Sciences, 7, 213-219, (2003).
Global terrestrial carbon storage and uncertainties in its temperature sensitivity examined with a simple model. Lenton, T.M., Huntingford, C. Global Change Biology, 9, 1333-1352 (2003). http://dx.doi.org/10.1046/j.1365-2486.2003.00674.x
Uncertainty in climate-carbon-cycle projections associated with the sensitivity of soil respiration to temperature. Jones, C.D., Cox, P., Huntingford, C. Tellus Series B-Chemical and Physical Meteorology, 55, p642-648 (2003).
Improved description of soil hydraulic and thermal properties of arctic peatland for use in a GCM. Hall, R.L., Huntingford, C., Harding, R.J. et al. Hydrological Processes, 17, p2611-2628 (2003). http://dx.doi.org/10.1002/hyp.1265
2000
An analogue model to derive additional climate change scenarios from existing GCM simulations. Huntingford, C., Cox, P.M. Climate Dynamics, 16, p575-586 (2000). http://dx.doi.org/10.1007/s003820000067
Contrasting responses of a simple terrestrial ecosystem model to global change. Huntingford, C., Cox, P.M, Lenton, T.M. Ecological Modelling, 134, p41-58 (2000). http://dx.doi.org/10.1016/S0304-3800(00)00330-6
Dual versus single source models for estimating surface temperature of African savannah. Huntingford, C., Verhoef, A., Stewart, J. Hydrology and Earth System Sciences, 4, Issue 1, p185-191 (Mar 2000).
1998
A canopy conductance and photosynthesis model for use in a GCM land surface scheme. Cox, P.M., Huntingford, C., Harding, R.J. Journal of Hydrology, 213, 79-94 (1998). http://dx.doi.org/10.1016/S0022-1694(98)00203-0
The behaviour of a mixed-layer model of the convective boundary layer coupled to a big leaf model of surface energy partitioning. Huntingford, C., Monteith, J.L. Source: Boundary Layer Meteorology, 88, 87-101 (1998). http://dx.doi.org/10.1023/A:1001110819090
The effect of orography on evaporation. Huntingford, C., Blyth, E.M., Wood, N. et al. Boundary Layer Meteorology, 86, 487-504 (1998). http://dx.doi.org/10.1023/A:1000795206459
An argument for the use of two-layer SVAT schemes to simulate terrestrial carbon dioxide fluxes. Huntingford, C., Hall, R.L., Verhoef, A. Hydrology and Earth System Sciences, 2, p299-302 (1998).
1997
Use of statistical and neural network techniques to detect how stomatal conductance responds to changes in the local environment. Huntingford, C., Cox, P.M. Ecological Modelling, 97, p217-246 (1997). http://dx.doi.org/10.1016/S0304-3800(96)01905-9
1996
A note on the similarity groups of the Penman-Monteith Big Leaf Model. Huntingford, C. Boundary Layer Meteorology, 79, p307-312 (1996). http://dx.doi.org/10.1007/BF00119444
An intercomparison of single and dual-source vegetation-atmosphere transfer models applied to transpiration from Sahelian savannah (Correction Volume 74, p397, 1995). Huntingford, C., Allen, S.J., Harding, R.J. Boundary Layer Meteorology, 77, p101-101 (1996).
1995
An intercomparison of single and dual-source vegetation-atmosphere transfer models applied to transpiration from Sahelian savanna. Huntingford, C., Allen, S.J., Harding, R.J. Boundary-Layer Meteorology, 74, p397-418 (1995). http://dx.doi.org/10.1007/BF00712380
Non-Dimensionalisation of the Penman-Monteith model. Huntingford, C. Journal of Hydrology, 170, p215-232 (1995). http://dx.doi.org/10.1016/002-1694(94)02673-Y
An exact solution to the one-phase zero-surface-tension Hele-Shaw free-boundary problem. Huntingford, C. Computers & Mathematics with Applications, 29, p45-50 (1995). http://dx.doi.org/10.1016/0898-1221(95)00044-Y
1994
A model for nonsmooth free boundaries in Hele-Shaw flows. Hohlov, Y.E., Howison, S.D., Huntingford, C. Et al. Quarterly Journal of Mechanics and Applied Mathematics, 47, p107-128 (1994). http://dx.doi.org/10.1093/qjmam/47.1.107
