Bonfils Celine

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Bonfils
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Celine
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  • Article
    Extending the record of photosynthetic activity in the eastern United States into the presatellite period using surface diurnal temperature range
    (American Geophysical Union, 2005-04-26) Bonfils, Celine ; Angert, Alon ; Henning, Cara C. ; Biraud, Sebastien ; Doney, Scott C. ; Fung, Inez Y.
    In this study, we demonstrate that mid-latitude surface measurements of diurnal temperature range (DTR) can be used to reconstruct decadal variability of regional-scale terrestrial photosynthetic activity 1) during and prior to the period with satellite retrievals of land greenness and 2) without the need for moisture data. While the two relative maxima present in the seasonal evolution of DTR can determine the beginning and the end of the growing season, the summertime average DTR can be used as a proxy of summertime terrestrial photosynthesis. In a case study in the eastern United States (1966–1997), the DTR reconstructions indicate significant natural decadal variability in photosynthetic activity, but no secular, long-term trend. The summertime photosynthesis was found to be controlled primarily by moisture availability. Also, contrary to existing model parameterizations, the timing of spring onset was found to depend on both temperature and moisture.
  • Article
    On the detection of summertime terrestrial photosynthetic variability from its atmospheric signature
    (American Geophysical Union, 2004-05-11) Bonfils, Celine ; Fung, Inez Y. ; Doney, Scott C. ; John, Jasmin G.
    We identify the climatic signatures of the summertime terrestrial photosynthesis variability using a long simulation of pre-industrial climate performed with the NCAR coupled global climate-carbon model. Since plant physiology controls simultaneously CO2 uptake and surface fluxes of water, changes in photosynthesis are accompanied by changes in numerous climate variables: daily maximum temperature, diurnal temperature range, Bowen ratio, canopy temperature and tropospheric lapse rate. Results show that these climate variables may be used as powerful proxies for photosynthesis activity for subtropical vegetation and for tropical vegetation when photosynthetic variability may be limited by water availability.
  • Article
    Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming
    (National Academy of Sciences, 2022-11-22) Po-Chedley, Stephen ; Fasullo, John T. ; Siler, Nicholas ; Labe, Zachary M. ; Barnes, Elizabeth A. ; Bonfils, Céline J. W. ; Santer, Benjamin D.
    Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 ± 0.08 K⋅decade between 1979 and 2014, but internal variability has offset this warming by 0.07 ± 0.07 K⋅decade. Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K⋅decade . The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models.