Title: On the Uncertainty of Phenological Responses to Climate Change and its Implication for Terrestrial Biosphere Models
Authors: MIGLIAVACCA MIRCOSONNENTAG OliverKEENAN TrevorCESCATTI AlessandroO'KEEFE JohnRICHARDSON Andrew D.
Citation: BIOGEOSCIENCES vol. 9 p. 2063–2083
Publisher: COPERNICUS GESELLSCHAFT MBH
Publication Year: 2012
JRC N°: JRC68738
ISSN: 1726-4170
URI: www.biogeosciences.net/9/2063/2012/
http://publications.jrc.ec.europa.eu/repository/handle/JRC68738
DOI: 10.5194/bg-9-2063-2012
Type: Articles in periodicals and books
Abstract: Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate systems through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Land surface models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we analyzed the Harvard Forest phenology record to investigate and characterize the sources of uncertainty in phenological forecasts and the subsequent impacts on model forecasts of carbon and water cycling in the future. Using a data-model fusion approach, we combined information from 20 years of phenological observations of 11 North American woody species with 12 phenological models of different complexity to predict leaf bud-burst. The evaluation of different phenological models indicated support for “spring warming” models with photoperiod limitations and, though to a lesser extent, to chilling models based on the “alternating” model structure. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2100 using 2 different IPCC climate scenarios (A1fi vs B1, i.e. high CO2 emissions vs low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% CI: 2.4 days century-1 for scenario B1 and 4.5 days century-1 for A1), whereas driver uncertainty was the largest (up to 7.7 days century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied somewhat among models (± 6.5 days by the end of simulation for scenario A1, ± 2.3 days for scenario B1). The forecast sensitivity of bud-burst to temperature (i.e., days budburst advanced per degree of warming) varied between 2.2 days °C-1 and 5.2 days °C-1, depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated carbon and water fluxes using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of the seasonality of processes, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and evapotranspiration (ET) of 9.6 % and 3.8% respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±3.0% for ET. The uncertainties we have quantified will affect the description of the seasonality of processes and in particular the simulation of carbon uptake by forest ecosystems. Differences among future climate scenarios represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, uncertainties related to model parameterization.
JRC Directorate:Sustainable Resources

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