A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios
Melaas, Eli K.
Gray, Josh M.
Friedl, Mark A.
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CitationChen, Min, Eli K. Melaas, Josh M. Gray, Mark A. Friedl, and Andrew D. Richardson. 2016. “A New Seasonal-Deciduous Spring Phenology Submodel in the Community Land Model 4.5: Impacts on Carbon and Water Cycling Under Future Climate Scenarios.” Global Change Biology 22 (11) (May 14): 3675–3688. Portico. doi:10.1111/gcb.13326.
AbstractA spring phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf-out dates is optimized using PhenoCam observations and coupled into the Community Land Model (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km2), we found that the revised model substantially outperformed the standard CLM seasonal-deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long-term trends (1950–2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf-out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf-out in colder regions, but later leaf-out in warmer regions, and no trend globally. The earlier spring leaf-out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr−1) and evapotranspiration (up to 24 mm yr−1) when results were integrated across the study region. These results suggest that the standard seasonal-deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land–atmosphere interactions and feedbacks may result.
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