Modeling leaf area index in North America using a process‐based terrestrial ecosystem model

Abstract

AbstractLeaf area index (LAI) is often used to quantify plant production and evapotranspiration with terrestrial ecosystem models (TEMs). This study evaluated the LAI simulation in North America using a data assimilation technique and a process‐based TEM as well as in situ and satellite data. We first optimized the parameters related to LAI in the TEM using a Markov Chain Monte Carlo method, and AmeriFlux site‐level and regional LAI data from advanced very high‐resolution radiometer. The parameterized model was then verified with the observed monthly LAI of major ecosystem types at site level. Simulated LAI was compared well with the observed data at sites of Harvard Forest (R2 = 0.96), University of Michigan Biological Station (R2 = 0.87), Howland Forest (R2 = 0.96), Morgan Monroe State Forest (R2 = 0.85), Shidler Tallgrass Prairie (R2 = 0.82), and Donaldson (R2 = 0.75). The root‐mean‐square error (RMSE) between modeled and satellite‐based monthly LAI in North America is 1.4 m2/m2 for the period of 1985–2010. The simulated average monthly LAI in recent three decades increased by (3 ± 0.5)% in the region, with 1.24, 1.46, and 2.21 m2/m2 on average, in Alaska, Canada, and the conterminous United States, respectively, which is consistent with satellite data. The model performed well for wet tundra, boreal forest, temperate coniferous forests, temperate deciduous forests, grasslands, and xeric shrublands (RMSE < 1.5 m2/m2), but not for alpine tundra and xeric woodlands (RMSE > 1.5 m2/m2). Both the spring and fall LAI in the 2000s are higher than that in the 1980s in the region, suggesting that the leaf phenology has an earlier onset and later senescence in the 2000s. The average LAI increased in April and September by 0.03 and 0.24 m2/m2, respectively. This study provides a way to quantify LAI with ecosystem models, which will improve future carbon and water cycling studies.