TY - JOUR

T1 - A new temperature-photoperiod coupled phenology module in LPJ-GUESS model v4.1

T2 - Optimizing estimation of terrestrial carbon and water processes

AU - Chen, Shouzhi

AU - Fu, Yongshuo H.

AU - Li, Mingwei

AU - Jia, Zitong

AU - Cui, Yishuo

AU - Tang, Jing

N1 - Publisher Copyright: © 2024 The Author(s).

PY - 2024

Y1 - 2024

N2 - Vegetation phenological shifts impact the terrestrial carbon and water cycle and affect the local climate system through biophysical and biochemical processes. Dynamic global vegetation models (DGVMs), serving as pivotal simulation tools for investigating climate impacts on terrestrial ecosystem processes, incorporate representations of vegetation phenological processes. Nevertheless, it is still a challenge to achieve an accurate simulation of vegetation phenology in the DGVMs. Here, we developed and implemented spring and autumn phenology algorithms into one of the DGVMs, LPJ-GUESS. The new phenology modules are driven by temperature and photoperiod and are parameterized for deciduous trees and shrubs by using remotely sensed phenological observations and the reanalysis data from ERA5. The results show that the LPJ-GUESS with the new phenology modules substantially improved the accuracy in capturing the start and end dates of growing seasons. For the start of the growing season, the simulated RMSE for deciduous trees and shrubs decreased by 8.04 and 17.34d, respectively. For the autumn phenology, the simulated RMSE for deciduous trees and shrubs decreased by 22.61 and 17.60d, respectively. Interestingly, we have also found that differences in the simulated start and end of the growing season also alter the simulated ecological niches and competitive relationships among different plant functional types (PFTs) and subsequentially influence the terrestrial carbon and water cycles. Hence, our study highlights the importance of accurate phenology estimation to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.

AB - Vegetation phenological shifts impact the terrestrial carbon and water cycle and affect the local climate system through biophysical and biochemical processes. Dynamic global vegetation models (DGVMs), serving as pivotal simulation tools for investigating climate impacts on terrestrial ecosystem processes, incorporate representations of vegetation phenological processes. Nevertheless, it is still a challenge to achieve an accurate simulation of vegetation phenology in the DGVMs. Here, we developed and implemented spring and autumn phenology algorithms into one of the DGVMs, LPJ-GUESS. The new phenology modules are driven by temperature and photoperiod and are parameterized for deciduous trees and shrubs by using remotely sensed phenological observations and the reanalysis data from ERA5. The results show that the LPJ-GUESS with the new phenology modules substantially improved the accuracy in capturing the start and end dates of growing seasons. For the start of the growing season, the simulated RMSE for deciduous trees and shrubs decreased by 8.04 and 17.34d, respectively. For the autumn phenology, the simulated RMSE for deciduous trees and shrubs decreased by 22.61 and 17.60d, respectively. Interestingly, we have also found that differences in the simulated start and end of the growing season also alter the simulated ecological niches and competitive relationships among different plant functional types (PFTs) and subsequentially influence the terrestrial carbon and water cycles. Hence, our study highlights the importance of accurate phenology estimation to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.

U2 - 10.5194/gmd-17-2509-2024

DO - 10.5194/gmd-17-2509-2024

M3 - Journal article

AN - SCOPUS:85189880105

VL - 17

SP - 2509

EP - 2523

JO - Geoscientific Model Development

JF - Geoscientific Model Development

SN - 1991-959X

IS - 7

ER -