Sensitivity of global terrestrial gross primary production to hydrologic states simulated by the Community Land Model using two runoff parameterizations

Huimin Lei, Maoyi Huang, L. Ruby Leung, Dawen Yang, Xiaoying Shi, Jiafu Mao, Daniel J. Hayes, Christopher R Schwalm, Yaxing Wei, Shishi Liu

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simulations of the carbon cycle, numerical experiments were performed using version 4 of the Community Land Model with two widely adopted runoff generation parameterizations from the TOPMODEL and Variable Infiltration Capacity (VIC) model under the same protocol. The results showed that differences in the runoff generation schemes caused a relative difference of 36% and 34% in global mean total runoff and soil moisture, respectively, with substantial differences in their spatial distribution and seasonal variability. Changes in the simulated gross primary production (GPP) were found to correlate well with changes in soil moisture through its effects on leaf photosynthesis (A<inf>n</inf>) and leaf area index (LAI), which are the two dominant components determining GPP. Soil temperature, which is influenced by soil moisture, also affects LAI and GPP for the seasonal-deciduous and stress-deciduous plant functional types that dominate in cold regions. Consequently, the simulated global mean GPP differs by 20.4% as a result of differences in soil moisture and soil temperature simulated between the two models. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling. Key Points Simulated terrestrial water cycle is sensitive to runoff generation schemes Hydrologic parameterizations have large impacts on the global C budgets Improving hydrologic representations to constrain C cycle modeling is important

Original languageEnglish (US)
Pages (from-to)658-679
Number of pages22
JournalJournal of Advances in Modeling Earth Systems
Volume6
Issue number3
DOIs
StatePublished - 2014

Fingerprint

Soil moisture
Parameterization
Runoff
primary production
parameterization
soil moisture
runoff
carbon cycle
Carbon
leaf area index
soil temperature
Water
Soils
Evapotranspiration
Photosynthesis
cold region
Hydrology
Infiltration
water
Spatial distribution

Keywords

  • carbon cycling
  • global scale
  • modeling
  • runoff generation scheme
  • soil moisture
  • vegetation dynamics

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)
  • Environmental Chemistry
  • Global and Planetary Change

Cite this

Sensitivity of global terrestrial gross primary production to hydrologic states simulated by the Community Land Model using two runoff parameterizations. / Lei, Huimin; Huang, Maoyi; Leung, L. Ruby; Yang, Dawen; Shi, Xiaoying; Mao, Jiafu; Hayes, Daniel J.; Schwalm, Christopher R; Wei, Yaxing; Liu, Shishi.

In: Journal of Advances in Modeling Earth Systems, Vol. 6, No. 3, 2014, p. 658-679.

Research output: Contribution to journalArticle

Lei, Huimin ; Huang, Maoyi ; Leung, L. Ruby ; Yang, Dawen ; Shi, Xiaoying ; Mao, Jiafu ; Hayes, Daniel J. ; Schwalm, Christopher R ; Wei, Yaxing ; Liu, Shishi. / Sensitivity of global terrestrial gross primary production to hydrologic states simulated by the Community Land Model using two runoff parameterizations. In: Journal of Advances in Modeling Earth Systems. 2014 ; Vol. 6, No. 3. pp. 658-679.
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abstract = "Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simulations of the carbon cycle, numerical experiments were performed using version 4 of the Community Land Model with two widely adopted runoff generation parameterizations from the TOPMODEL and Variable Infiltration Capacity (VIC) model under the same protocol. The results showed that differences in the runoff generation schemes caused a relative difference of 36{\%} and 34{\%} in global mean total runoff and soil moisture, respectively, with substantial differences in their spatial distribution and seasonal variability. Changes in the simulated gross primary production (GPP) were found to correlate well with changes in soil moisture through its effects on leaf photosynthesis (An) and leaf area index (LAI), which are the two dominant components determining GPP. Soil temperature, which is influenced by soil moisture, also affects LAI and GPP for the seasonal-deciduous and stress-deciduous plant functional types that dominate in cold regions. Consequently, the simulated global mean GPP differs by 20.4{\%} as a result of differences in soil moisture and soil temperature simulated between the two models. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling. Key Points Simulated terrestrial water cycle is sensitive to runoff generation schemes Hydrologic parameterizations have large impacts on the global C budgets Improving hydrologic representations to constrain C cycle modeling is important",
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AU - Lei, Huimin

AU - Huang, Maoyi

AU - Leung, L. Ruby

AU - Yang, Dawen

AU - Shi, Xiaoying

AU - Mao, Jiafu

AU - Hayes, Daniel J.

AU - Schwalm, Christopher R

AU - Wei, Yaxing

AU - Liu, Shishi

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AB - Soil moisture plays an important role in the coupled water, energy, and carbon cycles. In addition to surface processes such as evapotranspiration, the boundary fluxes that influence soil moisture are closely related to surface or subsurface runoff. To elucidate how uncertainties in representing surface and subsurface hydrology may influence simulations of the carbon cycle, numerical experiments were performed using version 4 of the Community Land Model with two widely adopted runoff generation parameterizations from the TOPMODEL and Variable Infiltration Capacity (VIC) model under the same protocol. The results showed that differences in the runoff generation schemes caused a relative difference of 36% and 34% in global mean total runoff and soil moisture, respectively, with substantial differences in their spatial distribution and seasonal variability. Changes in the simulated gross primary production (GPP) were found to correlate well with changes in soil moisture through its effects on leaf photosynthesis (An) and leaf area index (LAI), which are the two dominant components determining GPP. Soil temperature, which is influenced by soil moisture, also affects LAI and GPP for the seasonal-deciduous and stress-deciduous plant functional types that dominate in cold regions. Consequently, the simulated global mean GPP differs by 20.4% as a result of differences in soil moisture and soil temperature simulated between the two models. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling. Key Points Simulated terrestrial water cycle is sensitive to runoff generation schemes Hydrologic parameterizations have large impacts on the global C budgets Improving hydrologic representations to constrain C cycle modeling is important

KW - carbon cycling

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KW - soil moisture

KW - vegetation dynamics

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