A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

Ning Ma, Guo-Yue Niu, Youlong Xia, Xitian Cai, Yinsheng Zhang, Yaoming Ma, Yuanhao Fang

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

Original languageEnglish (US)
Pages (from-to)12,245-12,268
JournalJournal of Geophysical Research: Atmospheres
Volume122
Issue number22
DOIs
StatePublished - Nov 27 2017

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water storage
Carbon
energy transfer
atmospheres
Water
atmosphere
evaluation
carbon
evapotranspiration
energy
Evapotranspiration
Lakes
water
drainage
Runoff
lakes
snow cover
vegetation dynamics
irrigation
runoff

Keywords

  • energy fluxes
  • gross primary productivity
  • HUC2 region
  • land surface model
  • Noah-MP
  • snow cover fraction

ASJC Scopus subject areas

  • Geophysics
  • Oceanography
  • Forestry
  • Aquatic Science
  • Ecology
  • Condensed Matter Physics
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Physical and Theoretical Chemistry
  • Polymers and Plastics
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Materials Chemistry
  • Palaeontology

Cite this

A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States. / Ma, Ning; Niu, Guo-Yue; Xia, Youlong; Cai, Xitian; Zhang, Yinsheng; Ma, Yaoming; Fang, Yuanhao.

In: Journal of Geophysical Research: Atmospheres, Vol. 122, No. 22, 27.11.2017, p. 12,245-12,268.

Research output: Contribution to journalArticle

Ma, Ning ; Niu, Guo-Yue ; Xia, Youlong ; Cai, Xitian ; Zhang, Yinsheng ; Ma, Yaoming ; Fang, Yuanhao. / A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States. In: Journal of Geophysical Research: Atmospheres. 2017 ; Vol. 122, No. 22. pp. 12,245-12,268.
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AB - Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

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