Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset
Land surface models (LSMs) play a crucial role in climate prediction and carbon cycle assessment. To ensure their reliability, it is crucial to evaluate their performance in simulating key processes, such as evapotranspiration (ET) and gross primary productivity (GPP), across various temporal scales...
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2025-07-01
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| author | Bofeng Pan Xiaolu Wu Xitian Cai |
| author_facet | Bofeng Pan Xiaolu Wu Xitian Cai |
| author_sort | Bofeng Pan |
| collection | DOAJ |
| description | Land surface models (LSMs) play a crucial role in climate prediction and carbon cycle assessment. To ensure their reliability, it is crucial to evaluate their performance in simulating key processes, such as evapotranspiration (ET) and gross primary productivity (GPP), across various temporal scales and vegetation types. This study systematically evaluates the performance of the newly modernized Noah-MP LSM version 5.0 in simulating water and carbon fluxes, specifically ET and GPP, across temporal scales ranging from half-hourly (capturing diurnal cycles) to annual using observational data from 105 sites within the globally FLUXNET2015 dataset. The results reveal that Noah-MP effectively captured the overall variability of both ET and GPP, particularly at short temporal scales. The model successfully simulated the diurnal and seasonal cycles of both fluxes, though cumulative errors increased at the annual scale. Diurnally, the largest simulation biases typically occurred around noon; while, seasonally, biases were smallest in winter. Performance varied significantly across vegetation types. For ET, the simulations were most accurate for open shrublands and deciduous broadleaf forests, while showing the largest deviation for woody savannas. Conversely, GPP simulations were most accurate for wetlands and closed shrublands, showing the largest deviation for evergreen broadleaf forests. Furthermore, an in-depth analysis stratified by the climate background revealed that ET simulations failed to capture inter-annual variability in the temperate and continental zones, while GPP was severely overestimated in arid and temperate climates. This study identifies the strengths and weaknesses of Noah-MP in simulating water and carbon fluxes, providing valuable insights for future model improvements. |
| format | Article |
| id | doaj-art-6bb4d53c4ed04b2e81a014fc50a58cc3 |
| institution | DOAJ |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-6bb4d53c4ed04b2e81a014fc50a58cc32025-08-20T02:45:43ZengMDPI AGLand2073-445X2025-07-01147140010.3390/land14071400Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET DatasetBofeng Pan0Xiaolu Wu1Xitian Cai2School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, ChinaSchool of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, ChinaLand surface models (LSMs) play a crucial role in climate prediction and carbon cycle assessment. To ensure their reliability, it is crucial to evaluate their performance in simulating key processes, such as evapotranspiration (ET) and gross primary productivity (GPP), across various temporal scales and vegetation types. This study systematically evaluates the performance of the newly modernized Noah-MP LSM version 5.0 in simulating water and carbon fluxes, specifically ET and GPP, across temporal scales ranging from half-hourly (capturing diurnal cycles) to annual using observational data from 105 sites within the globally FLUXNET2015 dataset. The results reveal that Noah-MP effectively captured the overall variability of both ET and GPP, particularly at short temporal scales. The model successfully simulated the diurnal and seasonal cycles of both fluxes, though cumulative errors increased at the annual scale. Diurnally, the largest simulation biases typically occurred around noon; while, seasonally, biases were smallest in winter. Performance varied significantly across vegetation types. For ET, the simulations were most accurate for open shrublands and deciduous broadleaf forests, while showing the largest deviation for woody savannas. Conversely, GPP simulations were most accurate for wetlands and closed shrublands, showing the largest deviation for evergreen broadleaf forests. Furthermore, an in-depth analysis stratified by the climate background revealed that ET simulations failed to capture inter-annual variability in the temperate and continental zones, while GPP was severely overestimated in arid and temperate climates. This study identifies the strengths and weaknesses of Noah-MP in simulating water and carbon fluxes, providing valuable insights for future model improvements.https://www.mdpi.com/2073-445X/14/7/1400evapotranspirationgross primary productivitymodel evaluationNoah-MP LSMwater and carbon fluxes |
| spellingShingle | Bofeng Pan Xiaolu Wu Xitian Cai Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset Land evapotranspiration gross primary productivity model evaluation Noah-MP LSM water and carbon fluxes |
| title | Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset |
| title_full | Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset |
| title_fullStr | Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset |
| title_full_unstemmed | Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset |
| title_short | Evaluation of Noah-MP Land Surface Model-Simulated Water and Carbon Fluxes Using the FLUXNET Dataset |
| title_sort | evaluation of noah mp land surface model simulated water and carbon fluxes using the fluxnet dataset |
| topic | evapotranspiration gross primary productivity model evaluation Noah-MP LSM water and carbon fluxes |
| url | https://www.mdpi.com/2073-445X/14/7/1400 |
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