IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v129y2015i3p457-470.html
   My bibliography  Save this article

The improvement of a regional climate model by coupling a land surface model with eco-physiological processes: A case study in 1998

Author

Listed:
  • Li Dan
  • Fuqiang Cao
  • Rong Gao

Abstract

The Atmospheric-Vegetation Interaction Model (AVIM) is coupled with a Regional Integrated Environment Modeling System (RIEMS) to improve the regional simulation of climate variables. A case study in 1998 is implemented to study the improvement mechanism through land-air interaction in East Asia, especially in Asian summer monsoon regions. The coupled model reduces the warming bias in July in East China through the surface heat fluxes changes. Compared to the original model of RIEMS, the strong precipitation of eastern China in July is weakened by coupling of the interactive vegetation. The surface heat flux in uncoupled model is remarkably overestimated in these regions, and the enhanced heating from land surface, particularly with latent heat flux in July, will produce the overestimated temperature and precipitation in East China. Through coupling AVIM with RIEMS, the simulated area-averaged latent heat flux of two key regions decreases (e.g. from 132.36 to 103.13 W/m 2 over the region 1 between 105–125°E and 20–40°N) in July, which makes the overestimated temperature and precipitation declined, respectively. Copyright The Author(s) 2015

Suggested Citation

  • Li Dan & Fuqiang Cao & Rong Gao, 2015. "The improvement of a regional climate model by coupling a land surface model with eco-physiological processes: A case study in 1998," Climatic Change, Springer, vol. 129(3), pages 457-470, April.
    • Handle: RePEc:spr:climat:v:129:y:2015:i:3:p:457-470
    DOI: 10.1007/s10584-013-0997-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-013-0997-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10584-013-0997-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
    2. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    3. Oecd, 2009. "Climate Change and Africa," OECD Journal: General Papers, OECD Publishing, vol. 2009(1), pages 5-35.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing Peng & Li Dan & Jinming Feng & Kairan Ying & Xiba Tang & Fuqiang Yang, 2021. "Absolute Contribution of the Non-Uniform Spatial Distribution of Atmospheric CO 2 to Net Primary Production through CO 2 -Radiative Forcing," Sustainability, MDPI, vol. 13(19), pages 1-18, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eliseev, Alexey V. & Mokhov, Igor I., 2008. "Eventual saturation of the climate–carbon cycle feedback studied with a conceptual model," Ecological Modelling, Elsevier, vol. 213(1), pages 127-132.
    2. Brovkin, Victor & Cherkinsky, Alexander & Goryachkin, Sergey, 2008. "Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia," Ecological Modelling, Elsevier, vol. 216(2), pages 178-187.
    3. Ulaganathan, Kandasamy & Goud, Sravanthi & Reddy, Madhavi & Kayalvili, Ulaganathan, 2017. "Genome engineering for breaking barriers in lignocellulosic bioethanol production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1080-1107.
    4. Agudelo, César Augusto Ruiz & Bustos, Sandra Liliana Hurtado & Moreno, Carmen Alicia Parrado, 2020. "Modeling interactions among multiple ecosystem services. A critical review," Ecological Modelling, Elsevier, vol. 429(C).
    5. Ouardighi, Fouad El & Sim, Jeong Eun & Kim, Bowon, 2016. "Pollution accumulation and abatement policy in a supply chain," European Journal of Operational Research, Elsevier, vol. 248(3), pages 982-996.
    6. Farrelly, Damien J. & Everard, Colm D. & Fagan, Colette C. & McDonnell, Kevin P., 2013. "Carbon sequestration and the role of biological carbon mitigation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 712-727.
    7. Yonghua Li & Song Yao & Hezhou Jiang & Huarong Wang & Qinchuan Ran & Xinyun Gao & Xinyi Ding & Dandong Ge, 2022. "Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China," Land, MDPI, vol. 11(12), pages 1-22, December.
    8. U. Persson & Christian Azar, 2007. "Tropical deforestation in a future international climate policy regime—lessons from the Brazilian Amazon," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 12(7), pages 1277-1304, August.
    9. Wang, Weilong & Xiao, Jing & Wei, Xiaolan & Ding, Jing & Wang, Xiaoxing & Song, Chunshan, 2014. "Development of a new clay supported polyethylenimine composite for CO2 capture," Applied Energy, Elsevier, vol. 113(C), pages 334-341.
    10. Arce, G.L.A.F. & Carvalho, J.A. & Nascimento, L.F.C., 2014. "A time series sequestration and storage model of atmospheric carbon dioxide," Ecological Modelling, Elsevier, vol. 272(C), pages 59-67.
    11. Sato, Hisashi & Itoh, Akihiko & Kohyama, Takashi, 2007. "SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach," Ecological Modelling, Elsevier, vol. 200(3), pages 279-307.
    12. Fouad El Ouardighi & Hassan Benchekroun & Dieter Grass, 2016. "Self-regenerating environmental absorption efficiency and the $$\varvec{ soylent~green~scenario}$$ s o y l e n t g r e e n s c e n a r i o," Annals of Operations Research, Springer, vol. 238(1), pages 179-198, March.
    13. Cuce, Pinar Mert & Riffat, Saffa, 2015. "A comprehensive review of heat recovery systems for building applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 665-682.
    14. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    15. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2020. "Climate change and green transitions in an agent-based integrated assessment model," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    16. Elizabeth Kopits & Alex L. Marten & Ann Wolverton, 2013. "Moving Forward with Incorporating "Catastrophic" Climate Change into Policy Analysis," NCEE Working Paper Series 201301, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Jan 2013.
    17. Yuting Zhou & Grace E. Klinger & Eric L. Hegg & Christopher M. Saffron & James E. Jackson, 2022. "Skeletal Ni electrode-catalyzed C-O cleavage of diaryl ethers entails direct elimination via benzyne intermediates," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    18. Wramneby, Anna & Smith, Benjamin & Zaehle, Sönke & Sykes, Martin T., 2008. "Parameter uncertainties in the modelling of vegetation dynamics—Effects on tree community structure and ecosystem functioning in European forest biomes," Ecological Modelling, Elsevier, vol. 216(3), pages 277-290.
    19. Yuzhou Zhang & Jian Gong & Jianxin Yang & Jin Peng, 2023. "Evaluation of Future Trends Based on the Characteristics of Net Primary Production (NPP) Changes over 21 Years in the Yangtze River Basin in China," Sustainability, MDPI, vol. 15(13), pages 1-19, July.
    20. Zhiwei Wan & Xi Chen & Min Ju & Chaohao Ling & Guangxu Liu & Siping Lin & Huihua Liu & Yulian Jia & Meixin Jiang & Fuqiang Liao, 2020. "Streamflow Reconstruction and Variation Characteristic Analysis of the Ganjiang River in China for the Past 515 Years," Sustainability, MDPI, vol. 12(3), pages 1-20, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:climat:v:129:y:2015:i:3:p:457-470. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.