IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v120y2013i1p249-261.html
   My bibliography  Save this article

A comparison of downscaling techniques in the projection of local climate change and wheat yields

Author

Listed:
  • Qunying Luo
  • Li Wen
  • John McGregor
  • Bertrand Timbal

Abstract

This study aims to evaluate the performance of two mainstream downscaling techniques: statistical and dynamical downscaling and to compare the differences in their projection of future climate change and the resultant impact on wheat crop yields for three locations across New South Wales, Australia. Bureau of Meteorology statistically- and CSIRO dynamically-downscaled climate, derived or driven by the CSIRO Mk 3.5 coupled general circulation model, were firstly evaluated against observed climate data for the period 1980–1999. Future climate projections derived from the two downscaling approaches for the period centred on 2055 were then compared. A stochastic weather generator, LARS-WG, was used in this study to derive monthly climate changes and to construct climate change scenarios. The Agricultural Production System sIMulator-Wheat model was then combined with the constructed climate change scenarios to quantify the impact of climate change on wheat grain yield. Statistical results show that (1) in terms of reproducing the past climate, statistical downscaling performed better over dynamical downscaling in most of the cases including climate variables, their mean, variance and distribution, and study locations, (2) there is significant difference between the two downscaling techniques in projected future climate change except the mean value of rainfall across the three locations for most of the months; and (3) there is significant difference in projected wheat grain yields between the two downscaling techniques at two of the three locations. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Qunying Luo & Li Wen & John McGregor & Bertrand Timbal, 2013. "A comparison of downscaling techniques in the projection of local climate change and wheat yields," Climatic Change, Springer, vol. 120(1), pages 249-261, September.
  • Handle: RePEc:spr:climat:v:120:y:2013:i:1:p:249-261
    DOI: 10.1007/s10584-013-0802-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-013-0802-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10584-013-0802-8?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 A. Stott & J. A. Kettleborough, 2002. "Erratum: Origins and estimates of uncertainty in predictions of twenty-first century temperature rise," Nature, Nature, vol. 417(6885), pages 205-205, May.
    2. Luo, Qunying & Williams, Martin A. J. & Bellotti, William & Bryan, Brett, 2003. "Quantitative and visual assessments of climate change impacts on South Australian wheat production," Agricultural Systems, Elsevier, vol. 77(3), pages 173-186, September.
    3. Probert, M. E. & Dimes, J. P. & Keating, B. A. & Dalal, R. C. & Strong, W. M., 1998. "APSIM's water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems," Agricultural Systems, Elsevier, vol. 56(1), pages 1-28, January.
    4. Peter A. Stott & J. A. Kettleborough, 2002. "Origins and estimates of uncertainty in predictions of twenty-first century temperature rise," Nature, Nature, vol. 416(6882), pages 723-726, April.
    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. Luo, Qunying & Bange, Michael & Braunack, Michael & Johnston, David, 2016. "Effectiveness of agronomic practices in dealing with climate change impacts in the Australian cotton industry — A simulation study," Agricultural Systems, Elsevier, vol. 147(C), pages 1-9.
    2. A. Casanueva & S. Herrera & J. Fernández & J.M. Gutiérrez, 2016. "Towards a fair comparison of statistical and dynamical downscaling in the framework of the EURO-CORDEX initiative," Climatic Change, Springer, vol. 137(3), pages 411-426, August.
    3. Qunying Luo & Michael Bange & David Johnston, 2016. "Environment and cotton fibre quality," Climatic Change, Springer, vol. 138(1), pages 207-221, September.
    4. Stella Tsoka & Kondylia Velikou & Konstantia Tolika & Aikaterini Tsikaloudaki, 2021. "Evaluating the Combined Effect of Climate Change and Urban Microclimate on Buildings’ Heating and Cooling Energy Demand in a Mediterranean City," Energies, MDPI, vol. 14(18), pages 1-23, 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. Tonnang, Henri E.Z. & Hervé, Bisseleua D.B. & Biber-Freudenberger, Lisa & Salifu, Daisy & Subramanian, Sevgan & Ngowi, Valentine B. & Guimapi, Ritter Y.A. & Anani, Bruce & Kakmeni, Francois M.M. & Aff, 2017. "Advances in crop insect modelling methods—Towards a whole system approach," Ecological Modelling, Elsevier, vol. 354(C), pages 88-103.
    2. A. Lopez & E. Suckling & F. Otto & A. Lorenz & D. Rowlands & M. Allen, 2015. "Towards a typology for constrained climate model forecasts," Climatic Change, Springer, vol. 132(1), pages 15-29, September.
    3. Timothy Garrett, 2011. "Are there basic physical constraints on future anthropogenic emissions of carbon dioxide?," Climatic Change, Springer, vol. 104(3), pages 437-455, February.
    4. Jean Charles Hourcade & Franck Lecocq, 2003. "Le taux d'actualisation contre le principe de précaution ? Leçons à partir du cas des politiques climatiques," Working Papers halshs-00000967, HAL.
    5. Jenny Cifuentes & Geovanny Marulanda & Antonio Bello & Javier Reneses, 2020. "Air Temperature Forecasting Using Machine Learning Techniques: A Review," Energies, MDPI, vol. 13(16), pages 1-28, August.
    6. Simon Gosling & Jason Lowe & Glenn McGregor & Mark Pelling & Bruce Malamud, 2009. "Associations between elevated atmospheric temperature and human mortality: a critical review of the literature," Climatic Change, Springer, vol. 92(3), pages 299-341, February.
    7. Xavier Rodó & Mercedes Pascual & Francisco Doblas-Reyes & Alexander Gershunov & Dáithí Stone & Filippo Giorgi & Peter Hudson & James Kinter & Miquel-Àngel Rodríguez-Arias & Nils Stenseth & David Alons, 2013. "Climate change and infectious diseases: Can we meet the needs for better prediction?," Climatic Change, Springer, vol. 118(3), pages 625-640, June.
    8. Kesten C. Green & J. Scott Armstrong, 2007. "Global Warming: Forecasts by Scientists Versus Scientific Forecasts," Energy & Environment, , vol. 18(7), pages 997-1021, December.
    9. Yeon-Hee Kim & Seung-Ki Min & Nathan P. Gillett & Dirk Notz & Elizaveta Malinina, 2023. "Observationally-constrained projections of an ice-free Arctic even under a low emission scenario," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    10. Taylor, Chris & Cullen, Brendan & D'Occhio, Michael & Rickards, Lauren & Eckard, Richard, 2018. "Trends in wheat yields under representative climate futures: Implications for climate adaptation," Agricultural Systems, Elsevier, vol. 164(C), pages 1-10.
    11. Muhammad Aamir Khan & Alishba Tahir & Nabila Khurshid & Muhammad Iftikhar ul Husnain & Mukhtar Ahmed & Houcine Boughanmi, 2020. "Economic Effects of Climate Change-Induced Loss of Agricultural Production by 2050: A Case Study of Pakistan," Sustainability, MDPI, vol. 12(3), pages 1-17, February.
    12. Grotelüschen, Kristina & Gaydon, Donald S. & Langensiepen, Matthias & Ziegler, Susanne & Kwesiga, Julius & Senthilkumar, Kalimuthu & Whitbread, Anthony M. & Becker, Mathias, 2021. "Assessing the effects of management and hydro-edaphic conditions on rice in contrasting East African wetlands using experimental and modelling approaches," Agricultural Water Management, Elsevier, vol. 258(C).
    13. Marcos Jiménez Martínez & Christine Fürst, 2021. "Simulating the Capacity of Rainfed Food Crop Species to Meet Social Demands in Sudanian Savanna Agro-Ecologies," Land, MDPI, vol. 10(8), pages 1-28, August.
    14. Yang, Xuan & Zheng, Lina & Yang, Qian & Wang, Zikui & Cui, Song & Shen, Yuying, 2018. "Modelling the effects of conservation tillage on crop water productivity, soil water dynamics and evapotranspiration of a maize-winter wheat-soybean rotation system on the Loess Plateau of China using," Agricultural Systems, Elsevier, vol. 166(C), pages 111-123.
    15. Farquharson, Robert J. & Cacho, Oscar J. & Mullen, John D., 2005. "An economic approach to soil fertility management for wheat production in New South Wales and Queensland," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137866, Australian Agricultural and Resource Economics Society.
    16. Chauhan, Yashvir S., 2010. "Potential productivity and water requirements of maize-peanut rotations in Australian semi-arid tropical environments--A crop simulation study," Agricultural Water Management, Elsevier, vol. 97(3), pages 457-464, March.
    17. Oliver, Yvette M. & Robertson, Michael J. & Weeks, Cameron, 2010. "A new look at an old practice: Benefits from soil water accumulation in long fallows under Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 98(2), pages 291-300, December.
    18. Palosuo, Taru & Hoffmann, Munir P. & Rötter, Reimund P. & Lehtonen, Heikki S., 2021. "Sustainable intensification of crop production under alternative future changes in climate and technology: The case of the North Savo region," Agricultural Systems, Elsevier, vol. 190(C).
    19. Andrew L. Fletcher & Chao Chen & Noboru Ota & Roger A. Lawes & Yvette M. Oliver, 2020. "Has historic climate change affected the spatial distribution of water-limited wheat yield across Western Australia?," Climatic Change, Springer, vol. 159(3), pages 347-364, April.
    20. Zhang, Yuxi & Walker, Jeffrey P. & Pauwels, Valentijn R.N., 2022. "Assimilation of wheat and soil states for improved yield prediction: The APSIM-EnKF framework," Agricultural Systems, Elsevier, vol. 201(C).

    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:120:y:2013:i:1:p:249-261. 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.