IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v145y2017i1d10.1007_s10584-017-2086-x.html
   My bibliography  Save this article

How reliable are GCM simulations for different atmospheric variables?

Author

Listed:
  • Sajjad Eghdamirad

    (Korea University)

  • Fiona Johnson

    (University of New South Wales)

  • Ashish Sharma

    (University of New South Wales)

Abstract

Considerable variability exists in simulations of the future climate. This variability is caused by differences in the parameterisations across general circulation models (GCMs), the initial conditions used and the different assumptions made as to how emissions will evolve in the future. As a result, there is considerable disagreement between available projections of climate variables, which can be used to quantify the uncertainty each variable exhibits. This leads to the question—which variables (or set of variables) are more reliable for use in climate change impact assessments. This research presents a framework to quantify the relative reliability amongst a range of upper air atmospheric variables. This is made possible by pooling simulations across multiple models, trajectories (scenarios) and initial conditions in a rank-transformed space. A metric named the variable reliability score (VRS) assesses the relative reliabilities across different atmospheric variables on a common scale. The VRS has been applied to calculate the total reliability as well as reliability from each source of uncertainty, namely model, scenarios and initial conditions. This comparison helps to decide if more models, scenarios or ensembles are required for uncertainty analysis of climate change impact assessment. The variables compared include geopotential height and its north-south difference, specific humidity, eastward wind and northward wind, all at the 500 and 850 hPa pressure levels. These variables were chosen based on availability of data and their documented use in previous climate change impact assessment studies worldwide. A regional assessment of VRS over 21 regions around the world shows that though the magnitude of VRS varies spatially, the ranked reliability of the variable rank remains relatively similar. On average, the lowest reliability is associated with geopotential height, whilst wind speeds and the north-south difference of geopotential height have higher reliability.

Suggested Citation

  • Sajjad Eghdamirad & Fiona Johnson & Ashish Sharma, 2017. "How reliable are GCM simulations for different atmospheric variables?," Climatic Change, Springer, vol. 145(1), pages 237-248, November.
    • Handle: RePEc:spr:climat:v:145:y:2017:i:1:d:10.1007_s10584-017-2086-x
    DOI: 10.1007/s10584-017-2086-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10584-017-2086-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10584-017-2086-x?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. Chong-yu Xu, 1999. "Climate Change and Hydrologic Models: A Review of Existing Gaps and Recent Research Developments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 13(5), pages 369-382, October.
    2. Sajjad Eghdamirad & Fiona Johnson & Ashish Sharma, 2017. "Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments," Climatic Change, Springer, vol. 142(1), pages 37-52, May.
    Full references (including those not matched with items on IDEAS)

    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. Manohar Arora & Pratap Singh & N. Goel & R. Singh, 2008. "Climate Variability Influences on Hydrological Responses of a Large Himalayan Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1461-1475, October.
    2. Syed Abu Shoaib & Mohammad Zaved Kaiser Khan & Nahid Sultana & Taufique H. Mahmood, 2021. "Quantifying Uncertainty in Food Security Modeling," Agriculture, MDPI, vol. 11(1), pages 1-16, January.
    3. Thanh Le & Deg-Hyo Bae, 2013. "Evaluating the Utility of IPCC AR4 GCMs for Hydrological Application in South Korea," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3227-3246, July.
    4. Xumin Zhang & Simin Qu & Jijie Shen & Yingbing Chen & Xiaoqiang Yang & Peng Jiang & Peng Shi, 2023. "Effect of Distinct Evaluation Objectives on Different Precipitation Downscaling Methods and the Corresponding Potential Impacts on Catchment Runoff Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1913-1930, March.
    5. Jan Niel & E. Uytven & P. Willems, 2019. "Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4319-4333, September.
    6. Block, Paul, 2011. "Power Ahead: Meeting Ethiopiaâ..s Energy Needs under a Changing Climate," WIDER Working Paper Series 090, World Institute for Development Economic Research (UNU-WIDER).
    7. Adham, Ammar & Wesseling, Jan G. & Abed, Rasha & Riksen, Michel & Ouessar, Mohamed & Ritsema, Coen J., 2019. "Assessing the impact of climate change on rainwater harvesting in the Oum Zessar watershed in Southeastern Tunisia," Agricultural Water Management, Elsevier, vol. 221(C), pages 131-140.
    8. Ibrahim Sufiyan & Razak Zakariya & Ibrahim Rosnan Yaacob, 2018. "Delineation Of Flood Risk Zones And 3D Modeling In Terengganu River Catchment Using Gis And Swat," Environment & Ecosystem Science (EES), Zibeline International Publishing, vol. 2(2), pages 1-5, January.
    9. Bin Wang & De Li Liu & Cathy Waters & Qiang Yu, 2018. "Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia," Climatic Change, Springer, vol. 151(2), pages 259-273, November.
    10. Konstantine Georgakakos & Deg-Hyo Bae & Chang-Sam Jeong, 2005. "Utility of Ten-Day Climate Model Ensemble Simulations for Water Resources Applications in Korean Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(6), pages 849-872, December.
    11. N. Amraoui & M. A. Sbai & P. Stollsteiner, 2019. "Assessment of Climate Change Impacts on Water Resources in the Somme River Basin (France)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 2073-2092, April.
    12. Jew Das & Nanduri V. Umamahesh, 2016. "Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5575-5587, December.
    13. Paul Block & Kenneth Strzepek, 2011. "Power Ahead: Meeting Ethiopia's Energy Needs Under a Changing Climate," WIDER Working Paper Series wp-2011-090, World Institute for Development Economic Research (UNU-WIDER).
    14. Kashish Sadhwani & T. I. Eldho, 2023. "Assessing the Vulnerability of Water Balance to Climate Change at River Basin Scale in Humid Tropics: Implications for a Sustainable Water Future," Sustainability, MDPI, vol. 15(11), pages 1-19, June.
    15. Luis Garrote, 2017. "Managing Water Resources to Adapt to Climate Change: Facing Uncertainty and Scarcity in a Changing Context," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2951-2963, August.
    16. Yog Aryal & Jianting Zhu, 2017. "On bias correction in drought frequency analysis based on climate models," Climatic Change, Springer, vol. 140(3), pages 361-374, February.
    17. Ling Zhang & Zhuotong Nan & Wenjun Yu & Yingchun Ge, 2015. "Modeling Land-Use and Land-Cover Change and Hydrological Responses under Consistent Climate Change Scenarios in the Heihe River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4701-4717, October.
    18. Daniela D’Agostino & Alessandra Scardigno & Nicola Lamaddalena & Daniel Chami, 2014. "Sensitivity Analysis of Coupled Hydro-Economic Models: Quantifying Climate Change Uncertainty for Decision-Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4303-4318, September.
    19. Axel Bronstert, 2003. "Floods and Climate Change: Interactions and Impacts," Risk Analysis, John Wiley & Sons, vol. 23(3), pages 545-557, June.
    20. Mohsen Nasseri & Banafsheh Zahraie & Ardalan Tootchi, 2019. "Spatial Scale Resolution of Prognostic Hydrological Models: Simulation Performance and Application in Climate Change Impact Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 189-205, January.

    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:145:y:2017:i:1:d:10.1007_s10584-017-2086-x. 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.