IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v120y2013i4p871-887.html
   My bibliography  Save this article

Multi-variable error correction of regional climate models

Author

Listed:
  • Renate Wilcke
  • Thomas Mendlik
  • Andreas Gobiet

Abstract

Climate change impact research needs regional climate scenarios of multiple meteorological variables. Those variables are available from regional climate models (RCMs), but affected by considerable biases. We evaluate the application of an empirical-statistical error correction method, quantile mapping (QM), for a small ensemble of RCMs and six meteorological variables. Annual and monthly biases are reduced to close to zero by QM for all variables in most cases. Exceptions are found, if non-stationarity of the model’s error characteristics occur. Even in the worst cases of non-stationarity, QM clearly improves the biases of raw RCMs. In addition, QM successfully adjusts the distributions of the analysed variables. To approach the question whether time series and inter-variable relationships are still plausible after correction, we evaluate the root-mean-square error (RMSE), autocorrelation and inter-variable correlation. We found improvement or no clear effect in RMSE and autocorrelation, and no clear effect on the correlation between meteorological variables. These results demonstrate that QM retains the quality of the temporal structure in time series and the inter-variable dependencies of RCMs. It has to be emphasised that this cannot be interpreted as an improvement and that deficiencies of the RCMs in those features are retained as well. Our results give some indication for the performance of QM applied to future scenarios, since our evaluation relies on independent calibration and evaluation periods, which are affected by climate variability and change. The effect of non-stationarity, however, can be expected to be larger in far future. We demonstrate the retainment of the RCM’s temporal structure and inter-variable dependencies, and large improvements in biases. This qualifies QM as a valuable, though not perfect, method in the interface between climate models and climate change impact research. Nonetheless, in case of no correlation between re-analysis driven RCM and observation, one should consider that QM does not correct this correlation. Copyright The Author(s) 2013

Suggested Citation

  • Renate Wilcke & Thomas Mendlik & Andreas Gobiet, 2013. "Multi-variable error correction of regional climate models," Climatic Change, Springer, vol. 120(4), pages 871-887, October.
    • Handle: RePEc:spr:climat:v:120:y:2013:i:4:p:871-887
    DOI: 10.1007/s10584-013-0845-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10584-013-0845-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10584-013-0845-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. Matthias Themeßl & Andreas Gobiet & Georg Heinrich, 2012. "Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal," Climatic Change, Springer, vol. 112(2), pages 449-468, May.
    2. Henri Caussinus & Olivier Mestre, 2004. "Detection and correction of artificial shifts in climate series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 405-425, August.
    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. A. Casanueva & M. Frías & S. Herrera & D. San-Martín & K. Zaninovic & J. Gutiérrez, 2014. "Statistical downscaling of climate impact indices: testing the direct approach," Climatic Change, Springer, vol. 127(3), pages 547-560, December.
    2. Pascalle Smith & Georg Heinrich & Martin Suklitsch & Andreas Gobiet & Markus Stoffel & Jürg Fuhrer, 2014. "Station-scale bias correction and uncertainty analysis for the estimation of irrigation water requirements in the Swiss Rhone catchment under climate change," Climatic Change, Springer, vol. 127(3), pages 521-534, December.
    3. Philippe Roudier & Jafet Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    4. Kamruzzaman, Mohammad & Hwang, Syewoon & Choi, Soon-Kun & Cho, Jaepil & Song, Inhong & Jeong, Hanseok & Song, Jung-Hun & Jang, Teail & Yoo, Seung-Hwan, 2020. "Prediction of the effects of management practices on discharge and mineral nitrogen yield from paddy fields under future climate using APEX-paddy model," Agricultural Water Management, Elsevier, vol. 241(C).
    5. A. Casanueva & J. Bedia & S. Herrera & J. Fernández & J. M. Gutiérrez, 2018. "Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool," Climatic Change, Springer, vol. 147(3), pages 411-425, April.
    6. Yi Yang & Jianping Tang, 2023. "Downscaling and uncertainty analysis of future concurrent long-duration dry and hot events in China," Climatic Change, Springer, vol. 176(2), pages 1-25, February.
    7. Lagergren, Fredrik & Jönsson, Anna Maria, 2017. "Ecosystem model analysis of multi-use forestry in a changing climate," Ecosystem Services, Elsevier, vol. 26(PA), pages 209-224.
    8. Markus Stoffel & Thomas Mendlik & Michelle Schneuwly-Bollschweiler & Andreas Gobiet, 2014. "Possible impacts of climate change on debris-flow activity in the Swiss Alps," Climatic Change, Springer, vol. 122(1), pages 141-155, January.
    9. Maikel Mendez & Luis-Alexander Calvo-Valverde & Pablo Imbach & Ben Maathuis & David Hein-Grigg & Jorge-Andrés Hidalgo-Madriz & Luis-Fernando Alvarado-Gamboa, 2022. "Hydrological Response of Tropical Catchments to Climate Change as Modeled by the GR2M Model: A Case Study in Costa Rica," Sustainability, MDPI, vol. 14(24), pages 1-31, December.
    10. Lorenzo Sangelantoni & Eleonora Gioia & Fausto Marincioni, 2018. "Impact of climate change on landslides frequency: the Esino river basin case study (Central Italy)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 849-884, September.
    11. Mohamed Salem Nashwan & Shamsuddin Shahid & Eun-Sung Chung, 2020. "High-Resolution Climate Projections for a Densely Populated Mediterranean Region," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    12. Jönsson, Anna Maria & Lagergren, Fredrik, 2018. "Effects of climate and soil conditions on the productivity and defence capacity of Picea abies in Sweden—An ecosystem model assessment," Ecological Modelling, Elsevier, vol. 384(C), pages 154-167.
    13. Victoria M. Garibay & Margaret W. Gitau & Nicholas Kiggundu & Daniel Moriasi & Fulgence Mishili, 2021. "Evaluation of Reanalysis Precipitation Data and Potential Bias Correction Methods for Use in Data-Scarce Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1587-1602, March.
    14. Xu Chen & Ruiguang Han & Ping Feng & Yongjie Wang, 2022. "Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1305-1337, January.
    15. Zafar Iqbal & Shamsuddin Shahid & Tarmizi Ismail & Zulfaqar Sa’adi & Aitazaz Farooque & Zaher Mundher Yaseen, 2022. "Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    16. Chantal Donnelly & Wouter Greuell & Jafet Andersson & Dieter Gerten & Giovanna Pisacane & Philippe Roudier & Fulco Ludwig, 2017. "Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level," Climatic Change, Springer, vol. 143(1), pages 13-26, July.
    17. Roland Kaitna & Andreas Gobiet & Franz Sinabell & Markus Stoffel, 2014. "DEUCALION – Determining and Visualising Impacts of Greenhouse Climate Rainfall in Alpine Watersheds on Torrential Disasters," WIFO Studies, WIFO, number 59816.
    18. 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.
    19. Philippe Roudier & Jafet C. M. Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    20. Dengpan Xiao & Huizi Bai & De Li Liu, 2018. "Impact of Future Climate Change on Wheat Production: A Simulated Case for China’s Wheat System," Sustainability, MDPI, vol. 10(4), pages 1-15, April.

    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. Salem, Golam Saleh Ahmed & Kazama, So & Shahid, Shamsuddin & Dey, Nepal C., 2018. "Impacts of climate change on groundwater level and irrigation cost in a groundwater dependent irrigated region," Agricultural Water Management, Elsevier, vol. 208(C), pages 33-42.
    2. V. Savo & K. E. Kohfeld & J. Sillmann & C. Morton & J. Bailey & A. S. Haslerud & C. Le Quéré & D. Lepofsky, 2024. "Using human observations with instrument-based metrics to understand changing rainfall patterns," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    4. He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
    5. Markus Stoffel & Thomas Mendlik & Michelle Schneuwly-Bollschweiler & Andreas Gobiet, 2014. "Possible impacts of climate change on debris-flow activity in the Swiss Alps," Climatic Change, Springer, vol. 122(1), pages 141-155, January.
    6. Azaïs, Jean-Marc & Ribes, Aurélien, 2016. "Multivariate spline analysis for multiplicative models: Estimation, testing and application to climate change," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 38-53.
    7. Lledó, Ll. & Torralba, V. & Soret, A. & Ramon, J. & Doblas-Reyes, F.J., 2019. "Seasonal forecasts of wind power generation," Renewable Energy, Elsevier, vol. 143(C), pages 91-100.
    8. A. Casanueva & J. Bedia & S. Herrera & J. Fernández & J. M. Gutiérrez, 2018. "Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool," Climatic Change, Springer, vol. 147(3), pages 411-425, April.
    9. Elvina Faustina Dhata & Chang Ki Kim & Hyun-Goo Kim & Boyoung Kim & Myeongchan Oh, 2022. "Site-Adaptation for Correcting Satellite-Derived Solar Irradiance: Performance Comparison between Various Regressive and Distribution Mapping Techniques for Application in Daejeon, South Korea," Energies, MDPI, vol. 15(23), pages 1-20, November.
    10. S.M. Vicente-Serrano & A. El Kenawy & C. Azorin-Molina & O. Chura & F. Trujillo & E. Aguilar & N. Martín-Hernández & J.I. López-Moreno & A. Sanchez-Lorenzo & E. Moran-Tejeda & J. Revuelto & P. Ycaza &, 2016. "Average monthly and annual climate maps for Bolivia," Journal of Maps, Taylor & Francis Journals, vol. 12(2), pages 295-310, March.
    11. S. Dahech & G. Beltrando, 2012. "Observed temperature evolution in the City of Sfax (Middle Eastern Tunisia) for the period 1950–2007," Climatic Change, Springer, vol. 114(3), pages 689-706, October.
    12. Philippe Roudier & Jafet Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    13. Gumindoga, W. & Rientjes, T. H. M. & Haile, Alemseged Tamiru & Makurira, H. & Reggiani, P., 2019. "Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River Basin," Papers published in Journals (Open Access), International Water Management Institute, pages 23(7):2915-.
    14. Schönhart, Martin & Mitter, Hermine & Schmid, Erwin & Heinrich, Georg & Gobiet, Andreas, 2014. "Integrated Analysis of Climate Change Impacts and Adaptation Measures in Austrian Agriculture," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(3).
    15. Jie Shen & Colin M. Gallagher & QiQi Lu, 2014. "Detection of multiple undocumented change-points using adaptive Lasso," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1161-1173, June.
    16. Polo, Jesús & Ballestrín, Jesús & Carra, Elena, 2020. "Assessment and improvement of modeling the atmospheric attenuation based on aerosol optical depth information with applicability to solar tower plants," Energy, Elsevier, vol. 208(C).
    17. Philippe Roudier & Jafet C. M. Andersson & Chantal Donnelly & Luc Feyen & Wouter Greuell & Fulco Ludwig, 2016. "Projections of future floods and hydrological droughts in Europe under a +2°C global warming," Climatic Change, Springer, vol. 135(2), pages 341-355, March.
    18. Picard, F. & Lebarbier, E. & Budinskà, E. & Robin, S., 2011. "Joint segmentation of multivariate Gaussian processes using mixed linear models," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1160-1170, February.
    19. Leibin Wang & Robert V. Rohli & Qigen Lin & Shaofei Jin & Xiaodong Yan, 2022. "Impact of Extreme Heatwaves on Population Exposure in China Due to Additional Warming," Sustainability, MDPI, vol. 14(18), pages 1-13, September.
    20. Jie Chen & Xunchang John Zhang, 2021. "Challenges and potential solutions in statistical downscaling of precipitation," Climatic Change, Springer, vol. 165(3), pages 1-19, April.

    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:4:p:871-887. 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.