How does bias correction of regional climate model precipitation affect modelled runoff?

Hydrology and Earth System Sciences

Volumn 19, Issue 2, 2015, Pages 711-728

  Teng, J ^a   Potter, N J ^a   Chiew, F H S ^a   Zhang, L ^a   Wang, B ^a   Vaze, J ^a   Evans, J P ^b  

^a CSIRO   (Australia)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CATCHMENTS; CLIMATE CHANGE; ERRORS; MAPPING; RUNOFF; WEATHER FORECASTING;

BIAS-CORRECTION METHODS; CORRECTED PRECIPITATION; DAILY PRECIPITATIONS; PRECIPITATION SEQUENCE; REGIONAL CLIMATE MODELING; REGIONAL CLIMATE MODELS; SOUTHEAST AUSTRALIA; WEATHER RESEARCH AND FORECASTING MODELS;

CLIMATE MODELS;

CLIMATE EFFECT; CLIMATE MODELING; ERROR CORRECTION; FLOW MODELING; HYDROLOGICAL MODELING; MAPPING; PRECIPITATION (CLIMATOLOGY); REGIONAL CLIMATE; RUNOFF;

AUSTRALIA;

EID: 84922495757     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-19-711-2015     Document Type: Article

References (56)

1. Arguëso, D., Evans, J. P., and Fita, L.: Precipitation bias correction of very high resolution regional climate models, Hydrol. Earth Syst. Sci., 17, 4379-4388, doi:10.5194/hess-17-4379-2013, 2013.
2. Bennett, J. C., Ling, F. L. N., Post, D. A., Grose, M. R., Corney, S. P., Graham, B., Holz, G. K., Katzfey, J. J., and Bindoff, N. L.: High-resolution projections of surface water availability for Tasmania, Australia, Hydrol. Earth Syst. Sci., 16, 1287-1303, doi:10.5194/hess-16-1287-2012, 2012.
3. Bennett, J. C., Grose, M. R., Corney, S. P., White, C. J., Holz, G. K., Katzfey, J. J., Post, D. A., and Bindoff, N. L.: Performance of an empirical bias-correction of a high-resolution climate data set, Int. J. Climatol., 34, 2189-2204, doi:10.1002/joc.3830, 2014.
4. Berg, P., Feldmann, H., and Panitz, H. J.: Bias correction of high resolution regional climate model data, J. Hydrol., 448-449, 80-92, doi:10.1016/j.jhydrol.2012.04.026, 2012.
5. Boe, J., Terray, L., Habets, F., and Martin, E.: Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies, Int. J. Climatol., 27, 1643-1655, doi:10.1002/joc.1602, 2007.
6. Burnash, R. J. C., Ferral, R. L., and McGuire, R. A.: A Generalised Streamflow Simulation System-Conceptual Modelling for Digital Computers, Technical Report, Joint Federal and State River Forecast Center, Sacramento, 204 pp., 1973.
7. Chakravarti, I. M. and Laha, R. G.: Handbook of Methods of Applied Statistics, John Wiley & Sons, New York, 460 pp., 1967.
8. Chen, J., Brissette, F. P., and Leconte, R.: Uncertainty of downscaling method in quantifying the impact of climate change on hydrology, J. Hydrol., 401, 190-202, doi:10.1016/j.jhydrol.2011.02.020, 2011a.
9. Chen, J., Brissette, F. P., Poulin, A., and Leconte, R.: Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed, Water Resour. Res., 47, W12509, doi:10.1029/2011wr010602, 2011b.
10. Chen, J., Brissette, F. P., Chaumont, D., and Braun, M.: Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America,Water Resour. Res., 49, 4187-4205, doi:10.1002/wrcr.20331, 2013.
11. Chiew, F. H. S. and McMahon, T. A.: The applicability of morton and penman evapotranspiration estimates in rainfall-runoff modeling,Water Resour. Bull., 27, 611-620, doi:10.1111/j.1752-1688.1991.tb01462.x, 1991.
12. Chiew, F. H. S., Young, W., Cai, W., and Teng, J.: Current drought and future hydroclimate projections in southeast Australia and implications for water resources management, Stoch. Env. Res. Risk A., 25, 601-612, doi:10.1007/s00477-010-0424-x, 2010.
13. Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709, doi:10.1029/2008gl035694, 2008.
14. Cloke, H. L., Wetterhall, F., He, Y., Freer, J. E., and Pappenberger, F.: Modelling climate impact on floods with ensemble climate projections, Q. J. Roy. Meteor. Soc., 139, 282-297, doi:10.1002/qj.1998, 2013.
15. Dosio, A., Paruolo, P., and Rojas, R.: Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: analysis of the climate change signal, J. Geophys. Res., 117, D17110, doi:10.1029/2012jd017968, 2012.
16. Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions "Should we apply bias correction to global and regional climate model data?", Hydrol. Earth Syst. Sci., 16, 3391-3404, doi:10.5194/hess-16-3391-2012, 2012.
17. Evans, J. P. and McCabe, M. F.: Regional climate simulation over Australia's Murray-Darling basin: a multitemporal assessment, J. Geophys. Res., 115, D14114, doi:10.1029/2010jd013816, 2010.
18. Evans, J. P., Ekström, M., and Ji, F.: Evaluating the performance of a WRF physics ensemble over South-East Australia, Clim. Dynam., 39, 1241-1258, doi:10.1007/s00382-011-1244-5, 2012.
19. Evans, J. P., Ji, F., Lee, C., Smith, P., Arguëso, D., and Fita, L.: Design of a regional climate modelling projection ensemble experiment-NARCliM, Geosci. Model Dev., 7, 621-629, doi:10.5194/gmd-7-621-2014, 2014.
20. Flaounas, E., Bastin, S., and Janicot, S.: Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF, Clim. Dynam., 36, 1083-1105, doi:10.1007/s00382-010-0785-3, 2011.
21. Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling, Int. J. Climatol., 27, 1547-1578, doi:10.1002/joc.1556, 2007.
22. Grillakis, M. G., Koutroulis, A. G., and Tsanis, I. K.: Multisegment statistical bias correction of daily GCM precipitation output, J. Geophys. Res., 118, 3150-3162, doi:10.1002/jgrd.50323, 2013.
23. Gudmundsson, L., Bremnes, J. B., Haugen, J. E., and Engen-Skaugen, T.: Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations-a comparison of methods, Hydrol. Earth Syst. Sci., 16, 3383-3390, doi:10.5194/hess-16-3383-2012, 2012.
24. Gutjahr, O. and Heinemann, G.: Comparing precipitation bias correction methods for high-resolution regional climate simulations using COSMO-CLM, Theor. Appl. Climatol., 114, 511-529, doi:10.1007/s00704-013-0834-z, 2013.
25. Gutowski, W. J., Decker, S. G., Donavon, R. A., Pan, Z. T., Arritt, R. W., and Takle, E. S.: Temporal-spatial scales of observed and simulated precipitation in central U.S. climate, J. Climate, 16, 3841-3847, doi:10.1175/1520-0442(2003)0162.0.co;2, 2003.
26. Hagemann, S., Chen, C., Haerter, J. O., Heinke, J., Gerten, D., and Piani, C.: Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models, J. Hydrometeorol., 12, 556-578, doi:10.1175/2011jhm1336.1, 2011.
27. Jeffrey, S. J., Carter, J. O., Moodie, K. B., and Beswick, A. R.: Using spatial interpolation to construct a comprehensive archive of Australian climate data, Environ. Modell. Softw., 16, 309-330, doi:10.1016/S1364-8152(01)00008-1, 2001.
28. Ji, F., Ekström, M., Evans, J., and Teng, J.: Evaluating rainfall patterns using physics scheme ensembles from a regional atmospheric model, Theor. Appl. Climatol., 115, 297-304, doi:10.1007/s00704-013-0904-2, 2014.
29. Johnson, F. and Sharma, A.: A nesting model for bias correction of variability at multiple time scales in general circulation model precipitation simulations, Water Resour. Res., 48, W01504, doi:10.1029/2011wr010464, 2012.
30. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C.,Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437-471, doi:10.1175/1520-0477(1996)0772.0.co;2, 1996.
31. Lafon, T.: Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods, Int. J. Climatol., 33, 1367-1381, doi:10.1002/joc.3518, 2013.
32. Lenderink, G., Buishand, A., and van Deursen, W.: Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach, Hydrol. Earth Syst. Sci., 11, 1145-1159, doi:10.5194/hess-11-1145-2007, 2007.
33. Li, H., Sheffield, J., and Wood, E. F.: Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching, J. Geophys. Res., 115, D10101, doi:10.1029/2009jd012882, 2010.
34. Maraun, D.: Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums, Geophys. Res. Lett., 39, L06706, doi:10.1029/2012gl051210, 2012.
35. Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J.,Widmann, M., Brienen, S., Rust, H.W., Sauter, T., Themeßl, M., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and Thiele-Eich, I.: Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user, Rev. Geophys., 48, RG3003, doi:10.1029/2009rg000314, 2010.
36. Muerth, M. J., Gauvin St-Denis, B., Ricard, S., Velázquez, J. A., Schmid, J., Minville, M., Caya, D., Chaumont, D., Ludwig, R., and Turcotte, R.: On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff, Hydrol. Earth Syst. Sci., 17, 1189-1204, doi:10.5194/hess-17-1189-2013, 2013.
37. Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I-A discussion of principles, J. Hydrol., 10, 282-290, doi:10.1016/0022-1694(70)90255-6, 1970.
38. Perrin, C., Michel, C., and Andreassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275-289, doi:10.1016/s0022-1694(03)00225-7, 2003.
39. Piani, C., Haerter, J. O., and Coppola, E.: Statistical bias correction for daily precipitation in regional climate models over Europe, Theor. Appl. Climatol., 99, 187-192, doi:10.1007/s00704-009-0134-9, 2010a.
40. Piani, C., Weedon, G. P., Best, M., Gomes, S. M., Viterbo, P., Hagemann, S., and Haerter, J. O.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199-215, doi:10.1016/j.jhydrol.2010.10.024, 2010b.
41. Potter, N. J. and Chiew, F. H. S.: An investigation into changes in climate characteristics causing the recent very low runoff in the southern Murray-Darling Basin using rainfall-runoff models, Water Resour. Res., 47, W00G10, doi:10.1029/2010wr010333, 2011.
42. Schmidli, J., Frei, C., and Vidale, P. L.: Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods, Int. J. Climatol., 26, 679-689, doi:10.1002/joc.1287, 2006.
43. Seaby, L. P., Refsgaard, J. C., Sonnenborg, T. O., Stisen, S., Christensen, J. H., and Jensen, K. H.: Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections, J. Hydrol., 486, 479-493, doi:10.1016/j.jhydrol.2013.02.015, 2013.
44. Smith, A., Freer, J., Bates, P., and Sampson, C.: Comparing ensemble projections of flooding against flood estimation by continuous simulation, J. Hydrol., 511, 205-219, doi:10.1016/j.jhydrol.2014.01.045, 2014.
45. Teng, J., Chiew, F. H. S., Timbal, B., Wang, Y., Vaze, J., and Wang, B.: Assessment of an analogue downscaling method for modelling climate change impacts on runoff, J. Hydrol., 472-473, 111-125, doi:10.1016/j.jhydrol.2012.09.024, 2012a.
46. Teng, J., Vaze, J., Chiew, F. H. S.,Wang, B., and Perraud, J.-M.: Estimating the relative uncertainties sourced from GCMs and hydrological models in modeling climate change impact on runoff, J. Hydrometeorol., 13, 122-139, doi:10.1175/jhm-d-11-058.1, 2012b.
47. Teutschbein, C. and Seibert, J.: Regional climate models for hydrological impact studies at the catchment scale: a review of recent modeling strategies, Geography Compass, 4, 834-860, doi:10.1111/j.1749-8198.2010.00357.x, 2010.
48. Teutschbein, C. and Seibert, J.: Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods, J. Hydrol., 456-457, 12-29, doi:10.1016/j.jhydrol.2012.05.052, 2012.
49. Teutschbein, C. and Seibert, J.: Is bias correction of regional climate model (RCM) simulations possible for nonstationary conditions?, Hydrol. Earth Syst. Sci., 17, 5061-5077, doi:10.5194/hess-17-5061-2013, 2013.
50. Themeßl, M. J., Gobiet, A., and Leuprecht, A.: Empirical-statistical downscaling and error correction of daily precipitation from regional climate models, Int. J. Climatol., 31, 1530-1544, doi:10.1002/joc.2168, 2011.
51. Vaze, J., Chiew, F. H. S., Perraud, J.-M., Viney, N., Post, D. A., Teng, J., Wang, B., Lerat, J., and Goswami, M.: Rainfall-runoff modelling across southeast Australia: data sets, models and results, Aust. J. Water Resour., 14, 101-116, 2010.
52. Vaze, J., Post, D. A., Chiew, F. H. S., Perraud, J.-M., Viney, N., and Teng, J.: Conceptual rainfall-runoff model performance with different spatial rainfall inputs, J. Hydrometeorol., 12, 1100-1112, doi:10.1175/2011JHM1340.1, 2011.
53. Viney, N. R., Perraud, J.-M., Vaze, J., Chiew, F. H. S., Post, D. A., and Yang, A.: The usefulness of bias constraints in model calibration for regionalisation to ungauged catchments, 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, Cairns, Australia, 13-17 July 2009, 3421-3427, 2009.
54. Wilby, R. L., Hay, L. E., Gutowski, W. J., Arritt, R. W., Takle, E. S., Pan, Z., Leavesley, G. H., and Clark, M. P.: Hydrological responses to dynamically and statistically downscaled climate model output, Geophys. Res. Lett., 27, 1199-1202, doi:10.1029/1999gl006078, 2000.
55. Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Clim. Change, 62, 189-216, doi:10.1023/B:CLIM.0000013685.99609.9e, 2004.
56. Yang, W., Andreasson, J., Graham, L. P., Olsson, J., Rosberg, J., and Wetterhall, F.: Distribution-based scaling to improve usability of regional climate model projections for hydrological climate change impacts studies, Hydrol. Res., 41, 211-229, doi:10.2166/nh.2010.004, 2010.