Articles | Volume 17, issue 6
https://doi.org/10.5194/hess-17-2147-2013
https://doi.org/10.5194/hess-17-2147-2013
Research article
 | 
07 Jun 2013
Research article |  | 07 Jun 2013

Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction

E. P. Maurer, T. Das, and D. R. Cayan

Related authors

The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes
Edwin P. Maurer, Iris T. Stewart, Kenneth Joseph, and Hugo G. Hidalgo
Hydrol. Earth Syst. Sci., 26, 1425–1437, https://doi.org/10.5194/hess-26-1425-2022,https://doi.org/10.5194/hess-26-1425-2022, 2022
Short summary
Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies
E. P. Maurer, D. L. Ficklin, and W. Wang
Hydrol. Earth Syst. Sci., 20, 685–696, https://doi.org/10.5194/hess-20-685-2016,https://doi.org/10.5194/hess-20-685-2016, 2016
Short summary
Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers
D. L. Ficklin, B. L. Barnhart, J. H. Knouft, I. T. Stewart, E. P. Maurer, S. L. Letsinger, and G. W. Whittaker
Hydrol. Earth Syst. Sci., 18, 4897–4912, https://doi.org/10.5194/hess-18-4897-2014,https://doi.org/10.5194/hess-18-4897-2014, 2014
Short summary
Bias correction can modify climate model simulated precipitation changes without adverse effect on the ensemble mean
E. P. Maurer and D. W. Pierce
Hydrol. Earth Syst. Sci., 18, 915–925, https://doi.org/10.5194/hess-18-915-2014,https://doi.org/10.5194/hess-18-915-2014, 2014

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Uncertainty analysis
Daytime-only mean data enhance understanding of land–atmosphere coupling
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023,https://doi.org/10.5194/hess-27-861-2023, 2023
Short summary
Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning
Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, and Zeqiang Chen
Hydrol. Earth Syst. Sci., 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022,https://doi.org/10.5194/hess-26-2923-2022, 2022
Short summary
Unraveling the contribution of potential evaporation formulation to uncertainty under climate change
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, and Lila Collet
Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022,https://doi.org/10.5194/hess-26-2147-2022, 2022
Short summary
Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022,https://doi.org/10.5194/hess-26-1001-2022, 2022
Short summary
Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems
Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos
Hydrol. Earth Syst. Sci., 26, 197–220, https://doi.org/10.5194/hess-26-197-2022,https://doi.org/10.5194/hess-26-197-2022, 2022
Short summary

Cited articles

Abatzoglou, J. T. and Brown, T. J.: A comparison of statistical downscaling methods suited for wildfire applications, Int. J. Climatol., 32, 772–780, https://doi.org/10.1002/joc.2312, 2012.
AchutaRao, K. M. and Sperber, K. R.: ENSO Simulation in Coupled Ocean-Atmosphere Models: Are the Current Models Better?, Clim. Dynam., 27, 1–15, https://doi.org/10.1007/s00382-006-0119-7, 2006.
Ballester, J., Giorgi, F., and Rodo, X.: Changes in European temperature extremes can be predicted from changes in PDF central statistics, Climatic Change, 98, 277–284, https://doi.org/10.1007/s10584-009-9758-0, 2010.
Boé, 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, https://doi.org/10.1002/joc.1602, 2007.
Bürger, G., Murdock, T. Q., Werner, A. T., Sobie, S. R., and Cannon, A. J.: Downscaling Extremes – An Intercomparison of Multiple Statistical Methods for Present Climate, J. Climate, 25, 4366–4388, https://doi.org/10.1175/jcli-d-11-00408.1, 2012.
Download