Downloads · May initialization · JJAS and its months

Files and code

• Screening: all scores, per-year values, diagnostics and screening statistics (JSON)7.2 MB · SHA-256 859abb70d9ae…
• Per-cell scores and distribution ratios (NetCDF)4.0 MB · SHA-256 32b99f7844c0…
• Confirmation: full-pipeline scores, selections and tests (JSON)3.5 MB · SHA-256 0903cc72196a…
• Corrected forecast members of every method (NetCDF)18.8 MB · SHA-256 46a8bda99ffa…
• Output manifest: SHA-256 of every screening output file (JSON)3 kB
• MVS ratio-limit study: screening (JSON)1.9 MB · SHA-256 dda3247f131b…
• MVS ratio-limit study: confirmation (JSON)1.2 MB · SHA-256 d965155fc957…
• Independent validation record: every method scored on the seasons after the benchmark (JSON)0.1 MB · SHA-256 8e6447358ddb…
• Full write-up (docs/47) at commit 9f39792Definitions, design, all result tables and the references, as of the code that produced these results
• Code at commit 9f39792scripts/bias_methods.py (methods), scripts/bias_benchmark.py (screening), scripts/bias_confirmation.py (confirmation), config/bias_correction/may_jjas.json (settings)

Run provenance

References

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2. Cannon, A. J., Sobie, S. R., & Murdock, T. Q. (2015). Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes? Journal of Climate, 28, 6938–6959. doi:10.1175/JCLI-D-14-00754.1
3. Delle Monache, L., Hacker, J. P., Zhou, Y., Deng, X., & Stull, R. B. (2006). Probabilistic aspects of meteorological and ozone regional ensemble forecasts. Journal of Geophysical Research: Atmospheres, 111, D24307. doi:10.1029/2005JD006917
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5. Gudmundsson, L., Bremnes, J. B., Haugen, J. E., & Engen-Skaugen, T. (2012). Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations — a comparison of methods. Hydrology and Earth System Sciences, 16, 3383–3390. doi:10.5194/hess-16-3383-2012
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7. Johnson, S. J., Stockdale, T. N., Ferranti, L., et al. (2019). SEAS5: the new ECMWF seasonal forecast system. Geoscientific Model Development, 12, 1087–1117. doi:10.5194/gmd-12-1087-2019
8. Leander, R., & Buishand, T. A. (2007). Resampling of regional climate model output for the simulation of extreme river flows. Journal of Hydrology, 332, 487–496. doi:10.1016/j.jhydrol.2006.08.006
9. Lenderink, G., Buishand, A., & van Deursen, W. (2007). Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrology and Earth System Sciences, 11, 1145–1159. doi:10.5194/hess-11-1145-2007
10. Manzanas, R., Gutiérrez, J. M., Bhend, J., et al. (2019). Bias adjustment and ensemble recalibration methods for seasonal forecasting: a comprehensive intercomparison using the C3S dataset. Climate Dynamics, 53, 1287–1305. doi:10.1007/s00382-019-04640-4
11. Michelangeli, P.-A., Vrac, M., & Loukos, H. (2009). Probabilistic downscaling approaches: application to wind cumulative distribution functions. Geophysical Research Letters, 36, L11708. doi:10.1029/2009GL038401
12. Piani, C., Weedon, G. P., Best, M., et al. (2010). Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. Journal of Hydrology, 395, 199–215. doi:10.1016/j.jhydrol.2010.10.024
13. Schmidli, J., Frei, C., & Vidale, P. L. (2006). Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods. International Journal of Climatology, 26, 679–689. doi:10.1002/joc.1287
14. Switanek, M. B., Troch, P. A., Castro, C. L., et al. (2017). Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes. Hydrology and Earth System Sciences, 21, 2649–2666. doi:10.5194/hess-21-2649-2017
15. Teutschbein, C., & Seibert, J. (2012). Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods. Journal of Hydrology, 456–457, 12–29. doi:10.1016/j.jhydrol.2012.05.052
16. Themeßl, M. J., Gobiet, A., & Leuprecht, A. (2011). Empirical-statistical downscaling and error correction of daily precipitation from regional climate models. International Journal of Climatology, 31, 1530–1544. doi:10.1002/joc.2168
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18. Vrac, M., Drobinski, P., Merlo, A., et al. (2012). Dynamical and statistical downscaling of the French Mediterranean climate: uncertainty assessment. Natural Hazards and Earth System Sciences, 12, 2769–2784. doi:10.5194/nhess-12-2769-2012