Articles | Volume 30, issue 2
https://doi.org/10.5194/hess-30-421-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Technical note
| 
28 Jan 2026
Technical note |
| 28 Jan 2026
| 28 Jan 2026
Technical note: Including hydrologic impact definition in climate projection uncertainty partitioning: a case study of the Central American mid-summer drought
Related authors
Hydrol. Earth Syst. Sci., 26, 1425–1437, 2022
Cited articles
Aitken, G., Beevers, L., Parry, S., and Facer-Childs, K.: Partitioning model uncertainty in multi-model ensemble river flow projections, Climatic Change, 176, 153, https://doi.org/10.1007/s10584-023-03621-1, 2023.
Alfaro, E. J.: Caracterización del “veranillo” en dos cuencas de la vertiente del Pacífico de Costa Rica, América Central, Rev. Biol. Trop. J. Trop. Biol. Conserv., 62, 1–15, https://doi.org/10.15517/rbt.v62i4.20010, 2014.
Anderson, T., Anchukaitis, K., Pons, D., and Taylor, M.: Multiscale trends and precipitation extremes in the Central American Midsummer Drought, Environmental Research Letters, 14, 124016, https://doi.org/10.1088/1748-9326/ab5023, 2019.
Bosshard, T., Carambia, M., Goergen, K., Kotlarski, S., Krahe, P., Zappa, M., and Schär, C.: Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections, Water Resources Research, 49, 1523–1536, https://doi.org/10.1029/2011WR011533, 2013.
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?, Journal of Climate, 28, 6938–6959, https://doi.org/10.1175/JCLI-D-14-00754.1, 2015.
