Articles | Volume 20, issue 8
https://doi.org/10.5194/nhess-20-2243-2020
https://doi.org/10.5194/nhess-20-2243-2020
Research article
 | 
17 Aug 2020
Research article |  | 17 Aug 2020

Bias correction of a gauge-based gridded product to improve extreme precipitation analysis in the Yarlung Tsangpo–Brahmaputra River basin

Xian Luo, Xuemei Fan, Yungang Li, and Xuan Ji

Related subject area

Atmospheric, Meteorological and Climatological Hazards
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024,https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024,https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary
Probabilistic short-range forecasts of high-precipitation events: optimal decision thresholds and predictability limits
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024,https://doi.org/10.5194/nhess-24-2793-2024, 2024
Short summary
Surprise floods: the role of our imagination in preparing for disasters
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024,https://doi.org/10.5194/nhess-24-2633-2024, 2024
Short summary
Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024,https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary

Cited articles

Alexander, L. V.: Global observed long-term changes in temperature and precipitation extremes: A review of progress and limitations in IPCC assessments and beyond, Weather. Clim. Extremes, 11, 4–16, https://doi.org/10.1016/j.wace.2015.10.007, 2016. 
Andermann, C., Bonnet, S., and Gloaguen, R.: Evaluation of precipitation data sets along the Himalayan front, Geochem. Geophys. Geosys., 12, Q07023, https://doi.org/10.1029/2011gc003513, 2011. 
Bookhagen, B. and Burbank, D. W.: Toward a complete Himalayan hydrological budget: Spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge, J. Geophys. Res., 115, F03019, https://doi.org/10.1029/2009JF001426, 2010. 
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?, J. Climate, 28, 6938–6959, https://doi.org/10.1175/JCLI-D-14-00754.1, 2015. 
Chaudhary S., Dhanya C. T., and Vinnarasi R.: Dry and wet spell variability during monsoon in gauge-based gridded daily precipitation datasets over India, J. Hydrol., 546, 204–218, https://doi.org/10.1016/j.jhydrol.2017.01.023, 2017. 
Download
Short summary
In this study, we corrected Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) in the Yarlung Tsangpo–Brahmaputra River Basin using both linear and nonlinear methods, and their influences on resulting extreme precipitation indices were assessed. Results showed that all methods were able to correct mean precipitation, but their ability to correct wet-day frequency and coefficient of variation were markedly different.
Altmetrics
Final-revised paper
Preprint