Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

An improved bias correction scheme based on comparative precipitation characteristics

Kim, Kue Bum, Bray, Michaela ORCID: https://orcid.org/0000-0002-6850-6572 and Han, Dawei 2015. An improved bias correction scheme based on comparative precipitation characteristics. Hydrological Processes 29 (9) , pp. 2258-2266. 10.1002/hyp.10366

Full text not available from this repository.

Abstract

Bias correction is a necessary post-processing procedure in order to use regional climate model (RCM) simulated local climate variables as the input data for hydrological models owing to systematic errors of RCMs. Most of present bias correction methods adjust statistical properties between observed and simulated data on the basis of calendar periods, e.g. month or season. However, this matching statistic is only a necessary condition, not a sufficient condition, as temporal distribution of the precipitation between observed and simulated data is ignored. This study suggests an improved bias correction scheme that considers not only statistical properties but also the temporal distribution between the time series of observed and modelled data. The ratio of the observed precipitation to simulated precipitation is used to compare the behaviour between the observed and modelled precipitation data, and three criteria are proposed when dividing bias correction periods: (1) underestimation of precipitation, (2) stability of /underestimation of precipitation, (2) stability of precipitation ratio and (3) oscillation of precipitation ratio. The results show that the output of the proposed bias correction method follows the trend of the observed precipitation better than that of the conventional bias correction method. This study indicates that temporal distribution should not be ignored when choosing a comparison period for bias correction. However, the study is only a preliminary attempt to address this important issue, and we hope it will stimulate more research activities to improve the methodology. Future efforts on several unsolved problems have been suggested such as how to find out the optimal group number to avoid the overfitting and underfitting conditions.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
Publisher: Wiley
ISSN: 0885-6087
Date of Acceptance: 18 September 2014
Last Modified: 01 Nov 2022 09:50
URI: https://orca.cardiff.ac.uk/id/eprint/89372

Citation Data

Cited 5 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item