The Korean Meteorological Society 1

Atmosphere - Vol. 30 , No. 2

[ Article ]
Atmosphere - Vol. 30, No. 2, pp.155-167
Abbreviation: Atmos
ISSN: 1598-3560 (Print) 2288-3266 (Online)
Print publication date 30 Jun 2020
Received 18 Mar 2020 Revised 05 Jun 2020 Accepted 05 Jun 2020
DOI: https://doi.org/10.14191/Atmos.2020.30.2.155

전지구 고해상도 수문모델 적용을 위한 격자유량 추정 방법 적용 연구
류영 ; 지희숙 ; 황승언 ; 이조한*
국립기상과학원 현업운영개발부

Application of a Method Estimating Grid Runoff for a Global High-Resolution Hydrodynamic Model
Young Ryu ; Hee-Sook Ji ; Seung-On Hwang ; Johan Lee*
Operational Systems Development Department, National Institute of Meteorological Sciences, Jeju, Korea
Correspondence to : * Johan Lee, Operational Systems Development Department, National Institute of Meteorological Sciences, 33 Seohobuk-ro, Seogwipo-si, Jeju 63568, Korea. Phone: +82-64-780-6721, Fax: +82-64-738-6514 E-mail: johan.j.lee@gmail.com

Funding Information ▼

Abstract

In order to produce more detailed and accurate information of river discharge and freshwater discharge, global high-resolution hydrodynamic model (CaMa-Flood) is applied to an operational land surface model of global seasonal forecast system. In addition, bias correction to grid runoff for the hydrodynamic model is attempted. CaMa-Flood is a river routing model that distributes runoff forcing from a land surface model to oceans or inland seas along continental-scale rivers, which can represent flood stage and river discharge explicitly. The runoff data generated by the land surface model are bias-corrected by using composite runoff data from UNH-GRDC. The impact of bias-correction on the runoff, which is spatially resolved on 0.5o grid, has been evaluated for 1991~2010. It is shown that bias-correction increases runoff by 30% on average over all continents, which is closer to UNH-GRDC. Two experiments with coupled CaMa-Flood are carried out to produce river discharge: one using this bias correction and the other not using. It is found that the experiment adapting bias correction exhibits significant increase of both river discharge over major rivers around the world and continental freshwater discharge into oceans (40% globally), which is closer to GRDC. These preliminary results indicate that the application of CaMa-Flood as well as bias-corrected runoff to the operational global seasonal forecast system is feasible to attain information of surface water cycle from a coupled suite of atmospheric, land surface, and hydrodynamic model.


Keywords: Grid runoff, bias correction, global hydrodynamic model, river discharge, freshwater discharge

1. 서 론

기후변화와 더불어 폭염, 가뭄, 홍수 등 극한 기상의 출현이 빈번해짐에 따라, 지구시스템 내에서 지면 물순환 기작의 이해와 예측의 중요성은 점점 커지고 있다(Oki et al., 2004). 물은 태양열에 의해 증발되고 공기 중에서 응결 후 물방울이 되어 다시 육지와 해양으로 떨어진다. 이와 같은 물순환을 사실적으로 구현하는 것은 기후예측에 있어서나 지구시스템에서의 다른 기후 영향인자와의 상호작용을 이해하는데 있어 매우 중요하다(Chahine, 1992; Trenberth et al., 2007). 지면에서 물의 이동은 증발산, 토양, 격자유출 및 하천유출 등의 과정 및 이들 간 상호작용으로 발생되며, 이러한 물순환 과정을 이해하고자 수치적 근사 및 모델을 이용한 다양한 연구가 수행되어왔다(Vörösmarty et al., 1989; Dirmeyer and hukla, 1993; Van den Hoof et al., 2013; Harding et al., 2014).

육지에서 발생되는 총 강수의 60%는 증발에 의해 다시 대기로 돌아가고, 나머지는 강이나 내륙의 호수 등으로 모여 해양으로 흘러간다(