기업조회

본문 바로가기 주메뉴 바로가기

논문 기본정보

황사장기예측자료를 이용한 봄철 황사 발생 예측 특성 분석

논문 개요

기관명, 저널명, ISSN, ISBN 으로 구성된 논문 개요 표입니다.
기관명 NDSL
저널명 대기 = Atmosphere
ISSN 1598-3560,2288-3266
ISBN

논문저자 및 소속기관 정보

저자, 소속기관, 출판인, 간행물 번호, 발행연도, 초록, 원문UR, 첨부파일 순으로 구성된 논문저자 및 소속기관 정보표입니다
저자(한글) 강미선,이우정,장필훈,김미경,부경온,국립기상과학원 예보연구부,국립기상과학원 예보연구부,국립기상과학원 예보연구부,국립기상과학원 예보연구부,국립기상과학원 기후연구부
저자(영문)
소속기관
소속기관(영문)
출판인
간행물 번호
발행연도 2022-01-01
초록 This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.
원문URL http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=JAKO202218753898954
첨부파일

추가정보

과학기술표준분류, ICT 기술분류,DDC 분류,주제어 (키워드) 순으로 구성된 추가정보표입니다
과학기술표준분류
ICT 기술분류
DDC 분류
주제어 (키워드) Asian dust,Subseasonal prediction,GloSea5-ADAM,Hindcast