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Improving Usage of the Korea Meteorological Administration's Digital Forecasts in Agriculture: Correction Method for Daytime Hourly Air Temperature over Complex Terrain
작성일
2022-04-04
조회수
26


TitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitle 중규모 기상모델(WRF-ARW)을 활용한 서울시 옥상노화와 쿨루프의 기온저감 효과 분석Development of a micro scale CFD model to predict wind environment on mountainous terrain.A Statistical Parameter Correction Technique for WRF Medium-Range Prediction of Near-Surface Temperature and Wind Speed Using Generalized Linear ModelLandslide Susceptibility Assessment Considering the Saturation Depth Ratio by Rainfall ChangeEstimation of freeze damage risk according to developmental stage of fruit flower buds in spring
봄철 과수 꽃눈 발육 수준에 따른 저온해 위험도 산정
Establishment of Geospatial Schemes Based on Topo-Climatology for Farm-Specific Agrometeorological Information.
농장맞춤형 농업기상정보 생산을 위한 소기후 모형 구축
Estimating the Monthly Precipitation Distribution of North Korea Using the PRISM Model and Enhanced Detailed Terrain Information.
PRISM과 개선된 상세 지형정보를 이용한 월별 북한지역 강수량 분포 추정
Improving Usage of the Korea Meteorological Administration's Digital Forecasts in Agriculture: Correction Method for Daytime Hourly Air Temperature over Complex Terrain.
기상청 동네예보의 영농활용도 증진을 위한 방안: 복잡지형의 낮 기온 상세화 기법
AuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthors 곽재환, 김만일, 이승재J Park, HS Kim, SJ Lee, T Ha박주한, 이승재, 강민석, 김준, 양일규, 김병국, 유근기김희주, 오규식, 이승재T Ha, I Lee, K Kwon, SJ LeeJ Jeong, SJ LeeJH Kwak, MI Kim, SJ LeeJin-Hee Kim, Dae-jun Kim, Soo-Ock Kim, Eun-Jeong Yun, Okjung Ju, Jong Sun Park, Yong Soon ShinDae-jun Kim, Soo-Ock Kim, Jin-Hee Kim, Eun-Jeong YunDae-jun Kim, Jin-Hee KimEun-Jeong Yun, Soo-Ock Kim
PublicationPublicationPublicationPublication 20182018201820182018201820182019201920192019
JournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournalJournal Atmosphere 9The Journal of Engineering Geology 28Korean Journal of Agricultural and Forest MeteorologyKorean Journal of Agricultural and Forest MeteorologyKorean Journal of Agricultural and Forest Meteorology Korean Journal of Agricultural and Forest Meteorology
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머신러닝 기법의 산림 총일차생산성 예측 모델 비교.
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Title 머신러닝 기법의 산림 총일차생산성 예측 모델 비교. AuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthorsAuthors 이보라, 장근창, 김은숙..
이전글
Estimating the Monthly Precipitation Distribution of North Korea Using the PRISM Model and Enhanced Detailed Terrain Information
/ 관리자
TitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitleTitle 중규모 기상모델(WRF-ARW)을 활용한 서울시 옥상노화와 쿨루프의 기온저감 효과 분석Development of a micro scale CFD model to predict wind environment on moun..