{"title":"Assessment of seasonal forecasting potential for springtime Asian dust in South Korea using the KMA global seasonal forecasting system","authors":"Misun Kang, Woojeong Lee","doi":"10.1016/j.apr.2024.102262","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims to assess the potential of seasonal forecasting for springtime Asian dust days in South Korea using the Korea Meteorological Administration's Global Seasonal Forecasting System version 6 (KMA GloSea6). The system demonstrated similar predictive performance for springtime Asian dust days compared to GloSea5-ADAM, which incorporates the Asian Dust and Aerosol Model's emission algorithm into GloSea5. While KMA GloSea6 exhibited strong wind, cold, and moist biases in the Asian dust source region during the spring of the hindcast period, similar to GloSea5-ADAM, it showed an improved spatial distribution of ACC. The anomaly correlation coefficient for the annual variability of Asian dust occurrence frequency anomalies in the dust source region was also similar, with values of 0.41 for KMA GloSea6 and 0.43 for GloSea5-ADAM. Furthermore, in evaluating the seasonal forecasting of springtime Asian dust days using hindcast datasets, KMA GloSea6 accurately predicted 12 out of 24 instances, resulting in a forecast accuracy of 0.5, consistent with GloSea5-ADAM. When applying the criteria to spring 2022 and 2023 forecast data not used in the derivation, the predicted Asian dust days of 6.14 days in spring 2022 led to a “Near normal” prediction, differing from the observed “Below normal.” However, the spatial distribution showed “Below normal” conditions, aligning with observations in some areas. In spring 2023, the predicted 9.78 Asian dust days led to an “Above normal” prediction, consistent with observed conditions. These findings will contribute to advancing seasonal Asian dust forecasting in South Korea.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 11","pages":"Article 102262"},"PeriodicalIF":3.9000,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1309104224002277/pdfft?md5=009fa1a1bb33fc2e2fd038310bddac05&pid=1-s2.0-S1309104224002277-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002277","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to assess the potential of seasonal forecasting for springtime Asian dust days in South Korea using the Korea Meteorological Administration's Global Seasonal Forecasting System version 6 (KMA GloSea6). The system demonstrated similar predictive performance for springtime Asian dust days compared to GloSea5-ADAM, which incorporates the Asian Dust and Aerosol Model's emission algorithm into GloSea5. While KMA GloSea6 exhibited strong wind, cold, and moist biases in the Asian dust source region during the spring of the hindcast period, similar to GloSea5-ADAM, it showed an improved spatial distribution of ACC. The anomaly correlation coefficient for the annual variability of Asian dust occurrence frequency anomalies in the dust source region was also similar, with values of 0.41 for KMA GloSea6 and 0.43 for GloSea5-ADAM. Furthermore, in evaluating the seasonal forecasting of springtime Asian dust days using hindcast datasets, KMA GloSea6 accurately predicted 12 out of 24 instances, resulting in a forecast accuracy of 0.5, consistent with GloSea5-ADAM. When applying the criteria to spring 2022 and 2023 forecast data not used in the derivation, the predicted Asian dust days of 6.14 days in spring 2022 led to a “Near normal” prediction, differing from the observed “Below normal.” However, the spatial distribution showed “Below normal” conditions, aligning with observations in some areas. In spring 2023, the predicted 9.78 Asian dust days led to an “Above normal” prediction, consistent with observed conditions. These findings will contribute to advancing seasonal Asian dust forecasting in South Korea.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.