Asia-Pacific Journal of Atmospheric Sciences最新文献_第8页

Exceptionally persistent Eurasian cold events and their stratospheric link 异常持续的欧亚大陆冷事件及其平流层联系

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2023-01-13 DOI: 10.1007/s13143-022-00308-y

Kathrin Finke, Abdel Hannachi, Toshihiko Hirooka

{"title":"Exceptionally persistent Eurasian cold events and their stratospheric link","authors":"Kathrin Finke, Abdel Hannachi, Toshihiko Hirooka","doi":"10.1007/s13143-022-00308-y","DOIUrl":"10.1007/s13143-022-00308-y","url":null,"abstract":"<div><p>Persistent boreal winter cold spells (PCEs) can heavily strain the economy and significantly impact everyday life. While sudden stratospheric warmings are considered a precursor for Eurasian (EUR) cold events, these temperature extremes may occur during the full range of stratospheric variability. We investigate PCEs relative to the prevailing stratospheric polar vortex regime before their onset, with a particular focus on extremely weak (SSW) and strong (SPV) stratospheric winds by performing (lagged) composite analysis based on ERA5 reanalysis. On average, SPV PCEs that are concentrated over central EUR, are colder, shorter and set in more abruptly compared to SSW PCEs. A quasi-stationary, mid-tropospheric anticyclone over the Arctic Ocean that blocks warm air advection toward EUR is connected to the canonical downward progression of the negative North Atlantic Oscillation for SSW PCEs. In contrast, during SPV PCEs, the anticyclone is part of a Rossby wave having an origin co-located with negative wave activity flux anomalies over and being influenced by stratospheric wave reflection toward the North Atlantic. Its slow east-ward propagation is likely related to Arctic surface warming and unusually weak zonal winds over EUR.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 1","pages":"95 - 111"},"PeriodicalIF":2.3,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00308-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46705515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Development of PM2.5 Forecasting System in South Korea Using Chemical Transport Modeling and Machine Learning 利用化学输运模型和机器学习开发韩国PM2.5预报系统

IF 2.2 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2023-01-13 DOI: 10.1007/s13143-023-00314-8

Youn-Seo Koo, Hee-Yong Kwon, Hyosik Bae, Hui-Young Yun, Dae-Ryun Choi, SukHyun Yu, Kyung-Hui Wang, Ji-Seok Koo, Jae-Bum Lee, Min-Hyeok Choi, Jeong-Beom Lee

{"title":"A Development of PM2.5 Forecasting System in South Korea Using Chemical Transport Modeling and Machine Learning","authors":"Youn-Seo Koo, Hee-Yong Kwon, Hyosik Bae, Hui-Young Yun, Dae-Ryun Choi, SukHyun Yu, Kyung-Hui Wang, Ji-Seok Koo, Jae-Bum Lee, Min-Hyeok Choi, Jeong-Beom Lee","doi":"10.1007/s13143-023-00314-8","DOIUrl":"10.1007/s13143-023-00314-8","url":null,"abstract":"<div><p>Ambient exposure to PM2.5 can adversely affect public health, and forecasting PM2.5 is essential for implementing protection measures in advance. Current PM2.5 forecasting systems are primarily based on the chemical transport model of Community Multiscale Air Quality (CMAQ) modeling systems and the Weather Research and Forecasting (WRF) model. However, the forecasting accuracies of these models are substantially constrained by uncertainties in the input data of anthropogenic emissions and meteorological fields, as well as inherent limitations in the models. The PM2.5 forecasting system developed in this study aimed at overcoming the limitations of CMAQ predictions by utilizing advanced machine learning algorithms. The proposed system was developed using forecast data from CMAQ and WRF, as well as observed PM2.5 concentrations and meteorological variables at monitoring stations in China and South Korea. It was then applied to national PM2.5 forecasting in South Korea. This study focused on developing secondary input data and machine learning models that can reflect the long-range transport in Northeast Asia. The proposed system can forecast 6-h average PM2.5 concentrations up to two days in advance at 19 forecast regions in South Korea. To evaluate the performance of the proposed models, a real-time machine learning-based forecasting system was applied to 19 forecasting regions from January 2020 to April 2021. Herein, the four machine learning algorithms applied, including deep neural network, recurrent neural network, convolutional neural network, and Ensemble, could reduce the over-prediction of the CMAQ forecast by decreasing the normal mean bias and improving the index of agreement. The reduced false alarm rates and high prediction accuracy confirm the feasibility of these models for practical applications.\u0000</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 5","pages":"577 - 595"},"PeriodicalIF":2.2,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47748761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improvement of Korea Meteorological Administration Solar Energy Resources Map Using Fine-Scale Terrain Data 利用精细地形数据改进韩国气象局太阳能资源图

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2023-01-10 DOI: 10.1007/s13143-022-00312-2

Jinah Yun, Jinwon Kim, Minwoo Choi, Hee-Wook Choi, Yeon-Hee Kim, Sang-Sam Lee

{"title":"Improvement of Korea Meteorological Administration Solar Energy Resources Map Using Fine-Scale Terrain Data","authors":"Jinah Yun, Jinwon Kim, Minwoo Choi, Hee-Wook Choi, Yeon-Hee Kim, Sang-Sam Lee","doi":"10.1007/s13143-022-00312-2","DOIUrl":"10.1007/s13143-022-00312-2","url":null,"abstract":"<div><p>Real-time solar energy resources mapping is crucial for the development and management of solar power facilities. This study analyzes the effects of the digital elevation model (DEM) resolution on the accuracy of the surface insolation (insolation hereafter) calculated by the Korea Meteorological Administration solar energy mapping system, KMAP-Solar, using two DEMs of different resolutions, 1.5 km and 100 m. It is found that KMAP-Solar yields smaller land-mean insolation with the fine-scale DEM than the coarse-scale DEM. The fine-scale DEM reduces biases by as much as 32 Wm<sup>− 2</sup> for all observation sites, especially those in complex terrain and that the insolation error reduction is correlated with the difference in sky view factor (SVF) between the coarse- and fine-scale DEM. Both the coarse- and fine-scale DEMs generate the insolation-elevation and insolation-SVF relationship which is characterized by positive (negative) correlation between the insolation and the terrain altitude (SVF). However, the coarse-scale DEM substantially underestimates these relationships compared to the fine-scale DEM, mainly because the coarse-scale DEM underrepresents large terrain slopes and/or small SVFs, most seriously in high-altitude regions. The fine-scale DEM generates a more realistic insolation distribution than the coarse-scale DEM by incorporating a wider range of key terrain parameters involved in determining insolation. Improvements of insolation calculations in KMAP-Solar using a fine-scale DEM, especially in the areas of complex terrain, is of a practical value for Korea because the operational solar resources map from KMAP-Solar supports solar energy research, solar power plant installations, and real-time prediction and management of solar power within the power grid.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 3","pages":"297 - 309"},"PeriodicalIF":2.3,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00312-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48834080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning Method 使用WRF模式和机器学习方法改进的北太平洋西部热带气旋路径模拟

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2023-01-04 DOI: 10.1007/s13143-022-00313-1

Kyoungmin Kim, Donghyuck Yoon, Dong-Hyun Cha, Jungho Im

{"title":"Improved Tropical Cyclone Track Simulation over the Western North Pacific using the WRF Model and a Machine Learning Method","authors":"Kyoungmin Kim, Donghyuck Yoon, Dong-Hyun Cha, Jungho Im","doi":"10.1007/s13143-022-00313-1","DOIUrl":"10.1007/s13143-022-00313-1","url":null,"abstract":"<div><p>Accurate tropical cyclone (TC) track simulations are required to mitigate property damage and casualties. Previous studies have generally simulated TC tracks using numerical models, which tend to experience systematic errors due to model imperfections, although the model accuracy has improved over time. Recently, machine-learning methods have been applied to correct such errors. In this study, we used an artificial neural network (ANN) to correct TC tracks hindcasted by the Weather Research and Forecasting (WRF) model from 2006 to 2018 over the western North Pacific. TC categories that are stronger than tropical depressions (i.e., tropical storms, severe tropical storms, and typhoons) were selected from June to November, and a bias correction was made to target TC positions at 72 h. The WRF-simulated tracks were used as input variables for training and testing the ANN using the best track and reanalysis data. To obtain a reliable corrected result, the number of neurons in the ANN structure was optimized for TCs during 2006–2015, and the optimized ANN was verified for TCs from 2016–2018. Because the performance of the numerical model differed according to the TC track, the ANN was assessed by cluster analysis. The results of the ANN were analyzed using k-means clustering to classify TCs into eight clusters. Overall, ANN with post-processing improved the WRF performance by 4.34%. The WRF error was corrected by 8.81% for clusters where the ANN was most applicable.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 3","pages":"283 - 296"},"PeriodicalIF":2.3,"publicationDate":"2023-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00313-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42726579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Rain Drop Size Distribution to Elucidate the Precipitation Process using a Cloud Microphysics Conceptual Model and In Situ Measurement 利用云微物理概念模型和现场测量分析降水过程中的雨滴大小分布

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-20 DOI: 10.1007/s13143-022-00299-w

Joo Wan Cha, Hae Jung Koo, Bu-Yo Kim, Belorid Miloslav, Hyun Jun Hwang, Min Hoo Kim, Ki-Ho Chang, Yong Hee Lee

{"title":"Analysis of Rain Drop Size Distribution to Elucidate the Precipitation Process using a Cloud Microphysics Conceptual Model and In Situ Measurement","authors":"Joo Wan Cha, Hae Jung Koo, Bu-Yo Kim, Belorid Miloslav, Hyun Jun Hwang, Min Hoo Kim, Ki-Ho Chang, Yong Hee Lee","doi":"10.1007/s13143-022-00299-w","DOIUrl":"10.1007/s13143-022-00299-w","url":null,"abstract":"<div><p>\u0000Raindrop size distribution (DSD) is an important parameter in rainfall research and can be used for quantitative precipitation estimation (QPE) in meteorology and hydrology. DSD also improves the understanding of the uncertainty of cloud microphysical processes (CMPs) such as ice-based and warm rain growth during climate change. Changes in CMPs impact the generation of precipitation. However, the estimation of CMPs based on in situ observation is difficult because of the complexity of microphysics processes, and most previous studies on the CMP involved approximations to predict the types of microphysical processes affecting precipitation generation based on in situ observations performed in real-time. Therefore, we developed a simple method for understanding the CMPs of precipitation generation using a conceptual model of CMPs and in situ observation DSD data. We employed previously observed DSD parameters and a CMP conceptual model of the DSD observation-based microphysical process. As case studies, we applied DSD observation data obtained in Korea and East Asia to estimate the CMPs. For example, the major CMP of megacities was vapor deposition in Beijing (< 1 mm h<sup>−1</sup>) and Seoul (< 5 mm h<sup>−1</sup>), as the strong updraft of the urban heat island effect in megacities results in increased liquid water content, leading to the formation of large number of supersaturated clouds at higher altitudes.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 2","pages":"257 - 269"},"PeriodicalIF":2.3,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00299-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41708595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges in Attributing the 2022 Australian Rain Bomb to Climate Change 将2022年澳大利亚雨弹归因于气候变化的挑战

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-20 DOI: 10.1007/s13143-022-00305-1

Camille Cadiou, Robin Noyelle, Nemo Malhomme, Davide Faranda

{"title":"Challenges in Attributing the 2022 Australian Rain Bomb to Climate Change","authors":"Camille Cadiou, Robin Noyelle, Nemo Malhomme, Davide Faranda","doi":"10.1007/s13143-022-00305-1","DOIUrl":"10.1007/s13143-022-00305-1","url":null,"abstract":"<div><p>In February and March 2022, the eastern coast of Australia recorded an unprecedented amount of precipitation with extended floods and damages to properties amounting at least to AUD 2.3 billions. In this paper we use both reanalysis and observations to perform a statistical and dynamical attribution of this precipitation event to climate change. We define 1948-1977 as the counterfactual period and 1990-2019 as the factual one. The statistical attribution is based on fitting the generalized extreme value distribution for 3-days averaged precipitation annual maxima for the two periods, while the dynamical attribution aims at looking at the recurrence properties of sea-level pressure and geopotential height patterns in both periods. We find that the dynamics of the event consists in an unprecedented combination of several factors: a tropical atmospheric river, the presence of the Coral low pressure system and a blocking anticyclone offshore Eastern Australia. Our main finding is that no clear attribution statements can be made, both because of the unprecedented nature of this event, the lack of long high quality available data and the dependence of the results on the La Nina phase of El Nino Southern Oscillation.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 1","pages":"83 - 94"},"PeriodicalIF":2.3,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47771217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Evaluation of Deep-Learning-Based Very Short-Term Rainfall Forecasts in South Korea 基于深度学习的韩国极短期降雨预报评估

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-08 DOI: 10.1007/s13143-022-00310-4

Seok-Geun Oh, Chanil Park, Seok-Woo Son, Jihoon Ko, Kijung Shin, Sunyoung Kim, Junsang Park

{"title":"Evaluation of Deep-Learning-Based Very Short-Term Rainfall Forecasts in South Korea","authors":"Seok-Geun Oh, Chanil Park, Seok-Woo Son, Jihoon Ko, Kijung Shin, Sunyoung Kim, Junsang Park","doi":"10.1007/s13143-022-00310-4","DOIUrl":"10.1007/s13143-022-00310-4","url":null,"abstract":"<div><p>This study evaluates the performance of a deep learning model, Deep-learning-based Rain Nowcasting and Estimation (DEEPRANE), for very short-term (1–6 h) rainfall forecasts in South Korea. Rainfall forecasts and in-situ observations from June–September 2020, when record-breaking summer rainfall was observed in South Korea, are particularly considered. It is found that DEEPRANE adequately predicts moderate rainfall events (MREs; ≥ 1 mm h<sup>−1</sup>) and strong rainfall events (SREs; ≥ 10 mm h<sup>−1</sup>) with critical success indices of 0.6 and 0.4 at the 1-h lead time, respectively. The probability of detection scores of MRE forecasting is higher than the false alarm rates at all lead times, suggesting that DEEPRANE MRE forecast can be useful even at a long lead time. However, for SRE forecasting, the probability of detection scores becomes smaller than the false alarm rates at a lead time of 2 h. Localized heavy rainfall events (LHREs, ≥ 30 mm h<sup>−1</sup>) are also reasonably well predicted only at a lead time of 2 h. Irrespective of their patterns, the forecast scores systematically decrease with lead time. This result indicates that DEEPRANE SRE forecast is useful only for nowcasting. DEEPRANE generally shows better performance in the early morning hours when rainfall events are more frequent than in other hours. When considering synoptic conditions, better performance is found when rainfall events are organized by monsoon rainband rather than caused by extratropical or tropical cyclones. These results suggest that DEEPRANE is especially useful for nowcasting early-morning rainfall events which are embedded in the monsoon rainband.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 2","pages":"239 - 255"},"PeriodicalIF":2.3,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49542992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Comparative Assessment of Changes in Heat-Related Mortality Risk Under the RCP2.6 and RCP8.5 Scenarios Based on the CORDEX-CORE Ensembles 基于CORDEX-CORE集合的RCP2.6和RCP8.5情景下热相关死亡风险变化的比较评估

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-05 DOI: 10.1007/s13143-022-00304-2

Yuwen Fan, Eun-Soon Im

{"title":"A Comparative Assessment of Changes in Heat-Related Mortality Risk Under the RCP2.6 and RCP8.5 Scenarios Based on the CORDEX-CORE Ensembles","authors":"Yuwen Fan, Eun-Soon Im","doi":"10.1007/s13143-022-00304-2","DOIUrl":"10.1007/s13143-022-00304-2","url":null,"abstract":"<div><p>This study assesses the future heat-related mortality risk under varying levels of warming specified by the RCP2.6 and RCP8.5 scenarios using dynamically downscaled ensemble projections across six different domains. The excess mortality risk due to heat is estimated by the empirical relationship between daily maximum temperature (Tmax) and mortality. The changes in heat-related mortality based on three empirical formulas derived from different countries’ data are compared to examine the sensitivity of change patterns to the empirical formula. The ensemble projections reveal a drastic increase in heat-related mortality risk under the RCP8.5 scenario. However, a significant reduction is expected by limiting greenhouse gas emissions to the RCP2.6 level. While mitigation’s possible benefit is clearly exemplified by comparing the mortality risk derived from RCP2.6 and RCP8.5 projections, this study also provides valuable insights into regional hotspots by comparing the results from multi-domains. Regardless of the emission scenario (RCP2.6 vs. RCP8.5) and empirical formulas that represent the relationship between temperature and mortality, the most vulnerable regions to heat-related mortality risk are identified in the low-latitude near the equator where the adaptation capacities to avoid serious consequences are found to be poor. The higher risk of heat-related mortality in the future is largely attributable to a significant increase in frequency exceeding the optimum temperature where the mortality risk is minimum during the historical period.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 2","pages":"207 - 218"},"PeriodicalIF":2.3,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00304-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45028942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diagnostic Relations for the Intercept Parameter of Exponential Raindrop Size Distribution According to Rain Types Derived from Disdrometer Data and Their Impacts on Precipitation Prediction 指数型雨滴大小分布截距参数的诊断关系及其对降水预报的影响

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-05 DOI: 10.1007/s13143-022-00306-0

Joohyun Lee, Han-Gyul Jin, Jong-Jin Baik

{"title":"Diagnostic Relations for the Intercept Parameter of Exponential Raindrop Size Distribution According to Rain Types Derived from Disdrometer Data and Their Impacts on Precipitation Prediction","authors":"Joohyun Lee, Han-Gyul Jin, Jong-Jin Baik","doi":"10.1007/s13143-022-00306-0","DOIUrl":"10.1007/s13143-022-00306-0","url":null,"abstract":"<div><p>The raindrop size distribution observed from ground-based or airborne disdrometers has been widely used to understand the characteristics of clouds and precipitation. However, its variability needs to be studied further and properly considered for improving precipitation prediction. In this study, using disdrometer data, the diagnostic relations for the intercept parameter of the exponential raindrop size distribution <i>N</i><sub>0</sub> are derived for different rain types and the impacts of the diagnostic relations on precipitation prediction are examined. The disdrometer data observed at four sites in South Korea show spatiotemporal variations of <i>N</i><sub>0</sub>. Three different derivation methods proposed by previous studies are used to derive the diagnostic relations, and the diagnostic relation that best reproduces the observed <i>N</i><sub>0</sub> is selected. The diagnostic relation is implemented into the WRF single-moment 6-class microphysics (WSM6) scheme, and its impacts are investigated through the simulations of summertime precipitation events in South Korea. Compared to the simulation using the original WSM6 scheme (WSM6-O) where a constant <i>N</i><sub>0</sub> is used, the simulation where <i>N</i><sub>0</sub> is diagnosed by the diagnostic relation using the rainwater content at the lowest level (WSM6-L) yields better precipitation prediction. The WSM6-L simulation represents the variability of <i>N</i><sub>0</sub>. Also, the WSM6-L simulation predicts <i>N</i><sub>0</sub> that is on average smaller than the prescribed value in the WSM6-O simulation, agreeing with the observation to some extent. The smaller <i>N</i><sub>0</sub> in the WSM6-L simulation decreases the rainwater production by the accretion of cloud water and the melting of ice hydrometeors, decreasing the rainwater mixing ratio.</p></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 2","pages":"219 - 238"},"PeriodicalIF":2.3,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00306-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44369285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sub-Seasonal Experiment (SubX) Model-based Assessment of the Prediction Skill of Recent Multi-Year South Korea Droughts 基于亚季节试验(SubX)模式的韩国近年多年干旱预测能力评估

IF 2.3 4区地球科学

Asia-Pacific Journal of Atmospheric Sciences Pub Date : 2022-12-02 DOI: 10.1007/s13143-022-00307-z

Chang-Kyun Park, Jonghun Kam

{"title":"Sub-Seasonal Experiment (SubX) Model-based Assessment of the Prediction Skill of Recent Multi-Year South Korea Droughts","authors":"Chang-Kyun Park, Jonghun Kam","doi":"10.1007/s13143-022-00307-z","DOIUrl":"10.1007/s13143-022-00307-z","url":null,"abstract":"<div><h2>Abstract\u0000</h2><div><p>Reliable sub-seasonal forecast of precipitation is essential to manage the risk of multi-year droughts in a timely manner. However, comprehensive assessments of sub-seasonal prediction skill of precipitation remain limited, particularly during multi-year droughts. This study used various verification metrics to assess the sub-seasonal prediction skill of hindcasts of five Sub-seasonal Experiment (SubX) models for precipitation during two recent multi-year South Korea droughts (2007 − 10 and 2013 − 16). Results show that the sub-seasonal prediction skill of the SubX models were stage-, event-, and model-dependent over the recent multi-year droughts. According to the Brier skill scores, SubX models show a more skillful in one to four lead weeks during the drought onset and persistence stages, than the recovery stage. While the prediction skill of the SubX models in the first two initial weeks show more skillful prediction during the 2007–10 drought, the impact of the forecast initial time on the prediction skill is relatively weak during the 2013–16 drought. Overall, the EMC-GEFSv12 model with the 11 ensemble members (the largest among the five SubX models) show the most skillful forecasting skill. According to the sensitivity test to the ensemble member size, the EMC-GEFSv12 model had no gain for biweekly precipitation forecast with the nine ensemble members or more. This study highlights the importance of a robust evaluation of the predictive performance of sub-seasonal climate forecasts via multiple verification metrics.</p></div></div>","PeriodicalId":8556,"journal":{"name":"Asia-Pacific Journal of Atmospheric Sciences","volume":"59 1","pages":"69 - 82"},"PeriodicalIF":2.3,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13143-022-00307-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42990204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3