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4 pages, 167 KiB

Open AccessEditorial

Meteorological Extremes in Korea: Prediction, Assessment, and Impact

by Okjeong Lee and Sangdan Kim

Atmosphere 2021, 12(6), 782; https://doi.org/10.3390/atmos12060782 - 18 Jun 2021

Viewed by 1383

Abstract

The extreme climates that occur around the world every year have a profound impact on the quality of life for mankind since they can cause natural disasters beyond our control, such as droughts and floods [...] Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

Research

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16 pages, 5050 KiB

Open AccessArticle

Uncertainty of Rate of Change in Korean Future Rainfall Extremes Using Non-Stationary GEV Model

by Jiyu Seo, Jeongeun Won, Jeonghyeon Choi, Jungmin Lee, Suhyung Jang, Okjeong Lee and Sangdan Kim

Atmosphere 2021, 12(2), 227; https://doi.org/10.3390/atmos12020227 - 07 Feb 2021

Cited by 6 | Viewed by 1902

Abstract

Interest in future rainfall extremes is increasing, but the lack of consistency in the future rainfall extremes outputs simulated in climate models increases the difficulty of establishing climate change adaptation measures for floods. In this study, a methodology is proposed to investigate future [...] Read more.

Interest in future rainfall extremes is increasing, but the lack of consistency in the future rainfall extremes outputs simulated in climate models increases the difficulty of establishing climate change adaptation measures for floods. In this study, a methodology is proposed to investigate future rainfall extremes using future surface air temperature (SAT) or dew point temperature (DPT). The non-stationarity of rainfall extremes is reflected through non-stationary frequency analysis using SAT or DPT as a co-variate. Among the parameters of generalized extreme value (GEV) distribution, the scale parameter is applied as a function of co-variate. Future daily rainfall extremes are projected from 16 future SAT and DPT ensembles obtained from two global climate models, four regional climate models, and two representative concentration pathway climate change scenarios. Compared with using only future rainfall data, it turns out that the proposed method using future temperature data can reduce the uncertainty of future rainfall extremes outputs if the value of the reference co-variate is properly set. In addition, the confidence interval of the rate of change of future rainfall extremes is quantified using the posterior distribution of the parameters of the GEV distribution sampled using Bayesian inference. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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14 pages, 3752 KiB

Open AccessArticle

Future Changes in the Global and Regional Sea Level Rise and Sea Surface Temperature Based on CMIP6 Models

by Hyun Min Sung, Jisun Kim, Jae-Hee Lee, Sungbo Shim, Kyung-On Boo, Jong-Chul Ha and Yeon-Hee Kim

Atmosphere 2021, 12(1), 90; https://doi.org/10.3390/atmos12010090 - 08 Jan 2021

Cited by 19 | Viewed by 4614

Abstract

Estimating future sea level rise (SLR) and sea surface temperature (SST) is essential to implement mitigation and adaptation options within a sustainable development framework. This study estimates regional SLR and SST changes around the Korean peninsula. Two Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) [...] Read more.

Estimating future sea level rise (SLR) and sea surface temperature (SST) is essential to implement mitigation and adaptation options within a sustainable development framework. This study estimates regional SLR and SST changes around the Korean peninsula. Two Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) scenarios and nine Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations are used to estimate the changes in SLR and SST. At the end of the 21st century, global SLR is expected to be 0.28 m (0.17–0.38 m) and 0.65 m (0.52–0.78 m) for SSP 1–2.6 and SSP5-8.5, respectively. Regional change around the Korean peninsula (0.25 m (0.15–0.35 m; SSP1-2.6) and 0.63 m (0.50–0.76 m; SSP5-8.5)) is similar with global SLR. The discrepancy between global and regional changes is distinct in SST warming rather than SLR. For SSP5-8.5, SST around the Korean peninsula projects is to rise from 0.49 °C to 0.59 °C per decade, which is larger than the global SST trend (0.39 °C per decade). Considering this, the difference of regional SST change is related to the local ocean current change, such as the Kuroshio Current. Additionally, ocean thermal expansion and glacier melting are major contributors to SLR, and the contribution rates of glacier melting increase in higher emission scenarios. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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10 pages, 2417 KiB

Open AccessArticle

Reversibility of the Hydrological Response in East Asia from CO₂-Derived Climate Change Based on CMIP6 Simulation

by Min-Ah Sun, Hyun Min Sung, Jisun Kim, Jae-Hee Lee, Sungbo Shim, Kyung-On Boo, Young-Hwa Byun, Charline Marzin and Yeon-Hee Kim

Atmosphere 2021, 12(1), 72; https://doi.org/10.3390/atmos12010072 - 06 Jan 2021

Cited by 12 | Viewed by 2190

Abstract

Understanding the response of the Earth system to CO₂ removal (CDR) is crucial because the possibility of irreversibility exists. Therefore, the Carbon Dioxide Removal Model Inter-comparison Project (CDRMIP) for the protocol experiment in the Coupled Model Inter-comparison Project Phase 6 (CMIP6) has [...] Read more.

Understanding the response of the Earth system to CO₂ removal (CDR) is crucial because the possibility of irreversibility exists. Therefore, the Carbon Dioxide Removal Model Inter-comparison Project (CDRMIP) for the protocol experiment in the Coupled Model Inter-comparison Project Phase 6 (CMIP6) has been developed. Our analysis focuses on the regional response in the hydrological cycle, especially in East Asia (EA). The peak temperature changes in EA (5.9 K) and the Korean peninsula (KO) (6.1 K) are larger than the global mean surface air temperature (GSAT) response. The precipitation changes are approximately 9.4% (EA) and 23.2% (KO) at the phase change time (130–150 years); however, the largest increase is approximately 16.6% (EA) and 36.5% (KO) in the ramp-down period (150–160 years). In addition, the differences are below 5 mm/day and 1 day for the precipitation intensity indices (Rx1day and Rx5day) and frequency indices (R95 and R99), respectively. Furthermore, the monsoon rainband of the ramp-down period moves northward as the earlier onset with high confidence compared to the ramp-up period; however, it does not move north to the KO region. The results suggest that reducing CO₂ moves the rainband southward. However, a detailed interpretation in terms of the mechanism needs to be carried out in further research. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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21 pages, 6531 KiB

Open AccessArticle

Future Changes of Agro-Climate and Heat Extremes over S. Korea at 2 and 3 °C Global Warming Levels with CORDEX-EA Phase 2 Projection

by Sera Jo, Kyo-Moon Shim, Jina Hur, Yong-Seok Kim and Joong-Bae Ahn

Atmosphere 2020, 11(12), 1336; https://doi.org/10.3390/atmos11121336 - 09 Dec 2020

Cited by 5 | Viewed by 2143

Abstract

The changes of agro-climate and heat extremes, and their impact on rice cultivation are assessed over South Korea in context of 2 and 3 °C global warming levels (GWL) compared to pre-industrial levels, with ensemble regional climate model projection produced under the Coordinated [...] Read more.

The changes of agro-climate and heat extremes, and their impact on rice cultivation are assessed over South Korea in context of 2 and 3 °C global warming levels (GWL) compared to pre-industrial levels, with ensemble regional climate model projection produced under the Coordinated Regional Climate Downscaling Experiment–East Asia (CORDEX-EA) phase 2 protocols. It is found that the mean temperature increase under global warming has not only positive effects such as the extension of vegetable and crop periods and the widening of the cultivatable regions but also negative effects due to the shortening of the reproductive growth period. On the other hand, extreme heat changes in the future clearly show a negative effect on rice cultivation via the increase of hot days during heat-sensitive stages (27.16% under 2 °C GWL, 54.59% under 3 °C GWL) among rice phenology which determines the rice yield in tandem with rice flowering, ripening, and sterility problems. The major type of heat extreme is dominated by nationwide warm anomalies covering entire S. Korea, and the proportion of this type is projected to increase from 35.8% to 49.5% (57.4%) under 2 °C (3 °C) GWL in association with the thermal expansion of atmosphere which links to the favorable environment for occurring barotropic anti-cyclonic system. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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19 pages, 3820 KiB

Open AccessEditor’s ChoiceArticle

Representation of the 2016 Korean Heatwave in the Unified Model Global NWP Forecasts: The Impact of Remotely Forced Model Errors and Atmosphere-Ocean Coupling

by Eun-Jung Kim, Charline Marzin, Sean F. Milton, Kyung-On Boo, Yoonjae Kim, Jiyoung Oh and Hyun-Suk Kang

Atmosphere 2020, 11(12), 1275; https://doi.org/10.3390/atmos11121275 - 25 Nov 2020

Cited by 3 | Viewed by 1957

Abstract

This study investigates the effects of atmosphere-ocean coupling for medium-range forecasts by using coupled numerical weather prediction (NWP) experiments based on the unified model (UM) on a case study of the 2016 heatwave over the Korean Peninsula. Atmospheric nudging experiments were carried out [...] Read more.

This study investigates the effects of atmosphere-ocean coupling for medium-range forecasts by using coupled numerical weather prediction (NWP) experiments based on the unified model (UM) on a case study of the 2016 heatwave over the Korean Peninsula. Atmospheric nudging experiments were carried out to determine the key regions which may have large impacts on the forecasts of the heat wave. The results of the nudging experiments suggest that key forcing from the Mongolia region gives the largest impact to this case by causing a transport of warm air from the northwest part of Korea. Moreover, the Pacific region shows an important role in the global circulation in nudging experiments. Results from the atmosphere-ocean coupled model show no clear benefit for the extreme heat wave temperatures in this case. In addition, more model development seems to be needed to improve the representation of sea surface temperature (SST) in some key areas. Nevertheless, it is confirmed that the atmosphere-ocean coupled simulation produces a better representation of aspects of the large-scale flow such as the blocking high over the Kamchatka Peninsula, the high pressure system in the northwest Pacific and Hadley circulation. The results presented in this study show that atmosphere-ocean coupling can be an important way to improve the deterministic model forecasts as the lead time increases beyond a few days. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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13 pages, 2295 KiB

Open AccessArticle

Modeling Maximum Tsunami Heights Using Bayesian Neural Networks

by Min-Jong Song and Yong-Sik Cho

Atmosphere 2020, 11(11), 1266; https://doi.org/10.3390/atmos11111266 - 23 Nov 2020

Cited by 10 | Viewed by 2563

Abstract

Tsunamis are distinguished from ordinary waves and currents owing to their characteristic longer wavelengths. Although the occurrence frequency of tsunamis is low, it can contribute to the loss of a large number of human lives as well as property damage. To date, tsunami [...] Read more.

Tsunamis are distinguished from ordinary waves and currents owing to their characteristic longer wavelengths. Although the occurrence frequency of tsunamis is low, it can contribute to the loss of a large number of human lives as well as property damage. To date, tsunami research has concentrated on developing numerical models to predict tsunami heights and run-up heights with improved accuracy because hydraulic experiments are associated with high costs for laboratory installation and maintenance. Recently, artificial intelligence has been developed and has revealed outstanding performance in science and engineering fields. In this study, we estimated the maximum tsunami heights for virtual tsunamis. Tsunami numerical simulation was performed to obtain tsunami height profiles for historical tsunamis and virtual tsunamis. Subsequently, Bayesian neural networks were employed to predict maximum tsunami heights for virtual tsunamis. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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15 pages, 20857 KiB

Open AccessArticle

Assessment of Vulnerability to Drought Disaster in Agricultural Reservoirs in South Korea

by Young-Sik Mun, Won-Ho Nam, Min-Gi Jeon, Na-Kyoung Bang and Taegon Kim

Atmosphere 2020, 11(11), 1244; https://doi.org/10.3390/atmos11111244 - 18 Nov 2020

Cited by 13 | Viewed by 2978

Abstract

Drought is a natural disaster affecting agriculture worldwide. Drought mitigation and proactive response require a comprehensive vulnerability mapping approach considering various factors. This study investigates the vulnerability to agricultural drought in South Korea based on exposure, sensitivity, and adaptability. The evaluation of agricultural [...] Read more.

Drought is a natural disaster affecting agriculture worldwide. Drought mitigation and proactive response require a comprehensive vulnerability mapping approach considering various factors. This study investigates the vulnerability to agricultural drought in South Korea based on exposure, sensitivity, and adaptability. The evaluation of agricultural drought factors yielded 14 items, which are categorized into meteorological, agricultural reservoir, social, and adaptability factors. Each item is assigned a weight using the analytical hierarchy process (AHP). We analyzed vulnerability to drought disaster in agricultural reservoirs, and generated vulnerability maps by applying the vulnerability framework for climate change. The generated map was divided into four categories based on drought vulnerability: A (Very high), B (High), C (Moderate), and D (Low). The weights for the meteorological (0.498), agricultural reservoir (0.286), social (0.166), and adaptability (0.05) factors were obtained using AHP. The rating frequencies were 41.91%, 19.76%, 9.58%, and 5.39% for A, B, C, and D, respectively. The western region is extremely vulnerable to meteorological and agricultural reservoir factors, whereas the eastern region is more vulnerable to adaptability. The results of this study visually represent agricultural drought and can be used for evaluating regional drought vulnerability for assisting preemptive drought responses to identify and support drought-prone areas. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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16 pages, 2761 KiB

Open AccessArticle

An Update on the Status of Mean Sea Level Rise around the Korean Peninsula

by Phil J. Watson and Hak-Soo Lim

Atmosphere 2020, 11(11), 1153; https://doi.org/10.3390/atmos11111153 - 26 Oct 2020

Cited by 13 | Viewed by 2905

Abstract

The threat of sea level rise to the heavily populated Korean Peninsula, which contains around 15,000 km of coastline bordering open sea margins, has profound and far reaching implications. This study updates and extends previous detailed studies with the addition of a further [...] Read more.

The threat of sea level rise to the heavily populated Korean Peninsula, which contains around 15,000 km of coastline bordering open sea margins, has profound and far reaching implications. This study updates and extends previous detailed studies with the addition of a further 2 years of data to the end of 2019, providing renewed robustness to the identification of emerging threats associated with sea level rise within the warming sea margins around the Korean Peninsula. The study analyzes tide gauge records and satellite altimetry around the Republic of Korea using enhanced time series analysis techniques to detect coastal vertical land motion and current rates of rise in mean sea level to augment planning, design and risk management activities. Despite fluctuations over time at each site, the highest “relative” mean sea level at each of the seven longest tide gauge records occurs in 2019, with weak evidence of an acceleration in the increase in mean sea level around the Republic of Korea. Trends in sea surface height from satellite altimetry across this region note two discreet areas east and west of the Korean Peninsula around 37.5° N (around Ulleungdo Island and in the Gyeonggi Bay region of the Yellow Sea), where rates of rise are well above the global average trend. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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27 pages, 7416 KiB

Open AccessArticle

Effect of Climate Change on Annual Precipitation in Korea Using Data Screening Techniques and Climate Change Scenarios

by Ga-Kyun Lim, Byung-Sik Kim, Byung-Hyun Lee and Se-Jin Jeung

Atmosphere 2020, 11(10), 1027; https://doi.org/10.3390/atmos11101027 - 24 Sep 2020

Cited by 2 | Viewed by 1918

Abstract

Precipitation is essential for understanding hydrological processes and identifying the characteristics that must be considered to protect human lives and property from natural disasters. Hydrological analyses assume that precipitation shows stationarity. However, because of the recent changes in climate, the stationarity of climate [...] Read more.

Precipitation is essential for understanding hydrological processes and identifying the characteristics that must be considered to protect human lives and property from natural disasters. Hydrological analyses assume that precipitation shows stationarity. However, because of the recent changes in climate, the stationarity of climate data has been widely debated, and a need has arisen to analyze its nonstationary nature. In this study, we reviewed a method to analyze the stationarity of annual precipitation data from 37 meteorological stations that have recorded data for more than 45 years. Six stations that showed abnormal precipitation during the previous year were selected to evaluate the normality of future precipitation. The results showed that a significant trend was present in four out of 37 stations with unstable precipitation in 22 stations and persistent precipitation in 4 stations. The stationarity analysis of future annual precipitation using climate change scenarios suggested that no trend would be present in 11 stations and that unstable precipitation would be present in six stations. Persistent precipitation was identified in four stations. A comparison between the historical and predicted precipitation data conducted with the climate change scenarios showed that an increasing number of stations presented nonstationarity. Therefore, both stationarity and nonstationarity should be considered when performing hydrological analyses using annual precipitation data in Korea. Accordingly, prior to conducting any such analyses, the effect of climate change on annual precipitation should also be considered. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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15 pages, 4073 KiB

Open AccessArticle

Application of the Hidden Markov Bayesian Classifier and Propagation Concept for Probabilistic Assessment of Meteorological and Hydrological Droughts in South Korea

by Muhammad Nouman Sattar, Muhammad Jehanzaib, Ji Eun Kim, Hyun-Han Kwon and Tae-Woong Kim

Atmosphere 2020, 11(9), 1000; https://doi.org/10.3390/atmos11091000 - 18 Sep 2020

Cited by 16 | Viewed by 2647

Abstract

Drought is one of the most destructive natural hazards and results in negative effects on the environment, agriculture, economics, and society. A meteorological drought originates from atmospheric components, while a hydrological drought is influenced by properties of the hydrological cycle and generally induced [...] Read more.

Drought is one of the most destructive natural hazards and results in negative effects on the environment, agriculture, economics, and society. A meteorological drought originates from atmospheric components, while a hydrological drought is influenced by properties of the hydrological cycle and generally induced by a continuous meteorological drought. Several studies have attempted to explain the cross dependencies between meteorological and hydrological droughts. However, these previous studies did not consider the propagation of drought classes. Therefore, in this study, to consider the drought propagation concept and to probabilistically assess the meteorological and hydrological drought classes, characterized by the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), respectively, we employed the Markov Bayesian Classifier (MBC) model that combines the procedure of iteration of feature extraction, classification, and application for assessment of drought classes for both SPI and SRI. The classification results were compared using the observed SPI and SRI, as well as with previous findings, which demonstrated that the MBC was able to reasonably determine drought classes. The accuracy of the MBC model in predicting all the classes of meteorological drought varies from 36 to 76% and in predicting all the classes of hydrological drought varies from 33 to 70%. The advantage of the MBC-based classification is that it considers drought propagation, which is very useful for planning, monitoring, and mitigation of hydrological drought in areas having problems related to hydrological data availability. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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15 pages, 22609 KiB

Open AccessArticle

Linking Hydraulic Modeling with a Machine Learning Approach for Extreme Flood Prediction and Response

by Hyun Il Kim and Kun Yeun Han

Atmosphere 2020, 11(9), 987; https://doi.org/10.3390/atmos11090987 - 15 Sep 2020

Cited by 5 | Viewed by 2841

Abstract

An emergency action plan (EAP) for reservoirs and urban areas downstream of dams can alleviate damage caused by extreme flooding. An EAP is a disaster action plan that can designate evacuation paths for vulnerable districts. Generally, calculation of dam-break discharge in accordance with [...] Read more.

An emergency action plan (EAP) for reservoirs and urban areas downstream of dams can alleviate damage caused by extreme flooding. An EAP is a disaster action plan that can designate evacuation paths for vulnerable districts. Generally, calculation of dam-break discharge in accordance with dam inflow conditions, calculation of maximum water surface elevation as per hydraulic channel routing, and flood map generation using topographical data are prepared for the purposes of creating an EAP. However, rainfall and flood patterns exhibited in the context of climate change can be extremely diverse. In order to prepare an efficient flood response, techniques should be considered that are capable of generating flood maps promptly while taking dam inflow conditions into account. Therefore, this study aims to propose methodology that is capable of generating flood maps rapidly for any dam inflow conditions. The proposed methodology was performed by linking a dynamic numerical analysis model (DAMBRK) with a random forest regression technique. The previous standard method of drawing flood maps often requires a significant amount of time depending on accuracy and personnel availability; however, the technique proposed here is capable of generating a flood map within one minute. Through use of this methodology, the time taken to prepare flood maps in large-scale water-disaster situations can be reduced. Moreover, methodology for estimating flood risk via use of flood mapping has been proposed. This study would provide assistance in establishing disaster countermeasures that take various flood scenarios into account by promptly providing flood inundation information to disaster-related agencies. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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13 pages, 2055 KiB

Open AccessArticle

Quantitative Determination Procedures for Regional Extreme Drought Conditions: Application to Historical Drought Events in South Korea

by Chan Wook Lee, Moo Jong Park and Do Guen Yoo

Atmosphere 2020, 11(6), 581; https://doi.org/10.3390/atmos11060581 - 02 Jun 2020

Cited by 7 | Viewed by 2237

Abstract

Recently, the signs of extreme droughts, which were thought of as exceptional and unlikely, are being detected worldwide. It is necessary to prepare countermeasures against extreme droughts; however, current definitions of extreme drought are just used as only one or two indicators to [...] Read more.

Recently, the signs of extreme droughts, which were thought of as exceptional and unlikely, are being detected worldwide. It is necessary to prepare countermeasures against extreme droughts; however, current definitions of extreme drought are just used as only one or two indicators to represent the status or severity of a drought. More representative drought factors, which can show the status and severity that are relevant to extreme drought, need to be considered depending on the characteristics of the drought and comprehensive evaluation of various indices. Therefore, this study attempted to quantitatively define regional extreme droughts using more acceptable factors. The methodology comprises five factors that are indicative of extreme drought. The five factors are (1) duration (days), (2) number of consecutive years (years), (3) water availability, (4) return period, and (5) regional experience. The results were analyzed by applying the procedure to droughts that took place in 2014–2015 in South Korea. The results showed that the applied historical event did not enter the status of extreme drought, which is proposed in this study; however, the proposed methodology is applicable because it uses acceptable and reasonable factors to judge extreme drought, but it can also take into account the past regional experience of extreme drought. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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21 pages, 7466 KiB

Open AccessArticle

Deep Learning-Based Maximum Temperature Forecasting Assisted with Meta-Learning for Hyperparameter Optimization

by Trang Thi Kieu Tran, Taesam Lee, Ju-Young Shin, Jong-Suk Kim and Mohamad Kamruzzaman

Atmosphere 2020, 11(5), 487; https://doi.org/10.3390/atmos11050487 - 10 May 2020

Cited by 46 | Viewed by 5548

Abstract

Time series forecasting of meteorological variables such as daily temperature has recently drawn considerable attention from researchers to address the limitations of traditional forecasting models. However, a middle-range (e.g., 5–20 days) forecasting is an extremely challenging task to get reliable forecasting results from [...] Read more.

Time series forecasting of meteorological variables such as daily temperature has recently drawn considerable attention from researchers to address the limitations of traditional forecasting models. However, a middle-range (e.g., 5–20 days) forecasting is an extremely challenging task to get reliable forecasting results from a dynamical weather model. Nevertheless, it is challenging to develop and select an accurate time-series prediction model because it involves training various distinct models to find the best among them. In addition, selecting an optimum topology for the selected models is important too. The accurate forecasting of maximum temperature plays a vital role in human life as well as many sectors such as agriculture and industry. The increase in temperature will deteriorate the highland urban heat, especially in summer, and have a significant influence on people’s health. We applied meta-learning principles to optimize the deep learning network structure for hyperparameter optimization. In particular, the genetic algorithm (GA) for meta-learning was used to select the optimum architecture for the network used. The dataset was used to train and test three different models, namely the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Our results demonstrate that the hybrid model of an LSTM network and GA outperforms other models for the long lead time forecasting. Specifically, LSTM forecasts have superiority over RNN and ANN for 15-day-ahead in summer with the root mean square error (RMSE) value of 2.719 (°C). Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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18 pages, 5923 KiB

Open AccessArticle

Two Ways to Quantify Korean Drought Frequency: Partial Duration Series and Bivariate Exponential Distribution, and Application to Climate Change

by Jeongeun Won, Jeonghyeon Choi, Okjeong Lee, Moo Jong Park and Sangdan Kim

Atmosphere 2020, 11(5), 476; https://doi.org/10.3390/atmos11050476 - 07 May 2020

Cited by 9 | Viewed by 2362

Abstract

Studies using drought index to examine return levels of drought can be classified into two approaches: univariate frequency analysis using annual series extracted from drought index time series and multivariate frequency analysis that simultaneously reflects various characteristics of drought. In the case of [...] Read more.

Studies using drought index to examine return levels of drought can be classified into two approaches: univariate frequency analysis using annual series extracted from drought index time series and multivariate frequency analysis that simultaneously reflects various characteristics of drought. In the case of drought analysis, it is important to properly consider the duration, so, in this study, univariate frequency analysis is performed using the partial duration series. In addition, a bivariate frequency analysis is performed using a relatively simple bivariate exponential distribution to give a more realistic return level to major drought events in the past while reflecting the correlation between drought severities and durations. The drought severity–duration–frequency curves using each of the two frequency analyses are derived, and these curves are used to examine how the drought phenomenon currently in progress is evolving. From this, the advantages and disadvantages of the two approaches, as well as the points to be aware of in application, are discussed. Finally, using the two approaches to the proposed drought frequency analysis, the behavior of Korea’s future extreme droughts is investigated under the conditions of various future climate change scenarios. Full article

(This article belongs to the Special Issue Meteorological Extremes in Korea: Prediction, Assessment, and Impact)

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