The Arctic Oscillation (AO) is a well‐known mode that affects climate variability in the Northern Hemisphere. The equal‐weighed multi‐model ensemble (MME) of six state‐of‐the‐art models from the ...Copernicus Climate Change Service (C3S) and Pusan National University (PNU) was analysed to understand the wintertime AO performance for the hindcast period December–February 1993/1994–2016/2017. The hindcasts were chosen with lead times of 1 and 4 months with respect to the initialization date (August and November, respectively). The spread of the AO prediction skills of the individual models was significant. In general, the MME demonstrates superior skill compared to the average of single‐model skills in representing the AO pattern at lead times of 1 and 4 months. The AO‐related vertical structure predicted by MME is similar to the observation, but the upper‐level structure is relatively poor compared to the structure of the hindcasted lower‐ or mid‐level atmosphere. Both observation and MME indicate that since the mid‐1990s, the relationship between the AO and East Asian winter monsoon (EAWM) has been weak compared to the connection between the AO and El Niño–Southern Oscillation (ENSO). Simultaneously, the North Pacific centre of the AO moved eastward during the observational period. The MME showed an AO pattern similar to that observed. The eastward shift of the North Pacific centre of the AO may contribute to deepening the Aleutian low and its effect on the tight AO–ENSO relation demonstrated in observations and MME. Strong AO–ENSO relations and weak AO–EAWM connections are found in both observations and MME model. The observation and MME represent the wave activity flux from 60°N to the equator in the troposphere; consequently, the wave activity flux may contribute to the AO and ENSO connection in both observation and MME.
It is known that AO affects the EAWM through the SH, but in recent years, the relationship between AO–ENSO has been strengthened. We found that the AO–EAWM relationship weaker than the AO–ENSO relationship during DJF 1993/1994–2016/2017 in both observation and MME for the 1‐ and 4‐month leads. The movement of WAF from the pole to the equator in the troposphere may contribute to the connection between AO and ENSO.
This study conducted a correlation analysis between tropical cyclone genesis frequency (TCGF) in the western North Pacific (WNP) and heatwave days (HWD) in Korea during July and August for 1973–2018 ...and we found a strong positive correlation between them. This implied that the higher the TCGF in the WNP during July and August, the higher the HWD in Korea becomes. To examine the cause of the positive correlation between the TCGF during July and August in the WNP and the HWD in Korea, 15 years with the highest frequency and the lowest frequency out of the 46 years in the TCGF time series were selected and defined as high TCGF years and low TCGF years, respectively. According to the difference in atmospheric circulations between the two groups, in all layers of the troposphere, anomalous anticyclonic and cyclonic circulations were strengthened in the mid‐latitude region of East Asia and in the WNP, respectively, which was similar to the Pacific‐Japan (PJ) teleconnection pattern. The difference in the vertical meridional circulation averaged over the longitude range where Korea is located showed that anomalous upward and downward flows were strengthened in the WNP and in the latitude where Korea is located, respectively. This implied that the local Hadley circulation was strengthened during high TCGF years. Five hundred hectopascal wave activity flux originated from the North Atlantic, passed through the Scandinavian Peninsula, the North coast of Russia, and East Siberia before reaching Korea and the WNP. This spatial distribution was similar to the Scandinavia teleconnection pattern.
(a) Spatial distribution of data from observation stations and (b) monthly heatwave day variations in Korea.
Abstract This study investigates the influence of Okhotsk Sea blocking (OKB) on summer precipitation in East Asia in terms of the movement, enhancement and extension of the monsoon rainband. For this ...purpose, a composite analysis is conducted for nine OKB events that occur in June and July from 2000 to 2022. The results show that the OKB events that occur in June are associated with decreased precipitation in East Asia, whereas those that occur in July are related to increased precipitation in the same region. The long‐lasting OKB can continuously maintain and intensify anomalous cyclonic circulations in northeastern Asia, leading to enhanced vertically integrated moisture flux convergence (VIMFC) along the northern edge of the Western North Pacific subtropical high. However, there are differences in spatial distribution and displacement of anomalous cyclonic circulations between June and July. The OKB occurring in June is related to simultaneously developing and progressively strengthening anticyclonic circulation in the Okhotsk Sea as well as cyclonic circulation in northeastern Asia. Under the displacement of an intensified and southwardly extended cyclonic circulation, the VIMFC shifts southward and into a southeast‐to‐northwest orientation, compared to climatology, resulting in decreased precipitation in East Asia, particularly in southern China and southern Japan. On the other hand, when the OKB occur in July, anticyclonic circulation in the Okhotsk Sea is developed initially followed by cyclonic circulation in northeastern Asia, amplifying several days after onset. Anomalous cyclonic circulation is much weaker and located more northward than in June, which is favourable for stagnating and enhancing the VIMFC in East Asia. As a result, precipitation can increase in the region, particularly on the Korean Peninsula and in Japan.
The summer British–Baikal Corridor pattern (BBC) and the Silk Road pattern (SRP) manifest as zonally oriented teleconnections in the high and middle latitudes, respectively, of the Eurasian ...continent. In this study, we investigate the combined effects of the BBC and SRP on surface air temperatures over the Eurasian continent. It is found that the combination of the BBC and SRP results in two kinds of well-organized, large-scale circulation anomalies: the zonal tripole pattern and the Ω-like pattern in the 200-hPa geopotential height anomalies. The zonal tripole pattern is characterized by opposite variations between western Siberia/western Asia and Europe/central Asia/central Siberia, and the Ω-like pattern manifests as consistent variations over midlatitude Europe, western Siberia, and central Asia. Correspondingly, the resultant large-scale surface air temperature anomalies feature the same zonal tripole pattern and Ω-like pattern, respectively. Further results indicate that these two patterns resemble the two leading modes of surface air temperature anomalies over the middle to high latitudes of Eurasia. This study indicates that the temperature variations in the middle and high latitudes of Eurasia can be coordinated and evidently explained by the combination of the BBC and SRP, and it contributes to a more comprehensive understanding of the large-scale Eurasian climate variability.
This study examines the factors affecting the 2m‐temperatures (T2m) in South Korea in winter (DJF) from 1979/1980 to 2018/2019. For this purpose, we performed an empirical orthogonal function (EOF) ...analysis of the geopotential height at 500 hPa in the region 15°–75°N, 70°E–180° centred around the Korean Peninsula. The first EOF mode, which accounted for 31.1% of the total variance of the winter T2m in the region, is related to the KamChatka Blocking Frequency (KCBF). The second mode, which accounted for 18.3%, is associated with East Asian winter monsoon (EAWM). In addition to EOF analysis, the partial correlation (PC) analysis also confirmed that KCBF Index and EAWM Index, which are highly correlated with the winter T2ms in South Korea, are independent of each other. The individual and combined effects of the KCBF and EAWM are examined because they independently affect the winter T2ms in South Korea. According to the composite analysis, in the years when KCBF is higher than normal (H_KCBF), negative and positive Z500 anomalies are located over the south Sea of Japan and the Kamchatka Peninsula, respectively. In other words, the positive geopotential anomaly over the Kamchatka Peninsula lowers the T2ms of South Korea by blocking the flow of cold air moving eastward from the Korean Peninsula. In the years when a strong EAWM occurred (S_EAWM), negative and positive Z500 anomalies are located over the Manchuria region and the northwestern regions of Russia, respectively. Consequently, cold air in the north moves southward, resulting in lower T2ms in South Korea. For the combined effects of KCBF and EAWM on the T2ms, winters of 40 years are categorized into L_KCBF‐W_EAWM, L_KCBF‐S_EAWM, H_KCBF‐W_EAWM and H_KCBF‐S_EAWM years. The analyses show that when KCBF and EAWM are in phase, the T2ms in South Korea are more prominent than when they are out‐of‐phase.
Considering the combined effect of KCBF and EAWM in‐phase state, the effect on the winter temperature in South Korea is greater when looking at the combined effect rather than their individual effect through the composite anomaly of multiple variables.
This study examined the influence of atmospheric blocking on the variability of precipitation over South Korea during summer (June–July–August) by defining the blocking frequency over the Okhotsk Sea ...(Okhotsk Sea blocking frequency; OK_BF). According to composite analysis for the years of high precipitation over South Korea, blocking occurs more frequently over the Okhotsk Sea (140°E–160°E). Partial correlation and regression analyses were conducted to separate the contribution of OK_BF to precipitation variability from that of the low‐level meridional wind (LLMW) because LLMW over the region is another important aspect of summer precipitation in South Korea. The barotropic structures of positive geopotential height anomalies over the Okhotsk Sea associated with increasing OK_BF can induce negative temperature anomalies over South Korea due mainly to the equatorward advection of cold air masses from higher latitudes. The enhanced meridional temperature gradient can cause increases in baroclinic instability and zonal wind vertical shear according to the thermal wind balance. This instability can induce anomalous cyclonic circulations over South Korea, resulting in positive precipitation anomalies. The partial correlation coefficients (R2 = 0.35–0.40) between the OK_BF and precipitation indices, including mean precipitation, extreme precipitation intensity, wet days, and consecutive wet days, were all statistically significant at the 95% confidence level. Overall, the effects of the increasing OK_BF on both precipitation and potential evapotranspiration can intensify the surface water budget in South Korea.
The barotropic structures of blocking over the Okhotsk Sea (OKB) can induce negative temperature anomalies over South Korea (32.5°N–37.5°N, 125°E–130°E) due to the equatorward advection of cold air masses from higher latitudes. The enhanced meridional temperature gradient can cause increases in baroclinic instability and zonal wind vertical shear according to the thermal wind balance. The frequent occurrence of OKB can increase the baroclinic instability over South Korea, resulting in cyclonic circulations and increased precipitation over the same regions.
This study develops a statistical‐dynamical seasonal typhoon forecast model (SDTFM) that utilizes the statistical correlation between East Asia (EA) tropical cyclone (TC) landfall and atmospheric ...circulation predicted by a coupled general circulation model for seasonal prediction and its predictability is verified. A total of 40 ensemble members produced through different data assimilation and time‐lag methods introduced as a way to reduce the initial condition error and model uncertainty enabled the development of the new SDTFM. According to the results, the SDTFM developed in this study showed significant predictability in TC landfall prediction when using the month of May for the initial conditions for the entire East Asia (EEA) and its three sub‐domains: Northern East Asia (NEA), Middle East Asia (MEA), and Southern East Asia (SEA). The predicted TC season is July–September (JAS), and only for SEA, including South China, the Philippines, and Vietnam, it is July–November (JASON) considering the relatively long landfall period. The models developed for each domain significantly predict the interannual variability of TC landfall at the 99% confidence level. The cross‐validated results are still significant at the 99% confidence level in NEA and SEA and the 95% confidence level in MEA and EEA.
To predict tropical cyclone (TC) landfall in East Asia, a statistical‐dynamical seasonal typhoon forecast model (SDTFM) is developed using atmospheric circulation predicted by a coupled general circulation model as a predictor. The model shows a significant prediction skill at 99% confidence level for all domains (Northern East Asia (NEA), Middle East Asia (MEA), Southern East Asia (SEA), and entire East Asia (EEA)). According to the cross‐validation results, the SDTFM predicts TC landfalls at 99% confidence levels for NEA and SEA and 95% confidence levels for MEA and EEA, suggesting that the SDTFM can be used effectively for TC landfall prediction in East Asia.
In this study, a new statistical strategy to improve the long‐term prediction skill of a numerical model was developed. This new strategy begins by finding the major principal time series (PTs) in ...the observations using the self‐organizing map (SOM) method. Next, values at the model grid points that are highly correlated with the observational PTs for each ensemble member (EM) are combined to yield a modelled PT. Finally, the model prediction is corrected using the model PTs from the previous step. As the predictors for correction are objectively selected from among the signals found in model prediction, automatically considering their statistical correlation with predictands, the correction strategy is relatively free from the problem of selecting the proper predictor compared to conventional statistical correction methods. In addition, SOM shows a better performance in classifying nonlinear complex patterns than conventional data analysis methods, while both SOM and conventional methods such as the empirical orthogonal function show a comparable performance when classifying linear patterns. The new strategy is applied to the 12‐month‐lead sea surface temperatures hindcasted by the Pusan National University coupled general circulation model. After correction using the new strategy, temporal correlation coefficients and the hit rate are increased while normalized root mean square errors and the false alarm rate are decreased for each season and each lead time. The correction becomes more effective as the lead time increases. In particular, this correction effect is large over the region where the prediction skill without correction is apparently low, which implies that the biases leading to poor prediction skills are effectively reduced by the new strategy. Additionally, the prediction skill is steadily improved for all lead times as the number of EMs is increased, whereas it reaches a plateau when the number of neurons in the output layer of the SOM method exceeds a certain threshold.
Schematic diagram of the new correction strategy using SOM.
This study examined the characteristics of cold surges in the Korean Peninsula over the last 45 years (1975–2019). During the period, there were 37 cases of cold surges affected by blocking (B_CS) ...and 129 cases of cold surges not influenced by blocking (nB_CS), indicating that most of the cold surges were nB_CS. The blocking that caused a cold surge over the Korean peninsula occurred mostly in the Okhotsk region and Ural region (OK_B and UR_B, respectively). In rare cases, blocking occurred simultaneously in the two regions called double blocking (DO_B), causing strong and long‐lasting cold surges. The nB_CS was related closely to the propagating wave‐train, hence the mean duration of nB_CS was shorter than the B_CS because the wave‐train propagated fast from the northwest to the southeast. Although the number of occurrences of B_CS was low, B_CS was stronger and lasted longer than nB_CS. In the case of cold surges affected by UR_B, referred to as UR_CS, their progression was slower compared to the cold surges affected by nB_CS because UR_B is slowing the atmospheric flow in the west. For cold surges affected by OK_B (OK_CS), the progression was slower than nB_CS and UR_CS because blocking was located downstream, slowing the propagating trough. Accordingly, the mean durations of nB_CS, UR_CS, and OK_CS were 2.7, 3.6, and 5.1 days, respectively, the mean of the temperature anomaly throughout the cold surge, was −3.8, −5.4, and −5.1°C, respectively. Overall, both the intensity and the progression speed of the cold surges differed according to the presence and location of blocking. A common characteristic of all types of cold surges was that they occur after the passage of the trough having a baroclinic structure. In addition, all types of cold surges were linked to an expansion of the Siberian high.
The box plots show the distribution of (a) intensity, and (b) duration of the four types of cold surge in South Korea, where nB_CS, UR_CS, OK_CS, and DO_CS indicate cold surges of non‐blocking, Ural blocking, Okhotsk blocking, and double blocking types, respectively. In terms of intensity and duration, the characteristics of the four types of cold surge are more clearly distinguished. Overall, blocking type cold surge is stronger and lasts longer than non‐blocking type.
The hindcast data of Pusan National University coupled general circulation model (PNU CGCM), a participant model of the Asia‐Pacific Economic Cooperation Climate Center (APCC) Multi‐Model Ensemble ...Climate Prediction System, and August–October sea‐surface temperature (SST) in the northern Barents–Kara Sea (BKI) and the sea‐ice extent (SIE) in the Chukchi Sea (East Siberian Sea index ESI) are used for predicting 20 × 20‐km‐resolution anomalous surface air temperature at 2‐m height (aT2m) over Mongolia for boreal winter. For this purpose, area‐averaged surface air temperature (TI) and sea‐level pressure (SLP) over Mongolia are defined. Then four large‐scale indices, TImdl and SHImdl obtained from PNU CGCM, and TIMLR and SHIMLR obtained from multiple linear regressions on BKI and ESI, are incorporated using the artificial neural network (ANN) method for the prediction and statistical downscaling to obtain the monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter. An additional statistical method, which uses BKI and ESI as predictors of TI and SHI together with dynamic prediction by the CGCM, is used because of the relatively low skill of seasonal predictions by most of the state‐of‐the‐art models and the multi‐model ensemble systems over high‐latitude landlocked Eurasian regions such as Mongolia. The results show that the predictabilities of monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter are improved by applying ANN to both statistical and dynamical predictions compared to utilizing only dynamic prediction. The predictability gained by the proposed method is also demonstrated by the probabilistic forecast implying that the method forecasts aT2m over Mongolia in winter reasonably well.
Winter climatologies of T2m (colour, °C) and SLP (contour, hPa) from observation (1981–2015). Rectangle areas indicate domains for TI and SHI.
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