Empirical Orthogonal Function Mode Research Articles

Influence of Kamchatka Blocking and East Asian winter monsoon on the winter 2m‐temperature over South Korea

AbstractThis 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.

Distribution of lightning spatial modes and climatic causes in China

This paper investigates the distribution of spatial modes of cloud-to-ground (CG) lightning activity across China's land areas during the period 2010–20 and their possible causes based on the CG lightning dataset of the China National Lightning Detection Network. It is found that the first empirical orthogonal function mode (EOF1) occupies 32.86% of the total variance of the summer CG lightning anomaly variation. Also, it exhibits a negative–positive–negative meridional seesaw pattern from north to south. When the SST of the East Pacific and Indian Ocean warms abnormally and the SST of the Northwest Pacific becomes abnormally cold, a cyclonic circulation is stimulated in the Yellow Sea, East China Sea, and tropical West Pacific region of China. As the water vapor continues to move southwards, it converges with the water vapor deriving from the Bay of Bengal in South China, and ascending motion strengthens here, thus enhancing the CG lightning activity of this area. Affected by the abnormal high pressure, the corresponding CG lightning activities in North China and Northeast China are relatively weak. The ENSO phenomenon is the climate driver for the CG lightning activity occurring in land areas of China.摘要本文利用中国气象局国家雷电监测网 (CNLDN) 的地闪观测数据集, 分析了2010–2020年中国陆地区域地闪空间模态分布特征及其可能的气候成因. 研究发现, 夏季地闪第一模态的方差贡献率为32.86%, 其分布从北到南呈现出“−+−”的经向跷跷板模式. 当东太平洋和印度洋的海温异常增暖, 西北太平洋的海温异常变冷时, 在中国黄海, 东海及热带西太平洋地区激发出气旋性环流. 随着水汽南下至华南地区, 与来自孟加拉湾的水汽汇合, 上升运动在此加强, 从而使得该地区的雷电活动增强. 表明厄尔尼诺-南方涛动 (ENSO) 现象, 是发生在中国陆地区域的地闪活动的气候驱动因子.

A hybrid deep learning model for predicting the Kuroshio path south of Japan

At present, many prediction models based on deep learning methods have been widely used in ocean prediction with satisfactory results. However, few deep learning models are used to predict the Kuroshio path south of Japan. In this study, a hybrid deep learning prediction model is constructed based on the long short-term memory (LSTM) neural network, combined with the complex empirical orthogonal function (CEOF) and bivariate empirical mode decomposition (BEMD), called CEOF-BEMD-LSTM. We train the model by using a 50-year (1958-2007) long time series of daily mean positions of the Kuroshio path south of Japan extracted from a regional ocean reanalysis dataset. During the test period of 15 years (2008-2022) by using daily altimetry dataset, our model shows a good performance for the Kuroshio path prediction with the lead time of 120 days, with 0.44° root-mean-square error (RMSE) and 0.75 anomaly correlation coefficient (ACC). This model also has good prediction skill score (SS). Moreover, the CEOF-BEMD-LSTM model successfully hindcasts the formation of the latest Kuroshio large meander since the summer of 2017. Predictions of the Kuroshio path for the coming 120 days (from January1 to April 30, 2023) indicate that the Kuroshio will continue to remain in the state of the large meander. Besides, predictor(s) of the Kuroshio path south of Japan need to be sought and added in future research.

Deep Learning–Based Prediction of Kuroshio Path South of Japan

Abstract Variation of the Kuroshio path south of Japan has an important impact on weather, climate, and ecosystems due to its distinct features. Motivated by the ever-popular deep learning methods using neural network architectures in areas where more accurate reference data for oceanographic observations and reanalysis are available, we build four deep learning models based on the long short-term memory (LSTM) neural network, combined with the empirical orthogonal function (EOF) and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), namely, the LSTM, EOF–LSTM, CEEMDAN–LSTM, and EOF–CEEMDAN–LSTM. Using these models, we conduct long-range predictions (120 days) of the Kuroshio path south of Japan based on 50-yr ocean reanalysis and nearly 15 years of satellite altimeter data. We show that the EOF–CEEMDAN–LSTM performs the best among the four models, by attaining approximately 0.739 anomaly correlation coefficient and 0.399° root-mean-square error for the 120-day prediction of the Kuroshio path south of Japan. The hindcasts of the EOF–CEEMDAN–LSTM are successful in reproducing the observed formation and decay of the Kuroshio large meander during 2004/05, and the formation of the latest large meander in 2017. Finally, we present predictions of the Kuroshio path south of Japan at 120-day lead time, which suggest that the Kuroshio will remain in the state of the large meander until November 2022.

Low latitude monthly total electron content composite correlations

Spatial correlations of total electron content (TEC) variability are compared among two SAMI3 model runs and Jet Propulsion Laboratory Global Ionospheric Maps (JPL/GIM). Individual monthly correlation maps are constructed with Equatorial reference points at 12 evenly spaced longitudes and 12 universal times. TEC composite correlations (TCCs) are then calculated by averaging the individual maps, shifted zonally to synchronize local time. The TCC structures are quantified using Gaussian fits in the zonal and meridional directions. A non-zero large-scale “base correlation” is found in all three datasets for 2014, a year with high solar activity. Higher base correlations generally occur in the SAMI3 runs than in JPL/GIM. The SAMI3 run driven with climatological neutral fields shows higher correlations than the run driven with neutrals from a Whole Atmosphere Community Climate Model with thermosphere–ionosphere eXtension (WACCM-X) simulation. Base correlation values strongly correlate with monthly F10.7 standard deviations. Empirical orthogonal function (EOF) analyses confirm that large-scale correlations are usually, although not always, related to solar forcing. Strong correlations between the Ap index and EOF modes are also observed, consistent with the geomagnetic forcing of the TEC field. The widths of the correlation structures are also examined, and these vary considerably with local time, month, and dataset. Off-Equator conjugate point correlations are also calculated from each dataset and variations with the month and local time are analyzed. Analysis of TCCs for 2010, a year with low solar activity, shows that base correlations as well as correlations of the first EOF mode with F10.7 are generally weaker than in 2014.

Role of local and remote forcing on the decadal variability of Mixed Layer Depth in the Bay of Bengal

The Mixed Layer Depth (MLD) of an ocean acts as a storage of the incoming heat and releases via air-sea exchange processes. The present study tries to understand the decadal variability of MLD over the Bay of Bengal (BoB) and its association with local as well as external forcing. The time series and wavelet analysis confirm the significant decadal signals for the period from 1980 to 2015. The BoB MLD is found to have opposing trend prior to and post of 1998. In the decadal timescale, the BoB MLD is found to be comparably deep for regime-1 (1980–1998) and shallow for regime-2 (1999–2014) with stronger variation in the western bay. The local forcing like wind, wind-related processes, and Evaporation minus Precipitation (E-P) are found to have a prominent role to modulate the decadal variability of BoB MLD. The leading mode of the decadal Empirical Orthogonal Function (EOF-1) of MLD over the BoB shows a strong spatial pattern with the strongest in the western part of the Bay. The corresponding principal component shows a similar variability to Interdecadal Pacific Oscillation (IPO) signal. The enhancement of descending (ascending) branch of the Indian branch of Walker circulation (IWC) in the positive (negative) phase of IPO influences the changes over the equatorial Indian Ocean remotely modulate MLD of the coastal region of the BoB via the propagating coastal Kelvin waves. The decadal variability of MLD in the coastal region of the BoB is caused mainly by remote effect but the interior BoB is by the local factors.

Interannual to decadal sea level variability in the subpolar North Atlantic: the role of propagating signals

Abstract. The gyre-scale, dynamic sea surface height (SSH) variability signifies the spatial redistribution of heat and freshwater in the ocean, influencing the ocean circulation, weather, climate, sea level, and ecosystems. It is known that the first empirical orthogonal function (EOF) mode of the interannual SSH variability in the North Atlantic exhibits a tripole gyre pattern, with the subtropical gyre varying out of phase with both the subpolar gyre and the tropics, influenced by the low-frequency North Atlantic Oscillation. Here, we show that the first EOF mode explains the majority (60 %–90 %) of the interannual SSH variance in the Labrador and Irminger Sea, whereas the second EOF mode is more influential in the northeastern part of the subpolar North Atlantic (SPNA), explaining up to 60 %–80 % of the regional interannual SSH variability. We find that the two leading modes do not represent physically independent phenomena. On the contrary, they evolve as a quadrature pair associated with a propagation of SSH anomalies from the eastern to the western SPNA. This is confirmed by the complex EOF analysis, which can detect propagating (as opposed to stationary) signals. The analysis shows that it takes about 2 years for sea level signals to propagate from the Iceland Basin to the Labrador Sea, and it takes 7–10 years for the entire cycle of the North Atlantic SSH tripole to complete. The observed westward propagation of SSH anomalies is linked to shifting wind forcing patterns and to the cyclonic pattern of the mean ocean circulation in the SPNA. The analysis of regional surface buoyancy fluxes in combination with the upper-ocean temperature and salinity changes suggests a time-dependent dominance of either air–sea heat fluxes or advection in driving the observed SSH tendencies, while the contribution of surface freshwater fluxes (precipitation and evaporation) is negligible. We demonstrate that the most recent cooling and freshening observed in the SPNA since about 2010 were mostly driven by advection associated with the North Atlantic Current. The results of this study indicate that signal propagation is an important component of the North Atlantic SSH tripole, as it applies to the SPNA.

Variations of Summertime SSTA Independent of ENSO in the Maritime Continent and Their Possible Impacts on Rainfall in the Asian–Australian Monsoon Region

Abstract The sea surface temperature anomalies (SSTA) in the Maritime Continent (MC) region are mainly related to local variability, ENSO, and the Indian Ocean dipole. Using the reanalysis data from NOAA and NCEP–NCAR, by employing the empirical orthogonal function (EOF) analysis, we have explored the principal mode of ENSO-independent summertime SSTA in the MC and its associations with regional climate anomalies. After ENSO signals have been removed, the leading mode of SSTA in the MC exhibits a uniformly signed pattern, which mainly varies on an interannual time scale. The maintenance mechanisms of the ENSO-independent SSTA are different in different subregions, especially over the region south of Java and the tropical northwestern Pacific. When the time coefficient of the first leading EOF mode (EOF1) is positive, warmer SSTAs are observed in the area south of Java. The oceanic dynamic heating there facilitates the warmer SSTA. Thus, the Gill-type response of the atmosphere is found over the region south of Java. The diabatic cooling in the atmosphere is dominant over the tropical northwestern Pacific where the warmer SSTA is maintained by the absorption of solar radiation due to less cloud cover there. A tilted vertical circulation is hence formed, linking the tropical southeastern Indian Ocean with the tropical northwestern Pacific. The anomalous circulations in the Asian–Australian monsoon region are affected by this ENSO-independent SSTA mode, resulting in decreased summer rainfall anomaly in the region near the southeast coast of China and increased winter precipitation anomaly over the extratropical region of Australia.

Changes in the Dominant Mode of Summer Precipitation Over the Central‐Eastern Tibetan Plateau Around the Mid‐1990s

AbstractThe interdecadal changes in the dominant mode of the summer precipitation over the central‐eastern Tibetan Plateau (TP) are investigated around the mid‐1990s. It is found that the leading empirical orthogonal function mode of the interannual variations of summer precipitation over the central‐eastern TP is shown an out‐of‐phase pattern, with opposite variation between the southeastern and northeastern TP during 1961–1996, while the dominant mode become an in‐phase pattern during 1997–2019. During 1961–1996, the dipole pattern of TP precipitation is mainly related to the North Atlantic Oscillation (NAO) and associated circulation anomalies. However, the impact of NAO on the dipole pattern of TP precipitation has weakened since the mid‐1990s. In contrast, during 1997–2019, more pronounced positive height anomalies in the upper troposphere are observed over the whole TP regions. Meanwhile, the southerly moisture flux from the Bay of Bengal and the Philippine Sea is prevalent significantly with strong moisture convergence. Further analysis demonstrates that this interdecadal spatial change is mainly linked to the significant increasing of the sea surface temperature in the North Atlantic, South Atlantic, and Indo‐Pacific warm pool, via wave trains propagation. The wave train‐related positive height anomalies over the TP regions are in favor of the strengthening of the South Asian high (SAH). Moreover, the zonal and meridional mean temperature advections by SAH‐related circulation anomalies are primarily responsible for the intense vertical flow anomalies. Consequently, the summer precipitation anomalies over the entire TP regions are largely enhanced and formed the mono‐sign pattern during 1997–2019.

EMPIRICAL ORTHOGONAL FUNCTION (EOF) ANALYSIS BASED ON GOOGLE COLAB ON SEA SURFACE TEMPERATURE (SST) DATASET IN INDONESIAN WATERS

Global Sea Surface Temperature (SST) data observed from yearly to yearly is limited in its use to determine spatial and temporal variations. The analysis was carried out on SST data in Indonesian waters for 252 months or for 21 years, starting from January 2000 to December 2020. The method used for analysis was Empirical Orthogonal Function (EOF) with the help of a statistical engine, Google Colab. The EOF method aims to reduce large data into several modes without eliminating the main information from the observed data. Analysis with this method resulted in the three largest principal components initialized with EOF1EOF2 and EOF3 modes. The EOF1 mode explains 56.8% of the total variation and is the dominant pattern representing almost all SST data in Indonesian waters. The EOF2 mode represents 24.5% of the total variation. The EOF3 modes each account for 13.4% of the total variation. Each EOF mode contains coefficients containing variables in the form of grid data and eigenvectors. Grid data describe geographic locations and eigenvectors describe spatial dimensions. The effectiveness of the three resulting EOF modes is kept close to the original data. Mapping of SST in the Indonesian Territory for 20 years has been carried out in this research, this study describes the seasonal visualization of SST data in Indonesian waters using Google Colab. This visualization shows the comparison of the distribution of sea surface temperature in the Indonesian waters throughout the year with seasonal patterns.

Leading-Mode Connections of the Interannual Variability in Upper-Ocean Salinity in the Tropical Indian Ocean

Abstract Leading modes of interannual variability in upper-ocean salinity in the tropical Indian Ocean (TIO) and their connections were studied based on 17 years (2002–18) of oceanic historical and reanalysis data. Empirical orthogonal function (EOF) analysis depicted the dominant roles of the first two leading modes in salinity variability in the TIO over a wide range of interannual time scales. Among the rich oscillations of the leading EOF modes, a coherent near-biennial band was identified with basinwide loading of sea surface salinity anomalies (SSSa) (EOF1) leading/lagging the northeast–southwest dipolar mode of SSSa (EOF2) by around 4 months across the TIO, with southwestward migration of SSSa center. The spatial loadings of the SSSa leading modes in the TIO were strongly shaped by sea surface temperature–related freshwater fluxes and wind-driven regional ocean circulation on a near-biennial time scale. Composite analysis of the mixed layer salinity budget reflected characteristic features of basin-scale ocean–atmosphere coupling, both temporally and regionally during the life cycle of the near-biennial fluctuation in anomalous salinity in the TIO. Consistent with the intrinsic oscillation paradigm in the observed Indian Ocean dipole (IOD) variation, the dynamic and thermodynamic feedbacks associated with switches from the positive to negative IOD modes provided the phase-connection mechanisms for the SSSa leading-mode displacement over the TIO. Significance Statement This study investigates the leading modes of interannual variability in upper-ocean salinity in the tropical Indian Ocean (TIO). The intrinsic oscillation and associated dynamic and thermodynamic feedbacks over the TIO drive the basinwide connections of upper-ocean salinity variability. Our results show that a coherent near-biennial band is identifiable within the leading modes of sea surface salinity anomalies (SSSa), in which the wind-induced horizontal advections and evaporation-minus-precipitation anomalies associated with the switches from positive to negative Indian Ocean dipole modes mainly provide the phase-transition mechanism of SSSa. This research illustrates substantial evidence for the displacement of basin-scale sea surface temperature anomalies modulating the structures of SSSa and inducing the dynamical connections of leading modes of SSSa on the near-biennial time scale.

Inversion of the Full-Depth Temperature Profile Based on Few Depth-Fixed Temperatures

Seawater temperature plays a key role in underwater acoustics and marine fishery, etc. In oceanographic surveys, it is often desirable to detect the temperature profile and obtain its spatio-temporal variation. The present study shows that the temperatures at the depths which are the three extreme points of the first two empirical orthogonal function (EOF) modes, contain the largest amount of information. Based on the back propagation (BP) neural network, a model for reconstructing the full-depth temperature profile using a few temperatures at fixed depth is established. The experimental result shows that the root mean square error (RMSE) of the temperature profile inversion in the test set is mostly less than 0.2 °C, and the three-dimensional temperature field obtained in this study is relatively reliable.

Recent changes in circulation patterns and their opposing impact on extreme precipitation at the west coast of Norway

Understanding recent and future changes of extreme precipitation is essential for climate change adaptation. Here, we use 3800 extreme precipitation events produced by an ensemble seasonal prediction system. The ensemble represents the climate from 1981 to 2018 and we analyse 3-day maximum precipitation events in September–October–November for the west coast of Norway. Two dominant atmospheric patterns, described by an empirical orthogonal function (EOF) analysis, are related to the results of the extreme value statistics. The principal components of the second and third mode of EOFs have significant trends over the last 40 years, but with an opposing impact on the return values of extreme precipitation. This explains the observed stationarity of extreme precipitation over recent decades at the west coast of Norway, which was also found in previous studies. The second mode of EOFs also shows a relation to the sea-ice coverage in the Barents and Kara Seas, which suggests a connection between the decline of sea-ice to the changes in the atmospheric pattern.

Investigations into mode characteristics of wind fields off the Guangdong coast using Empirical Orthogonal Function

As one of the clean and renewable energy sources, wind energy has received increasing attentions from the public in recent years. Large-scale investigations into wind speeds and directions can provide guidance and reference for regional wind energy assessment. In this paper, ECMWF-ERA5 wind field data were used to explore wind field characteristics off the Guangdong coast, where Empirical Orthogonal Function (EOF) analysis was employed to characterize the spatial and temporal patterns of wind fields over a long period. The results show that: (1) According to the characteristics of wind speeds, the research domain can be divided into three major sub-domains, including the landward sub-domain where the wind speed is lower and the wind direction are highly variable, the transitional sub-domain where the wind field has a gradual trend and the wind direction are the most dispersed, and the seaward sub-domain where the wind speed is higher and the wind direction are more concentrated; (2) Variance contributions of the first EOF mode for east–west and north–south components of wind speed vectors are 99.3% and 99.5%, respectively. This indicates that the seasonal oscillation of winter–summer has a one-year cycle. Additionally, variance contributions of the second EOF mode are only 1.4% and 1.5%, respectively, showing a spring–autumn monsoonal oscillation with a six-month to one-year cycle. Variance contributions of the third EOF mode for east–west and north–south components are only 0.5% and 0.7%, respectively. This indicates that a one-year to two-year cycle of oscillations exists, which may be related to the Tropospheric Biennial Oscillation (TBO) of the inter-annual variability of the East Asian summer wind.

Linking the Antarctic sea ice extent changes during 1979–2020 to seasonal modes of Antarctic sea ice variability

The Antarctic sea ice extent slowly expanded through the four-decade-long satellite era until 2014 when the expansion came to a halt, followed by a rapid contraction in the next couple of years. This sudden unexpected trend reversal has sparked considerable research interest and several mechanisms have been proposed to explain it; however, much remains to be explored. In this study, we show that the long-term increasing trend in the Antarctic sea ice extent and its recent reversal can be largely explained by the first, second and fourth empirical orthogonal function mode of sea ice variability in austral summer, autumn and spring, respectively. We illustrate that the sea ice variability represented by the three modes is mostly consistent with what is expected from the anomalous atmospheric circulations associated with planetary wavetrains that are triggered by anomalous sea surface temperature (SST) and convective activities over the Southern Indian and Pacific Oceans. More specifically, the results suggest a teleconnection between the increasing periods in the Antarctic sea ice extent in the past four decades and the positive SST anomalies over the southeastern Indian Ocean and the western tropical Pacific Ocean. The opposite occurs over the decreasing period. Accordingly, the same mechanisms, in different phases, have been associated with the periods of increasing and decreasing Antarctic sea ice extent.

PDO Modulation on the Relationship between ENSO and Typhoon Tracks

Abstract This study explores the role of the Pacific decadal oscillation (PDO) in modulating the relationship between El Niño–Southern Oscillation (ENSO) and typhoon tracks. Tropical cyclone (TC) trajectories in the western North Pacific (WNP) in 1950–2017 are clustered into seven clusters, including three recurved trajectories and four straight-moving tracks. These clusters are distinguished well by number of TCs, intensity, lifetime, genesis position/month, landing, and track. The sea surface temperature (SST) anomaly in the composite analysis and accumulated cyclone energy (ACE) of each cluster demonstrate that there are four clusters dominated by ENSO. The associated ENSO effects on these clusters are manifested by steering flow and vertical wind shear (VWS) in the composite differences between El Niño and La Niña years. However, such ENSO effects on TC quantity, genesis location, and track of these corresponding clusters are significantly enhanced during the PDO positive phases only for two clusters that are formed in the southeastern part of the WNP and undergo a long lifetime and track, because the PDO explains little local environmental variance where the other two clusters are located in the northern part of the WNP. This conclusion is also supported by TC track density analysis. The two leading modes of empirical orthogonal functions (EOF) analysis of TC track density are significantly correlated with ENSO. The enhancement of ENSO effects during the PDO positive phase exhibits by the second mode through local SST, VWS, and steering flow. Significance Statement Accurate prediction of tropical cyclone (TC) activity can help preparedness and therefore reduce the losses of life and property. Long-term track prediction relies on our understanding how TC tracks are associated with interannual and longer climate variability. This study uses historical data of 1950–2017 in the western North Pacific and reveals that only for two of four track clusters that are affected by El Niño–Southern Oscillation (ENSO), the associated ENSO effects are enhanced during the Pacific decadal oscillation positive phases because the oscillation has significant influence on vertical wind shear and steering flow where these two clusters are located. The findings enrich the mechanisms of TC track variabilities and will help improve long-term prediction of TC tracks.

The inhibition of warm advection on the southward expansion of sea ice during early winter in the Bering Sea

Recent observations demonstrate that the Bering Sea exhibits a substantial positive trend of sea ice area increment (ΔSIA, difference in SIA between the current and preceding months) in January contrasted to the considerable negative sea ice area (SIA) trend from 1979 to 2020, and the ΔSIA is unrelated to the local wind field anomaly. To better understand the January ΔSIA variability and its physical characteristics, we explore two distinct empirical orthogonal function (EOF) modes of sea ice concentration increments. EOF1 features a reduction in sea ice concentration (SIC) in the south of St. Lawrence Island. EOF2 is characterized by the rise of SIC surrounding St. Lawrence Island. EOF1 is related to the well-known physical process of December strong poleward heat transport in mixed layer depth. During the southward expansion of sea ice, the multiyear variation of the December SST tendency mostly relies on warm advection in the Bering Sea shelf rather than net air-sea heat flux, and the abnormal northeast wind in December no longer plays the role of a dynamic process dominating the ice area expansion, but generates a stronger poleward heat transport in the Bering Sea shelf to inhibit the southward development of sea ice in the later stage. The two physical processes together result in oceanic poleward heat transport regulating the Bering Sea SIA in competition with atmospheric forcing in early winter. Since PC1 (principal component (PC) time series for EOF1) has a high correlation of -0.76 with the maximum SIA in the Bering Sea, it can be used as the prediction index of the Bering Sea maximum SIA.

Application of Empirical Orthogonal Function Analysis to 1 km Ensemble Simulations and Himawari–8 Observation in the Intensification Phase of Typhoon Hagibis (2019)

An empirical orthogonal function (EOF) analysis was performed for the inner core of Typhoon Hagibis (2019) in the intensification phase. The Himawari–8 geostationary infrared (IR) brightness temperature (BT) collocated at the Hagibis’s center was combined with the IR BT simulated by a radiative transfer model, with 1 km ensemble simulations conducted by an atmosphere model and the coupled atmosphere–wave–ocean model. The ensemble simulations were conducted under one control atmospheric initial condition and the 26 perturbed ones with two different oceanic initial conditions. The first four EOF modes showed symmetric and asymmetric patterns such as a curved band, cloud dense overcast, and eye pattern used in the classification of the Dvorak technique. The influence of ocean coupling on the modes appeared only in the early intensification phase but was relatively small compared to the difference from the Himawari–8 observations. While ocean coupling and different oceanic initial condition quantitatively affected the IR BT, the normalized amplitude for the first EOF mode did not become close to that of the Himawari–8 observation in the late intensification phase. The intensification rate in the late intensification phase was inconsistent between the simulation results and the estimate from the Himawari–8 normalized amplitude by multiple linear regression analysis.

How has the North Pacific Gyre Oscillation affected peak season tropical cyclone genesis over the western North Pacific from 1965 to 2020?

The North Pacific Gyre Oscillation (NPGO) is an important mode of decadal variability in North Pacific sea surface temperature (SST) and sea surface height. This study investigated the potential influence of the NPGO on spatial characteristics of peak season (July to October) tropical cyclone genesis (TCG) number over the western North Pacific (WNP) from 1965 to 2020. We show that the NPGO was the first leading empirical orthogonal function mode of North Pacific SST during the peak tropical cyclone season in that time. On a decadal time scale, the NPGO has opposite impacts on TCG in the west and east WNP. The relatively weak positive correlation west of 140° E and the strong negative correlation east of 140° E result in an overall significant negative correlation between the NPGO and WNP total TCG number (r = −0.49), which is much more robust than the relationship between the Pacific Decadal Oscillation and TCG. The critical factors of the NPGO that affect TCG are vertical motion in the west WNP and vertical wind shear (VWS) in the east WNP. The positive NPGO pattern could induce an anomalous off-equatorial vertical circulation, resulting in an upward motion and increased convective precipitation in the west WNP, favoring local TCG. The anomalous convective precipitation enhances the zonal gradient of the atmospheric heat source in the east WNP, increasing VWS. The North Pacific low-level anticyclonic and upper-level cyclonic associated with the NPGO further enhance the VWS in the east WNP and lead to the negative low-level relative vorticity, inhibiting local TCG. This study emphasizes the importance of the climate impact of the NPGO in recent decades. The findings here have significant implications for the decadal prediction of change in WNP TCG.

Frequency of different types of El Niño events under global warming

AbstractThe El Niño–Southern Oscillation (ENSO) is the dominant natural climate pattern that influences the global climate on subdecadal timescales. Thus, a better understanding of the impacts of global warming on the characteristics of ENSO events offers large socioeconomic benefits. Changes in the frequency of the eastern Pacific (EP), central Pacific (CP) and total El Niño events are analysed in the future period (2051–2100) under the two shared socioeconomic pathways (SSPs) scenarios (i.e., SSP2‐4.5 and SSP5‐8.5) compared to the historical period (1951–2000) using outputs of eight models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Types of El Niño events are diagnosed based on pattern correlation coefficients (PCCs) between monthly sea surface temperature (SST) anomalies and the first two leading empirical orthogonal function (EOF) modes of SST anomalies in the tropical Pacific. Based on the ensemble of models, the number of total El Niño events decreases by 26 and 16% under the SSP2‐4.5 and SSP5‐8.5 scenarios, respectively, in the future compared to the historical period. A smaller decrease in the number of total El Niño events under the faster warming rate of the SSP5‐8.5 scenario suggests that the response of ENSO dynamics to global warming is not linear. Analysis of the Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5) dataset during the period 1951–2020 indicates that the ratio of the number of CP El Niño to EP El Niño has substantially increased over the past two decades. Nevertheless, under both the SSP2‐4.5 and SSP5‐8.5 scenarios in the future period, the ratio of the number of CP El Niño to EP El Niño does not change considerably compared to that in the historical period. This suggests that the recent increase in the frequency of CP El Niño could be a result of multidecadal variations rather than anthropogenic global warming.