Cyclostationary Empirical Orthogonal Function Research Articles

Analysis of sea level variability and its contributions in the Bohai, Yellow Sea, and East China Sea

Understanding the sea level variability of the Bohai, Yellow Sea, and East China Sea (BYECS) is crucial for the socio-cultural and natural ecosystems of the coastal regions. In this study, based on satellite altimetry data, selected time range from 1993 to 2020, using the cyclostationary empirical orthogonal function (CSEOF) analysis method distinguishes the primary sea level variability modes. The analysis encompasses the seasonal signal, trend, and El Niño-Southern Oscillation (ENSO) associated mode of sea level anomaly. The amplitude of the annual cycle demonstrates a non-stationary signal, fluctuating between -15% and 15% from the average. Monsoons, atmospheric forcing, ocean circulation, wind-driven Ekman transport, and the Kuroshio emerge as the primary factors influencing BYECS variability on seasonal scales. The satellite altimetry sea level exhibits an average trend within the range of 3-4 mm/year, while the steric sea level trend is generally smaller, falling within the range of 0-2 mm/year. Throughout the entire period, the contribution of steric sea level to the mean sea level trend consistently remains below 25%. Furthermore, BYECS sea level variations have a sensitive response to strong El Niño years, with a clear regionalization of the response, which is related to the intricate atmospheric circulation and local wind pressures, as well as the influence of ocean circulation. In conclusion, we gained a more comprehensive understanding of sea level variability in the BYECS, especially the annual cycle of sea level amplitude and the response of ENSO. However, more studies still need to be done to differentiate the various factors in sea level variations.

The dominant modes of recent sea level variability from 1993 to 2020 in the China Seas

A better understanding of internal climatic variability is essential for estimating and predicting regional sea level rise in the coming decades. Based on the satellite altimeter data, the cyclostationary empirical orthogonal function (CSEOF) analysis is used to extract and examine the seasonal signal, trend, El Niño-Southern Oscillation (ENSO)-related, and low-frequency mode of sea level anomaly in the China Seas from 1993 to 2020. The interannual changes in the annual cycle of sea level were significantly influenced by the mean surface pressure and the 10-m zonal wind component. Furthermore, strong El Niño events (1997/1998) can significantly affect seasonal fluctuations through precipitation and runoff. By recombining the loading vector and principal component time series of the trend mode, we estimate the sea level trends to be about 3.63 ± 0.37 mm/yr. The South China Sea, followed by the Yellow Sea, is where ENSO's effects on sea level fluctuations are most noticeable. The 2015–2016 El Niño, which was a combination of the Central Pacific (CP) ENSO Eastern Pacific (EP) ENSO, had average sea levels that were much lower than those of the 1997–1998 (CP ENSO) and 2009–2010 (CP ENSO). The Pacific Decadal Oscillation (PDO) can significantly affect the low frequency mode, but other sources also contribute to this mode. The South China Sea, especially to the west of Luzon Island, exhibits the highest level of variability in the low-frequency mode. Finally, our work shows that, in contrast to global or oceanic scales, regional CSEOF analysis does, in fact, capture regional sea level variability more accurately and detailed.

Spatiotemporal patterns of groundwater over South Korea

Understanding the large-scale spatiotemporal pattern of multi-depth groundwater levels is critical to develop water management plans and policies for sustainable ecological and social prosperity, which are still lacking. Here, we investigate three major spatiotemporal modes of groundwater levels from ∼200 groundwater monitoring stations over the southern Korean Peninsula (2009–2020), using the Cyclostationary empirical orthogonal function analysis. The first two major modes are associated with the seasonality of recharge and discharge and groundwater use during the 2016/17 drought, which explained half of the total variance. The third major mode indicated a decreasing trend of deep groundwater levels over the western Korean Peninsula, where key administrative and authority offices have been relocated via balanced national land development policies. Furthermore, at least three million Koreans over this region likely experience groundwater depletion by the 2080s. Observational evidence of emerging groundwater depletion suggests a window of opportunity for pre-emptive groundwater management plans.

Evaluation of multi‐RCM ensembles for simulating spatiotemporal variability of Asian summer monsoon precipitation in the CORDEX‐East Asia Phase 2 domain

AbstractFive regional climate models (RCMs)—CCLM, RegCM, HadGEM3‐RA, SNURCM and WRF—participating in the Coordinated Regional Climate Downscaling Experiment‐East Asia (CORDEX‐EA) Phase 2 project are evaluated for their ability to simulate spatiotemporal variability in Asian summer precipitation. For this purpose, two dynamical downscaling sets, experiments forced by ERA‐Interim reanalysis data (reproduction experiment) and historical data from three Coupled Model Intercomparison Project 5 (CMIP5) general circulation models (GCMs) (historical experiment) are analysed. The horizontal resolution of the downscaled results is 25 km, and the analysis period is from 1981 to 2005 (25 years). The RCMs show reasonable performance in simulating the spatial and temporal characteristics of summer precipitation in CORDEX‐EA Phase 2 domain. To assess spatiotemporal patterns in Asian precipitation, cyclostationary empirical orthogonal function (CSEOF) analysis is used. In the first mode representing seasonal variations, the model ensemble results of both the reproduction experiment (Rep_ENS) and the historical experiment (His_ENS) simulate the peak times, location of precipitation and progression of the monsoons in Asia reasonably. Their features are greatly influenced by the moisture flux, indicating that the relation between precipitation and 850 hPa moisture flux is depicted well by RCM ensembles. In the second mode, which represents intraseasonal variations, the Rep_ENS depicts the western North Pacific summer monsoon break (WNPSM break) phenomenon similar to the observation. Although the His_ENS simulates the WNPSM break later than the observation, it does present the intraseasonal variation in the East Asian summer monsoon region. Based on these results, the five RCM ensemble results show the ability to capture spatiotemporal characteristics of summer precipitation in CORDEX‐EA Phase 2 domain, as well as added value from dynamical downscaling.

Spatiotemporal variations of 100 m wind in Mongolia and implications for wind energy resources

AbstractMongolia is a high‐altitude inland country, which experiences strong near‐surface winds that could be valuable resources for wind power generation. In this study, we examine the spatiotemporal variations of 100 m wind and assess wind energy potential in Mongolia using the European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) data during 1979–2020. Mongolia exhibits two peaks in the monthly variation of 100 m wind, the higher peak in April and the lower peak in November. The eastern and southern (ES) region of the country is characterized by relatively high wind speed, night‐time diurnal maximum of wind speed and relatively small amplitudes of monthly and diurnal variations of wind speed. This region is classified to have good potential for wind energy development with a long mean episode length. On the other hand, the western and northern (WN) region is characterized by relatively low wind speed, afternoon diurnal maximum of wind speed and relatively large amplitudes of monthly and diurnal variations of wind speed. This region is classified to have less wind energy potential. Four hotspots which have the greatest wind energy potential are found near the eastern border of Mongolia, south of the Gobi‐Altai Mountains, near the southern border of Mongolia and in the southern region. Two principal modes of spatiotemporal variations of 100 m wind speed are obtained using the cyclostationary empirical orthogonal function (CSEOF) analysis method. The first CSEOF mode shows a spatial contrast between western and eastern Mongolia and is positively amplified in winter and negatively amplified in summer, which is associated with the seasonal change of the East Asian monsoon. The second mode is amplified in spring and autumn and shows mountain–basin contrasts that are reversed diurnally, which may be associated with the mountain–plains solenoid circulations and resultant vertical mixing of momentum.

Global Terrestrial Water Storage Reconstruction Using Cyclostationary Empirical Orthogonal Functions (1979–2020)

Terrestrial water storage (TWS) anomalies derived from the Gravity Recovery and Climate Experiment (GRACE) mission have been useful for several earth science applications, ranging from global earth system science studies to regional water management. However, the relatively short record of GRACE has limited its use in understanding the climate-driven interannual-to-decadal variability in TWS. Targeting these timescales, we used the novel method of cyclostationary empirical orthogonal functions (CSEOFs) and the common modes of variability of TWS with precipitation and temperature to reconstruct the TWS record of 1979–2020. Using the same common modes of variability, we also provide a realistic, time-varying uncertainty estimate of the reconstructed TWS. The interannual variability in the resulting TWS record is consistent in space and time, and links the global variations in TWS to the regional ones. In particular, we highlight improvements in the representation of ENSO variability when compared to other available TWS reconstructions.

Impacts of the COVID-19 lockdown in China on new particle formation and particle number size distribution in three regional background sites in Asian continental outflow

Despite the curtailment of atmospheric condensing precursor gases during the Coronavirus disease 2019 (COVID-19) lockdown (LD) period, unexpected haze events via the formation of new particles and their subsequent growth have been identified. This study investigated the impact of emission reduction during the Chinese LD period on the new particle formation (NPF) frequency and corresponding particle number size distribution (PNSD) at three regional background atmospheric monitoring sites in the western coastal areas of the Korean Peninsula. During this duration, the number concentrations of the nucleation- (<25 nm) and accumulation-mode (>90 nm) particles significantly decreased in Baengryeong (BRY), showing decreases of 34% and 29%, respectively. Unlike BRY, the PNSD in Anmyeon (AMY), which is influenced by nearby industrial emissions, remained nearly unchanged during the LD period, possibly because the reduction in industrial emissions was not significant during the social distancing period enforced by Korea. Bongseong (BOS) showed a similar variation to that of BRY; however, the magnitude of the reduction was weaker because of its higher altitude compared to other sites. The cyclostationary empirical orthogonal function technique was applied to the measured PNSDs at the three sites to objectively classify NPF events. Because mode 1 of cyclostationary loading vectors commonly represented the typical diurnal variation of PNSD during regional NPF events at three sites, mode 1 of the corresponding principal component time series was used for NPF classification. The NPF frequency decreased by 7%, 1%, and 7% in BRY, AMY, and BOS, respectively, despite favorable meteorological conditions, such as increased temperature and insolation during the LD period. The diurnal variation in the sulfuric acid (H2SO4) proxy implied that the H2SO4 proxy acted as a determining factor for NPF events during the NPF occurrence time (8–12 local hours) in AMY and BOS; however, NPF occurrence in BRY was not connected to the H2SO4 proxy level. This suggests that BRY was more likely to be influenced by the reduction in organic species in the continental upwind regions, while the occurrence of NPF events in AMY and BOS can be suppressed in association with the distinct reduction in inorganic compounds represented by the H2SO4 proxy during the LD period.

Impacts of Climate Oscillation on Offshore Wind Resources in China Seas

The long-term stability and sustainability of offshore wind energy resources are very important for wind energy exploration. In this study, the Cyclostationary Empirical Orthogonal Function (CSEOF) method, which can determine the time varying spatial distributions and long-term fluctuations in the cyclostationary geophysical process, was adopted to investigate the geographical and temporal variability of offshore wind resources in China Seas. The CSEOF analysis was performed on wind speeds at 70 m height above the sea surface from a validated combined Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) wind product (2000–2016) with high spatial resolution of 12.5 km, and Climate Forecast System Reanalysis (CFSR) wind data (1979–2016) with a grid size of 0.5° × 0.5°. The decomposition results of the two datasets indicate that the first CSEOF mode represents the variability of wind annual cycle signal and contributes 77.7% and 76.5% to the wind energy variability, respectively. The principal component time series (PCTS) shows an interannual variability of annual wind cycle with a period of 3–4 years. The second mode accounts for 4.3% and 4.7% of total wind speed variability, respectively, and captures the spatiotemporal contribution of El Niño Southern Oscillation (ENSO) on regional wind energy variability. The correlations between the mode-2 PCTS of scatterometer or CFSR winds and the Southern Oscillation Index (SOI) are greater than 0.7, illustrating that ENSO has a significant impact on China’s offshore wind resources. Moreover, the mode-1 or mode-2 spatial pattern of CFSR winds is basically consistent with that of scatterometer data, but CFSR underestimates the temporal variability of annual wind speed cycle and the spatial changes of wind speed related to ENSO. Compared with reanalysis data, scatterometer winds always demonstrate a finer structure of wind energy variability due to their higher spatial resolution. For ENSO events with different intensities, the impact of ENSO on regional wind resources varies with time and space. In general, El Niño has reduced wind energy in most regions of China Seas except for the Bohai Sea and Beibu Bay, while La Niña has strengthened the winds in most areas except for the Bohai Sea and southern South China Sea.

Evaluation of Technology for the Analysis and Forecasting of Precipitation Using Cyclostationary EOF and Regression Method

Precipitation time series exhibit complex fluctuations and statistical changes. Existing research stops short of a simple and feasible model for precipitation forecasting. In this article, the authors investigate and forecast precipitation variations in South Korea from 1973 to 2021 using cyclostationary empirical orthogonal function (CSEOF) and regression methods. First, empirical orthogonal function (EOF) and CSEOF analyses are used to examine the periodic changes in the precipitation data. Then, the autoregressive integrated moving average (ARIMA) method is applied to the principal component (PC) time series derived from the EOF and CSEOF precipitation analyses. The fifteen leading EOF and CSEOF modes and their corresponding PC time series clearly reflect the spatial distribution and temporal evolution characteristics of the precipitation data. Based on the PC forecasts of the EOF and CSEOF models, the EOF–ARIMA composite model and CSEOF–ARIMA composite model are used to obtain quantitative precipitation forecasts. The comparison results show that both composite models have good performance and similar accuracy. However, the performance of the CSEOF–ARIMA model is better than that of the EOF–ARIMA model under various measurements. Therefore, the CSEOF–ARIMA composite forecast model can be considered an efficient and feasible technology representing an analytical approach for precipitation forecasting in South Korea.

Cyclostationary EOF Modes of Antarctic Sea Ice and Their Application in Prediction

AbstractThis study examines the modes of sea ice concentration (SIC) in the Southern Ocean from a new perspective using the cyclostationary empirical orthogonal function (CSEOF) method, which decomposes a space‐time field into a combination of modulating variability on phase‐locked annual cycles. The first CSEOF mode of SIC (72.55% of total variance) represents the normal annual cycle modulated by a low‐frequency oscillation. The second mode of SIC (3.39%) represents the trend pattern, which reveals that the SIC increases in most regions of the Southern Ocean except for those adjacent to the Antarctic Peninsula, wherein the decreasing SIC trend is evident in austral warm seasons. This trend mode also explains that the sea ice in the Weddell Sea is increasing in austral summer and decreasing in austral winter. The Principal Component (PC) of this model is negatively corrected with the Southern Annular Mode index with a correlation coefficient of about −0.5. The third mode of SIC (2.48%) represents a wavenumber‐2 Antarctic Circumpolar Wave mode that is linked to ENSO. As the CSEOF method decomposes the space‐time SIC field into low‐frequency modulations of phase‐locked annual cycles, it can be used for SIC prediction, by taking the spatial modes as the basis functions and predicting their PCs from the autoregressive models. However, this CSEOF‐based SIC prediction model exhibits unsatisfactory forecast skills, even with optimized model parameters. Therefore, it is still necessary to study more SIC prediction models and evaluate their forecast skills in the future.

Identifying ENSO-related interannual and decadal variability on terrestrial water storage

We apply two statistical techniques to satellite measurements to identify a relationship between terrestrial water storage (TWS) and El Niño-Southern Oscillation (ENSO). First, we modified and used the least-squares regression of a previous study using longer records. Second, we applied a cyclostationary empirical orthogonal function analysis (CSEOF). Although the CSEOF technique is distinct from the least-squares regression in that it does not consider proxies, each method produces two modes (decadal and interannual), showing consistency with each technique in spatial pattern and its evolution amplitudes. We also compared the results obtained by the two methods for thirty watersheds, of which five watersheds were compared with previous studies. The combination of the two modes explains the total variance in most watersheds showing the role that interannual and decadal ENSO-related signals in understanding terrestrial water storage variability. The results show that the decadal mode, along with the interannual mode, also plays an important role in describing the local TWS.

Observation of aerosol size distribution and new particle formation under different air masses arriving at the northwesternmost South Korean island in the Yellow Sea

Particle number size distribution (PNSD) was measured with scanning mobility particle sizers from January 2014 to December 2016 at the Baengnyeong-do Comprehensive Monitoring Observatory, located on a rural island between China and the Korean Peninsula. Five different typical air mass transport pathway types were identified using the fuzzy c-means clustering method. Aerosols from the Shandong Province (Type 3) and South Korea (Seoul Metropolitan Area; Type 4) generally showed larger modal diameters than those transported from Mongolia and West Manchuria through the free troposphere (Type 1), which is attributable to the coagulation and condensational growth of preexisting particles. New particle formation (NPF) events, identified from the first mode of cyclostationary empirical orthogonal function analysis of the PNSD were observed in 42.2% (strong NPF [16.9%], weak NPF [25.3%]) of the days included in this study. Strong NPF events were frequently observed from October to March under the influence of pristine free tropospheric air masses transported along the Type 1 pathway, which can be characterized as NPF supported by meteorological conditions and a small condensation sink (3.77 × 10−3 s−1) under a limited precursor gas supply (i.e., SO2). Some occasional strong NPF events occurred under the influence of Type 3 air masses, primarily in spring (April to May), with a relatively high particle growth rate (6.95 nm h−1) and condensation sink (6.74 × 10−3 s−1), attributed to the relatively high preexisting particle concentration and abundant gaseous precursors.

The leading modes of NH extratropical tropopause variability and their connection with stratosphere-troposphere variability

The leading modes of Northern Hemisphere tropopause variability for November–April (1979/1980–2018/2019) and the associated stratosphere-troposphere variability were analyzed based on the NCEP and ERA interim reanalysis products. For this, cyclostationary empirical orthogonal function technique is employed. The first two modes feature the intraseasonal evolution of tropopause pressure anomalies over the Arctic, which respond directly to stratospheric temperature fluctuations in association with stratospheric polar vortex variations. These two modes reflect the link between stratospheric polar vortex strength and high-latitude tropospheric circulation. The first mode represents a single-phase fluctuation of the stratospheric polar vortex from winter to early spring. The second mode describes a two-phase fluctuation of the stratospheric vortex with opposite signs in winter and in spring. Tropopause pressure anomalies near the mid-latitude tropospheric jet regions exhibit significant zonal variation. In the first mode, in particular, these mid-latitude tropopause anomalies are linked to asymmetric jet variations in the Atlantic and the Pacific regions. In regard to the Northern Annular mode, distinct vertical evolution structures of the two modes are practically related to the varying evolutionary structure of extreme vortex events with relatively long persistence.

Influence of Northern Hemispheric Winter Warming on the Pacific Storm Track

Effect of global warming on the sub-seasonal variability of the Northern Hemispheric winter (NDJFM) Pacific storm-track (PST) activity has been investigated. Previous studies showed that the winter-averaged PST has shifted northward and intensified, which was explained in terms of energy exchange with the mean field. Effect of global warming exhibits spatio-temporal heterogeneity with predominance over the Arctic region and in the winter season. Therefore, seasonal averaging may hide important features on sub-seasonal scales. In this study, distinct sub-seasonal response in storm track activities to winter Northern Hemispheric warming is analyzed applying cyclostationary empirical orthogonal function analysis to ERA5 data. The key findings are as follows. Change in the PST is not uniform throughout the winter; the PST shifts northward in early winter (NDJ) and intensifies in late winter (FM). In early winter, the combined effect of weakened baroclinic process to the south of the climatological PST and weakened barotropic damping to the north is responsible for the northward shift. In late winter, both processes contribute to the amplification of the PST. Further, change in baroclinic energy conversion is quantitatively dominated by eddy heat flux, whereas axial tilting of eddies is primarily responsible for change in barotropic energy conversion. A close relationship between anomalous eddy heat flux and anomalous boundary heating, which is largely determined by surface turbulent heat flux, is also demonstrated.

Investigation of South Korea Precipitation Variation using Empirical Orthogonal Function (EOF) and Cyclostationary EOF

The monthly precipitation data of 56 stations during 47 years (1973-2019) in South Korea are comprehensively analysed using the EOF technique and CSEOF technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The first mode account for 77.07% of the total variance and exhibits annual cycle of corresponding PC time series with traditional spatial pattern, and the second mode spatial patterns account for 8.13% of the total variance and show strong north to south gradient. In CSEOF analysis, two leading modes temporal pattern of PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation, the first mode temporal pattern of PC time series account for 73.55% of the total variance and shows an increasing linear trend which represents that temporal variability of first mode pattern has been strengthened. The spatial distribution corresponding to two leading modes show monthly spatial variation. Compared with the EOF analysis, the CSEOF analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of South Korea historical precipitation.

20th Century Multivariate Indian Ocean Regional Sea Level Reconstruction

AbstractDespite having some of the world's most densely populated and vulnerable coastlines, Indian Ocean sea level variability over the past century is poorly understood relative to other ocean basins primarily, due to the short and sparse observational records. In an attempt to overcome the limitations imposed by the lack of adequate observations, we have produced a 20th century Indian Ocean sea level reconstruction product using a new multivariate reconstruction technique. This technique uses sea level pressure and sea surface temperature in addition to sea level data to help constrain basin‐wide sea level variability by (1) the removal of large spurious signals caused as a result of insufficient tide gauge data specifically during the first half of the 20th century and (2) through its information on large‐scale climate modes such as El Niño‐Southern Oscillation and Indian Ocean Dipole. Basis functions generated by Cyclostationary Empirical Orthogonal Functions are used for the reconstruction. This new multivariate technique provides improved regional sea level variability estimates along with a longer record length in comparison to existing globally reconstructed sea level data. The biggest advantage of using this multivariate reconstruction technique lies in its ability to reconstruct Indian Ocean sea level for the first half of the 20th century, providing a long sea level record for the study of Indian Ocean internal climate variability. This will enable future studies to help improve the understanding of how sea level trends and variability can be modulated by internal climate variability in the Indian Ocean.

Relationship between submicron particle formation and air mass history observed in the Asian continental outflow at Gosan, Korea, during 2008–2018

We investigated the impact of air mass origin on submicron particle size distributions and new particle formation (NPF) events using 10-year measurements at Gosan, Korea, in the Asian continental outflow. NPF events were identified on approximately 27.1% of total observation days, and 123 and 381 days of them were classified as strong and weak NPF days, respectively, based on the first-mode loading vectors and corresponding principal components in the cyclostationary empirical orthogonal function analysis. NPF events occurred less than 15% of the total observation days for the South China (SC), Pacific Ocean, and stagnation (ST) air mass sectors, whereas 33.1% (243 days out of total 734 observation days) were identified as NPF events for the air mass traveling from the North China (NC) sector. Consistently, the lowest mode diameter (50.5 nm), highest formation rate, and the lowest growth rate were found in the NC air mass sector. The highest mode diameter (89.8 nm) was observed at the SC air mass sector because of the coagulation of newly formed aerosols under relatively humid conditions during the transport in summer. The condensation sink for SC (10.70 ± 2.35 × 10−3 s−1) and ST (10.80 ± 4.24 × 10−3 s−1) was approximately 25% higher than that for the NC air mass sector.

Characteristics of stratospheric polar vortex fluctuations associated with sea ice variability in the Arctic winter

The leading two modes of winter (November–February) Arctic sea ice cover variability and their linkage to stratospheric polar vortex variations are analyzed based on the cyclostationary EOF techniques. The first mode represents an accelerating trend of Arctic sea ice decline associated with Arctic amplification, particularly in the Barents and Kara Seas. The second mode is associated with decadal-scale phase shifts of dipole sea ice anomalies in the North Atlantic caused by NAO circulation. The first two modes of sea ice variability represent respectively a forced climate change and internal variability, and result in temporally and spatially distinct stratospheric polar vortex weakening. Sea ice reduction in the Barents and Kara Seas for the first mode is linked to a stratospheric vortex weakening during mid January–late February. The second mode with the dipole structure of positive sea ice anomalies in the Barents and Greenland Seas and negative anomalies in the Hudson Bay and Labrador Sea is related to a stratospheric vortex weakening during December–early February. The spatial evolutionary structure of anomalous polar vortex also exhibits differences between the two modes. When stratospheric anomalies are fully developed, stratospheric vortex is shifted to Eurasia in the first mode and to Europe in the second mode.

Physical mechanisms of surface wind variability at Incheon Airport

AbstractThe mechanisms of surface wind variability observed by Aerodrome Meteorological Observation System at Incheon International Airport (IIA), located near the western coast of the Korean Peninsula, are investigated using cyclostationary empirical orthogonal function (CSEOF) analysis. Despite the complex nature of surface wind, as various factors contribute to its variance, distinct features of surface wind variability are separated reasonably into CSEOF modes. The physical interpretation of each mode using the ERA‐Interim reanalysis data is accomplished through regression analysis in CSEOF space. In essence, three atmospheric features dominate the surface wind variability: East Asian monsoon, land–sea breeze, and baroclinic waves. East Asian monsoon, the first mode, explains ~12% of the total variance of the surface wind at IIA. The annual reversal of the monsoon circulation due to the thermal contrast between the Asian continent and the western Pacific is captured as the single most dominant source of surface wind variability at IIA. The second CSEOF mode reveals that zonal circulation induced by land–sea breeze dominates the diurnal variation of the surface wind at IIA, and explains ~8% of the total variance. The largest fraction of variability is associated with baroclinic waves, which is separated into many CSEOF modes due to their irregular phase and wavelength, and the locations of vortex centre. Modes 3–10 are all associated with baroclinic waves and they together explain ~42% of the total variance. Baroclinic waves are amplified as they move over the ocean due to strong turbulent flux from the ocean surface induced by the associated upper tropospheric vortices.

Summertime variability of the western North Pacific subtropical high and its synoptic influences on the East Asian weather

Variation of the western North Pacific subtropical high (WNPSH) is an important meteorological factor for determining summertime rainfall and temperature over East Asia. Here, three major modes of summertime WNPSH variability are identified and corresponding environmental changes are investigated using cyclostationary empirical orthogonal function analysis. The leading mode exhibits a clear reinforcement of WNPSH associated with global warming. The second and third modes are characterized by intra-seasonal variation of the WNPSH intensity related to sea surface temperature variability in the central and eastern equatorial Pacific. Although WNPSH variability is regarded as a local manifestation, it reflects much wider changes in the entire North Pacific. The three modes exert seasonally and geographically distinct impacts on the East Asian weather by setting anomalous atmospheric circulation and altering the direction of moisture and heat transport. As such, the leading WNPSH modes are an important indicator of summertime weathers in countries neighboring the western North Pacific. This study also shows that extreme weather events are likely to increase as global warming intensifies.