Empirical Orthogonal Function Method Research Articles

Reasons for the Weakening of Tropical Depressions in the South China Sea

AbstractThe frequency and location distribution of tropical depressions (TDs) from 1979 to 2017 in the South China Sea (SCS) are statistically analyzed based on the best track data of tropical cyclones (TCs) from the Shanghai Typhoon Institute, China Meteorological Administration (CMA-STI). ECMWF interim reanalysis data (ERA-Interim) are used to investigate the reasons for the weakening of TDs in this study. The results show that there are 4.8 TDs formed in the SCS per year, and these TDs can be separated into 3.2 developing cases (DTDs) and 1.6 nondeveloping cases (NTDs) according to whether they intensify into tropical storms. Further objective classification by the multivariable-time empirical orthogonal function (MVT-EOF) method finds that the weakening cases in the positive-PC1 (the first principle component) mode occur in May–September, with the reason for weakening being a shortage of moisture. The decrease of westerly wind south of the NTDs reduces the water vapor transportation from the Indian Ocean. Binary TCs in the northwestern Pacific acquire water vapor from the eastern boundary of the SCS NTDs. Meanwhile, the weak high-level divergence and low-level convergence are not enough for the accumulation of local moisture and maintaining local convections inside the NTDs. The weakening cases in negative-PC1 mode occur in October–December with the reason for weakening being the invasion of cold air from the north. Strong cold air advection in the lower troposphere increases the vertical wind shear in front of the NTDs, and sharply reduce sensible and latent heat flux as well. Seasonal dependence exists in the causes of the SCS NTDs weakening.

Synoptic weather patterns for large wildfires in the northwestern United States—a climatological analysis using three classification methods

Wildfire regimes respond to atmospheric variability on multiple time scales from interannual variations of drought to daily fluctuations of humidity and wind. Synoptic weather patterns effectively link both short- and long-term atmospheric variability, and thus, understanding fire-prone synoptic patterns is an integral part of fire management programs. Different analysis procedures of varying complexity have been used to identify the most common synoptic weather patterns conducive to wildfires. In this study, we examine the utility of three synoptic-pattern classification methodologies, namely Composite, Empirical Orthogonal Function (EOF), and Self Organizing Map (SOM). We focused on the synoptic weather patterns associated with 203 wildfires that burned 50,000 acres (20,250 ha) or more and 80 wildfires that burned 100,000 acres (40,500 ha) or more in the Northwestern United States between 1984 and 2014. The basic 500-hPa geopotential height patterns identified by the three analysis methods were found to be similar for the two fire-size categories, but the strengths of the geopotential height anomalies were larger for the larger size fires. All three methods were able to consistently identify the dominant pattern with only small differences in strength and position of the anomalies, but the EOF and SOM methods yielded other less dominant, but still important, patterns. Particularly, the SOM method captured transitional synoptic patterns that may account for 20–30% of these large wildfires.

Spatial-temporal characteristics and influencing factors of relative humidity in arid region of Northwest China during 1966–2017

Playing an important role in global warming and plant growth, relative humidity (RH) has profound impacts on production and living, and can be used as an integrated indicator for evaluating the wet-dry conditions in the arid and semi-arid area. However, information on the spatial-temporal variation and the influencing factors of RH in these regions is still limited. This study attempted to use daily meteorological data during 1966–2017 to reveal the spatial-temporal characteristics of RH in the arid region of Northwest China through rotated empirical orthogonal function and statistical analysis method, and the path analysis was used to clarify the impact of temperature (T), precipitation (P), actual evapotranspiration (ETa), wind speed (W) and sunshine duration (S) on RH. The results demonstrated that climatic conditions in North Xinjiang (NXJ) was more humid than those in Hexi Corridor (HXC) and South Xinjiang (SXJ). RH had a less significant downtrend in NXJ than that in HXC, but an increasingly rising trend was observed in SXJ during the last five decades, implying that HXC and NXJ were under the process of droughts, while SXJ was getting wetter. There was a turning point for the trend of RH in Xinjiang, which occurred in 2000. Path analysis indicated that RH was negatively correlated to T, ETa, W and S, but it increased with increase of P. S, T and W had the greatest direct effects on RH in HXC, NXJ and SXJ, respectively. ETa was the factor which had the greatest indirect effect on RH in HXC and NXJ, while T was the dominant factor in SXJ.

Empirical orthogonal function analysis and modeling of global ionospheric spherical harmonic coefficients

We developed a global empirical model for computing spherical harmonic (SH) coefficients based on the empirical orthogonal function (EOF) method and periodic functions by utilizing global ionospheric SH coefficients data provided by Center for Orbit Determination in Europe (CODE) during the years 2005–2016. Results show that the first four-order base functions and corresponding associated coefficients can represent 97.15% of the basic characteristics of the original data. The first four-order associated coefficients have noticeable periodic variations, and the correlation between these coefficients and the solar activity intensity is high. By fitting the associated coefficients with the periodic function that takes into account the influence of solar activity, it is possible to establish an EOF model to characterize the variations of the ionospheric SH coefficients with few model parameters and further calculate the global vertical total electron content (VTEC). Relative to the existing global VTEC EOF models, this EOF method can achieve high-accuracy modeling of global VTEC with a smaller number of model coefficients. By comparing the SH coefficients and the global VTEC between the EOF model and CODE, results demonstrate that the EOF model can achieve high accuracy and reliability under different solar activities. The difference between the EOF model and CODE is basically at the same level as that between the individual ionospheric analysis centers and CODE. In the extreme event of magnetic storms, the EOF model can also present higher accuracy than the international reference ionosphere (IRI) model.

RESPONS SUHU PERMUKAAN LAUT DAN KLOROFIL-A TERHADAP KEJADIAN ENSO DAN IODM DI WILAYAH INDO-PASIFIK TROPIS

Fenomena anomali laut-atmosfer antar-tahunan dari El Nino Southern Oscillation (ENSO) dan Indian Ocean Dipole Mode (IODM) di wilayah Indo-Pasifik Tropis memberikan dampak pada ekosistem laut, hidrologi dan variabilitas iklim. Penelitian ini bertujuan untuk menganalisis pola spasial dan variabilitas temporal suhu permukaan laut (SPL) dan klorofil-a permukaan (Chl-a) terkait dengan ENSO dan IODM di Indo-Pasifik Tropis. Data deret waktu bulanan dari tahun 1980-2017 (37 tahun) diperoleh dari pusat data global, dan dianalisis menggunakan metode empirical orthogonal function (EOF). Hasil penelitian menunjukkan nilai tiga terbesar pertama dari SPL (Chl-a) menjelaskan 81,7% (76%) dari total explained variance. Struktur spasial SPL mode-1 (56%) membentuk seperti dua kutub asimetris antara timur dan barat Pasifik Tropis dengan pola yang berbeda di lepas Pantai Peru. Pola ini diduga berhubungan dengan tahun normal atau La Nina. Selanjutnya, kondisi EL Nino dan IODM diduga tergambarkan oleh SPL mode-2 (19%), dengan fase negatif dominan di atas ekuator Pasifik dan menghilangnya area upwelling di lepas Pantai Peru.

Response of the Asian summer Monsoons to a high-latitude thermal forcing: mechanisms and nonlinearities

This study investigates mechanisms and nonlinearities in the response of the Asian Summer Monsoons (ASM) to high-latitude thermal forcings of different amplitudes. Using a suite of runs carried out with an intermediate-complexity atmospheric general circulation model, we find that the imposed forcings produce a strong precipitation response over the eastern ASM but a rather weak response over the southern ASM. The forcing also causes a precipitation dipole with wet conditions over the eastern Tibetan Plateau (TP) and dry conditions over the Bay of Bengal (BoB) and southeast Asia. A moderate increase of precipitation along the southern margin of the TP is also produced. Simulations designed to isolate the causal mechanisms show that thermodynamic interactions involving the tropical surface oceans are far less important than the water-vapour feedback for the transmission of information from the high-latitudes to the ASM. Additionally, we assess the nonlinearity of the ASM precipitation response to the forcing amplitude using a novel application of the empirical orthogonal function method. The response can be decomposed in two overlapping patterns. The first pattern represents a precipitation dipole with wet conditions over the eastern TP and dry conditions over BoB, which linearly increases with forcing amplitude becoming quasi-stationary for large forcing amplitudes (i.e. amplitudes leading to Arctic temperature anomalies larger than 10 °C). The second pattern is associated with increased precipitation over the southeastern TP and is nonlinearly dependent on forcing, being most important for intermediate forcing amplitudes (i.e. amplitudes leading to Arctic temperature anomalies between 5 and 10 °C).

The response of surface chlorophyll to mesoscale eddies generated in the eastern South China Sea

This study investigates the response of surface chlorophyll (CHL) to mesoscale eddies generated in the eastern South China Sea (ESCS) during their lifecycles based on global eddy dataset and chlorophyll data from January 2003 to December 2016. The results show that the responses of CHL anomalies to cyclones are stronger than anticyclones generated in the Luzon Strait (LS) and in the area off northwest Luzon Island (NWLI). CHL anomalies are higher when cyclones disappear than when they are generated in the LS and in the NWLI. Furthermore, impacts of different eddy dynamic mechanisms (eddy advection, eddy trapping, eddy pumping and eddy-induced Ekman pumping) on CHL anomalies are quantified during eddy lifecycles based on empirical orthogonal function (EOF) method. Our results reveal that CHL anomalies in cyclones generated in the NWLI are affected by eddy pumping and its strengthening effect enhanced until the middle stage of their lifecycles. CHL anomalies in cyclones generated in the LS are modulated by eddy advection and linear Ekman pumping. CHL anomalies in anticyclones generated in the LS are jointly induced by eddy trapping, nonlinear Ekman pumping and eddy pumping. This study helps us attribute surface CHL to specific mechanisms and understand the differences in the response of surface CHL to mesoscale eddies generated in the ESCS during their lifecycles, and thus gains a deeper understanding of the role of mesoscale eddies in regulating the marine primary production.

Application of DINCAE to Reconstruct the Gaps in Chlorophyll-a Satellite Observations in the South China Sea and West Philippine Sea

The Data Interpolating Empirical Orthogonal Functions (DINEOF) method has demonstrated usability and accuracy for filling spatial gaps in remote sensing datasets. In this study, we conducted the reconstruction of the chlorophyll-a concentration (Chl-a) data using a convolutional neural networks model called Data-Interpolating Convolutional Auto-Encoder (DINCAE), and we compared its performance with that of DINEOF. Furthermore, the cloud-free sea surface temperature (SST) was used as a phytoplankton dynamics predictor for the Chl-a reconstruction. Finally, four reconstruction schemes were implemented: DINCAE (Chl-a only), DINCAE (Chl-a and SST), DINEOF (Chl-a only), and DINEOF (Chl-a and SST), denoted rec1, rec2, rec3, and rec4 respectively. To quantitatively evaluate the accuracy of these reconstruction schemes, both the cross-validation and in situ data were used. The study domain was chosen to be the Northern South China Sea (SCS) and West Philippine Sea (WPS), bounded by 115–125°E and 16–24°N to test the model performance for the reconstruction of Chl-a under different Chl-a controlling mechanisms. The in situ validation showed that rec1 performs best among the four reconstruction schemes, and that adding SST into the Chl-a reconstruction cannot improve the reconstruction results. However, for cross validation, adding SST can slightly improve spatial distributions of the root mean square error (RMSE) between the reconstructed data and the original data, especially over the SCS continental shelf. Furthermore, the potential of DINCAE prediction is confirmed in this paper; thus, the trained DINCAE model can be re-applied to reconstruct other missing data, and more importantly, it can also be re-trained using the reconstructed data, thereby further improving reconstruction results. Another consideration is efficiency; with similar reconstruction conditions, DINCAE is 5–10 times faster than DINEOF.

Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen

The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.

Changes in the hydrodynamic characteristics of the upper layer of the South China Sea during the period of super typhoon Rammasun (2014)

Severe typhoon Rammasun (2014) was strengthened (super typhoon) in the east of the Leizhou Peninsula before moving into the Beibu Gulf. This study used the empirical orthogonal function (EOF) method to analyze the spatiotemporal variations in the sea surface wind (SSW), surface level anomaly (SLA), sea surface temperature (SST), mixed layer depth (MLD) and precipitation of the SCS. The study found that this typhoon had a significant influence on the SSW, SLA, SST, MLD and precipitation changes. During the typhoon Rammasun, the spatial distribution of precipitation showed obvious ‘left-hand-side intensification’ relative to the typhoon track. However, the SST decreased rapidly, and cooling showed a clear ‘right-hand-side intensification’, and two cyclonic eddies in the southwestward were observed from the mode of EOF-1 of the SLA. The spatiotemporal variations of SST, MLD, SLA, SSW and precipitation during the period of super typhoon Rammasun were excellently reflected by the EOF method. The variabilities of SST, MLD, SLA, SSW and precipitation in the SCS during the typhoon period and the relationship between the variabilities were further analyzed.

Detection of urbanization effect on the climate change in Liaoning Province based on empirical orthogonal function methods

Detection of urbanization effect on the climate change in Liaoning Province based on empirical orthogonal function methods

Variability of ITF front at 115°E in the Eastern Indian Ocean: from 15-years Gridded CTD Argo Float Data

This study aims to investigate a depth-latitude spatial and temporal variability of ITF front at 115°E, using 15-years (2004–2018) of monthly gridded CTD Argo float dataset in the Indo–Australia Basin. The Empirical Orthogonal Function method was performed to analysis these time-series data. It is shown that mean meridional extent of ITF front is established between 14°S and 10°S. The ITF front can be described by the first five modes of potential temperature and salinity EOF’s, which accounted for 88.6% and 80.7% of the total variance, respectively. The first EOF mode (67.9%) of depth-latitude temperature reveals spatial pattern which is out-of-phase between near-surface layer (<100 m) and thermocline layer, for example, during the northwest monsoon period, warmer and saltier water in the upper-layer and colder and fresher thermocline water are frequently observed, which differ to those observed during the southeast monsoon period. EOF principal components of temperature and salinity exhibit strong annual variation, followed by intraseasonal and interannual scales. On inter-annual scales, fluctuation of temperature and salinity is well correlated with ENSO and IODM, as previously expected.

Spatio-Temporal Patterns of Rainfall Variability for Wet Season over Togo in West Africa

Climate change is affecting rainfall variability. This paper investigated the June-September (JJAS) rainfall variability using reanalyzed and observed da-tasets from 1976 to 2015 in Togo. The rotated empirical orthogonal function (REOF) method was used to get the distribution patterns of JJAS rainfall. The Mann-Kendall (MK) statistic was also used to detect temporal trend of the ro-tated principal component time series (RPCs) that represent the modes of posi-tive loadings. The REOF method has revealed four significant patterns that ex-plained 65.1% of the total variance; the first, the second and the fourth REOF modes exhibit mainly positive loadings, whereas the third exhibits negative loadings. The first mode (REOF1) represents mainly the southern part of Togo; the second mode (REOF2) represents the northern part, the third mode (REOF3) represents the western part and the fourth (REOF4) represents the north-eastern part of Togo. The Mann-Kendall test has revealed an increasing and significant trend of rainfall in the northern region of Togo. In contrast, the trends were not significant in the southern and north-eastern parts of the coun-try. These results form a basis on which adaptation strategies may be taken in this region with high rainfall variability.

Monitoring the spatiotemporal terrestrial water storage changes in the Yarlung Zangbo River Basin by applying the P-LSA and EOF methods to GRACE data

The Yarlung Zangbo River Basin is a regulator of water vapor changes in China and even Asia. To avoid the shortcomings of traditional water resource monitoring methods, this study used Gravity Recovery and Climate Experiment (GRACE) data to monitor the terrestrial water storage anomaly (TWSA) in this river from 2002 to 2015 with the help of the polynomial-least squares approach (P-LSA) and the empirical orthogonal function (EOF). The obtained TWSA was compared with hydrometeorological data from several sources to discuss the applicability, uniqueness and response relationship. The results showed that (1) the combination of P-LSA and EOF had strong applicability to explore the TWSA in the study area, with R2 = 0.75 and 0.80, respectively, and could indirectly reflect dry and wet conditions in southwestern China. (2) The TWSA revealed significant cyclical and seasonal fluctuations of approximately 12 months and increased from upstream to downstream and from north to south, which was discussed for the first time in the research area. (3) The EOF method can effectively identify the TWSA principal component and structure (EOF1 contribution = 91.08%) by removing noise and redundancy, which is beneficial for revealing the laws essential for TWSA changes. (4) The TWSA in the studied watershed was unique (i.e., the clearest periodic changes with the best fitting effect (R = 0.90); peak, low and peak-low difference values that were 1.82, 1.19 and 1.52 times larger than those of the 8 other rivers; and the largest downward trend of 4.13 mm·a−1). (5) Rainfall was the decisive factor influencing the TWSA, with correlation coefficients (R) >0.60. This study enhances our overall understanding of the TWSA in this plateau watershed and provides a scientific basis for optimal water resource management.

Evaluating climate and irrigation effects on spatiotemporal variabilities of regional groundwater in an arid area using EOFs

Groundwater level is an important variable in the evolution process of ecological environment systems. However, spatiotemporal changes in groundwater level are attributed to the comprehensive influence of natural and anthropogenic activities. Therefore, understanding the major driving forces to changes in spatiotemporal patterns of groundwater level is essential for sustainable utilization of regional groundwater and sustaining healthy ecosystems, especially in arid areas. In this study, based on monthly observations of depth to groundwater table (DTGT) from 67 monitoring wells during 2001–2010 in the Yichang Irrigation Sub-district (YISD) of the Hetao Irrigation District (HID), which is located in Northwest China with an arid climate, the empirical orthogonal function (EOF) method was used to analyze the spatiotemporal variations of DTGT and the major driving forces. The EOF analysis results showed that the first two spatial structures (EOF1 and EOF2) of DTGT were found in this region, which explained over 65% and 8% of the spatial variation of DTGT, respectively. Meteorological factors (evaporation and temperature) were the first leading factors to drive the temporal pattern of the first expansion coefficient (EC1) corresponding to the EOF1 at intra-annual scale as well as inter-annual scale. Particularly, temperature controlled the EC1 pattern during the freezing period from December to March. Soil texture was shown to have good correlations with the spatial patterns of DTGT, although these correlations diminished when the depth exceeded 250 cm. This study provides strong evidence that the principal spatiotemporal variations of groundwater can be effectively extracted by the EOF method, thereby obtaining integrated views of the relationships between the groundwater system and meteorological and anthropogenic factors.

Analysis for Spatio-Temporal Variation Characteristics of Droughts in Different Climatic Regions of the Mongolian Plateau Based on SPEI

Continuous climate warming in the last few decades has led to global climate anomalies, resulting in frequent drought events in arid/semiarid regions with fragile and sensitive ecological environment. The Mongolian Plateau (MP) is located at the mid-latitude arid/semiarid climate region, which is deemed as the most sensitive region in response to global climate change. In order to understand the spatiotemporal characteristics of droughts in Mongolian Plateau under changing climate, we divided the study area into three climatic regions via Köppen climate classification. Then, the seasonal and annual drought trends were analyzed by standardized precipitation evaporation index (SPEI), which is a function of monthly mean temperatures, highest temperatures, lowest temperatures and precipitations, collected from the 184 meteorological stations from 1980 to 2015. Mann–Kendall (MK) test was employed to detect if there is an abrupt change of annual drought, while the empirical orthogonal function method (EOF) was adopted to investigate the spatiotemporal characteristics of droughts across the Mongolian Plateau. Results from MK test illustrated that the SPEI-12 exhibited statistically significant downward trends (a &lt; 0.05) for all three climatic regions of the Mongolian Plateau. EOF spatial analysis indicated that Region III experienced the most severe drought from 1980 to 2015. During the 35 years period, an abrupt change of drought was detected in 1999. Before year 1999, the climate was relatively humid. However, the entire region became more arid after year 1999, reflected by remarkably increased frequency and intensity of drought. SPEI-3 revealed the trend of drought at seasonal scale. We found that drought became more severe in spring, summer, and fall seasons for the entire MP. However, winter became more humid. Different climate regions exhibited quite different drought seasonality: Region I experienced a severe arid trend in summer and fall. For Region II and III, summer became more arid. All three regions became more humid in winter season, especially for Region I, with the Sen’s slope of 0.0241/a.

A Novel Identification of the Polar/Eurasia Pattern and Its Weather Impact in May

The Polar/Eurasia (POL) pattern was previously identified based on the empirical orthogonal function method and monthly mean data, in which the positive and negative phases are anti-symmetric in spatial distribution. This paper identifies the positive (POL+) and negative (POL−) phases of the POL pattern through applying a novel approach, i.e., self-organizing maps, to daily 500-hPa geopotential height fields in May over 1948–2017. The POL+, POL1−, and POL2− patterns defined by this method represent actual physical modes. The POL+ pattern features a wave train from the northeastern Atlantic/northern Europe via the subarctic regions of Eurasia to Lake Baikal. The POL1− pattern is characterized by a planetary-scale dipole pattern with a positive anomaly band over subarctic Eurasia and a negative anomaly band from central Asia to the Sea of Okhotsk. The anomaly centers of the POL2− pattern are basically anti-symmetrical tothose of the POL+ pattern. The POL+ pattern increases the blocking frequency over the northeastern Atlantic/northern Europe and northeastern Asia, where high-frequency transient eddies are highly recurrent in the north. Accordingly, precipitation increases apparently in the subarctic Asian continent and western Siberia, and decreases around Europe and Lake Baikal. A mimic wave train is also observed in the surface air temperature anomaly field. During the POL1− period, the blocking frequency is abnormally high over Eurasia, whereas high-frequency transient eddies are apparently suppressed over northern Eurasia. Correspondingly, significant precipitation deficits are observed in northern Eurasia. The POL1− pattern also causes a remarkable temperature increase in the subarctic seas of Eurasia and a considerable temperature drop in the midlatitude Asian continent. As the POL2− pattern prevails, the blocking frequency decreases over the North Atlantic/Europe but strengthens over the Asian continent. The POL2− pattern also causes wavelike anomalies of precipitation and surface air temperature over northern Eurasia.

Reconstruction of Large-Scale Sea Surface Temperature and Salinity Fields Using Sub-Regional EOF Patterns From Models

A method for reconstruction of gridded fields of sea surface variables from time-dependent observations, using sub-regional EOF (Empirical Orthogonal Functions) patterns from models, is presented and tested. Covariance fields, calculated from the model results over long enough time span, are used to find EOF modes. The gravest “observational” amplitudes and their first temporal derivatives are determined from the least-square minimization of fitting errors in relation to the observed values. The field is reconstructed by superposition of continuous model-based mode patterns multiplied by observational amplitudes that meet adopted statistical limits. If the observational amplitude exceeds the limits, gridded fields for this and higher modes are not produced. We applied the method in the northeastern Baltic over the model time series 2010-2015. Daily averages of sea surface temperature (SST) and salinity (SSS) from the high-resolution (grid step 0.5 nautical miles) sub-regional HBM model were spatially averaged over bins of 5x5 nautical miles. Three first modes cover 99% of variance of temperature and 61.4% of salinity. As shown by experiments with pseudo-observations (model values at these points reconstructed to the model grid and then compared with the original model data), reconstruction performance depends on the configuration of the observation points in the model domain. Still, a few first modes usually produce acceptable results. When removing the SST seasonal cycle prior to EOF analysis, spatial patterns of leading modes remained practically unchanged, share of variance of the three first modes was reduced to 88,6% and reconstruction errors were reduced by about 25%. Sufficient spatial data coverage of the larger basin with ship-born observations usually takes quite long time – of the order of month; therefore, time correction of the amplitudes using the found temporal derivatives improves the accuracy of reconstruction. The method is compared with the Optimal Interpolation (OI) by using the pseudo-observations. Results show that, for SST reconstruction, the OI method is significantly worse than the EOF method. For SSS, OI is slightly better than EOF. The superiority of EOF is that the remote correlation patterns can be used in the reconstruction, which is important when the observations are sparse.

Shoreline evolution in an embayed beach adjacent to tidal inlet: The impact of anthropogenic activities

Embayed beaches are widely distributed around the world. Their shoreline evolution is controlled primarily by the upstream headland and prevailing wave conditions. Tidal inlets are also ubiquitous in sandy coasts. They are quite dynamic and act as a sediment source or sink, depending on the sediment transport pattern and budget. An embayed beach may develop downstream of a tidal inlet if a protruding headland is formed at the inlet, owing to either natural processes or human construction. In this study, Gaolong Bay, located downstream of a tidal inlet (Qinglan Inlet) in Wenchang City, Hainan Island, China, is used as an example to examine the effects of an upstream tidal inlet on the evolution of an embayed beach. Emphasis is placed on the impact of anthropogenic activities, such as landfilling and jetty construction. Historical remote sensing data were collected, and the evolution of the shoreline from 1998 to 2018 was analyzed. The shoreline change pattern in Gaolong Bay was identified with the empirical orthogonal function (EOF) method, and the mechanisms behind these changes were explored with a coupled current–wave–sediment transport modeling system. Our results indicate that the construction of an artificial peninsula and a jetty beside the inlet channel dramatically changed the evolution of the Gaolong Bay shoreline. Defying the classical expectation of shoreline retreat downdrift of a tidal inlet, a clockwise shoreline rotation was prevalent in Gaolong Bay, with the shadow zone accreting and the distal zone retreating, along with an overall shoreline propagation (translation). The static equilibrium shoreline planform model (model of equilibrium of bay beaches [MEPBAY]) was further used to predict the future evolution of the shoreline. This study demonstrates that an embayed beach downdrift of a tidal inlet can exhibit a complex response to human interventions at the inlet and highlights the necessity of considering adjacent shoreline changes when assessing the impact of inlet stabilization.

Characteristics of Ozone Pollution, Regional Distribution and Causes during 2014–2018 in Shandong Province, East China

The summer ozone pollution of Shandong province has become a severe problem in the period 2014–2018. Affected by the monsoon climate, the monthly average ozone concentrations in most areas were unimodal, with peaks in June, whereas in coastal areas the concentrations were bimodal, with the highest peak in May and the second highest peak in September. Using the empirical orthogonal function method, three main spatial distribution patterns were found. The most important pattern proved the influences of solar radiation, temperature, and industrial structure on ozone. Spatial clustering analysis of the ozone concentration showed Shandong divided into five units, including Peninsula Coastal area (PC), Lunan inland area (LN), Western Bohai area (WB), Luxi plain area (LX), and Luzhong mountain area (LZ). Influenced by air temperature and local circulation, coastal cities had lower daytime and higher nighttime ozone concentrations than inland. Correlation analysis suggested that ozone concentrations were significantly positively correlated with solar radiation. The VOCs from industries or other sources (e.g., traffic emission, petroleum processing, and chemical industries) had high positive correlations with ozone concentrations, whereas NOx emissions had significantly negatively correlation. This study provides a comprehensive understanding of ozone pollution and theoretical reference for regional management of ozone pollution in Shandong province.