T-mode Principal Component Analysis Research Articles

Trend of surface solar radiation over China in relation to changing synoptic patterns

A comprehensive understanding of the relationship between atmospheric circulations and variations in surface solar radiation (SSR) is important for effectively utilizing solar resources and assessing climate change impacts. Here, we identify four synoptic patterns by T-mode principal component analysis method during 1980–2020 associated with the spatio-temporal variations of SSR in China, including geopotential height anomalies of west-high-east-low (Type 1), north-high-south-low (Type 2), east-low-west-high (Type 3), and north-low-south-high (Type 4). For the whole summer, there are more days of Type 1 and Type 2, accounting for 28.74 % and 28.58 % respectively. In particular, Type 1 experiences positive anomalies in cloud cover, water vapor and significantly reduced SSR reaching the Earth’s surface. Type 2 pattern is characterized with low (high) anomalies of SSR over the Yangtze River Basin (Northeast China). And the north of the Yangtze River Basin is controlled by a northerly dry and cold airflow, leading to low cloudiness and precipitation with increased SSR reaching the ground in Type 3. Type 4 pattern exhibits a negative (positive) SSR anomalies in the Yellow River Basin (the Yangtze River Basin and Northeast China). Notably, the reduction of summer SSR in China since the 1980s is largely explained by the long-term changes of Type 2 and Type 4 synoptic patterns. These findings improve the understanding of the relationship between atmospheric circulations and SSR, and provide a scientific basis for policy planning of solar energy and dual-carbon targets in China.

Sensitivity analysis of the WRF simulated planetary boundary layer height to synoptic conditions over eastern China

Accurately representing the planetary boundary layer height (PBLH) and its thermal/dynamic structures within is essential for simulating meteorological and environmental conditions in numerical models. However, how accurately model reproduces PBL processes under diverse synoptic conditions remains under-explored. Using the Weather Research Forecasting model that configured with the widely-used YSU boundary layer scheme, the present study conducted a nearly three-year PBL simulation to examine its sensitivity to synoptic conditions in eastern China. Nine types of synoptic patterns were identified by combining T-mode principal component analysis with K-means clustering. The simulated PBLH varied significantly with synoptic patterns, with the PBLH magnitude over land following the order: quasi-summer monsoon > transition > quasi-winter monsoon. In terms of simulation biases, the model presented an overall overestimation of PBLH over most land and an underestimation over the ocean compared with two spaceborne lidars (Cloud Aerosol Transport System; Cloud Aerosol Lidar with Orthogonal Polarization) and radiosondes; The overestimation and underestimation were amplified under quasi-summer monsoon types. As the synoptic patterns were characterized by different levels of pressure, wind, temperature, and humidity. This study further explored the relationship between model biases and meteorological factors. The results showed that the simulated PBLH biases in unstable conditions were linearly dependent on thermal factors, and showed less relationship with dynamical factors. The negative PBLH biases under warm, dry, and unstable conditions can be attributed to the model's underestimation of virtual potential temperature at lowest model level. While the positive PBLH biases under cold, wet, and stable conditions were caused by warm bias of virtual potential temperature profile at lower levels.

Transport and Potential Sources Regions of Double High Pollution in Nanjing by Different Synoptic Situations

Based on the hourly concentration data of fine particulate matter （PM2.5） and ozone （O3） in Nanjing from 2015 to 2019， the synoptic situation that occurred in Nanjing， in which high PM2.5 and high O3 coexisted （hereinafter referred to as double high pollution （DHP））， was typed using T-mode principal component analysis. Additionally， the backward trajectory clustering analysis method， potential source contribution method （PSCF）， and concentration weight trajectory analysis method （CWT） were used to study the transport paths and potential source region distribution of the DHP of Nanjing by different synoptic situations. The synoptic situations favorable to the DHP in Nanjing were the control of weak low-pressure type （Type1） and high-pressure center （Type2）. Synoptic situations could have had an effect on the directional origin of the backward trajectory. In Type1， the Nanjing area was affected by two low pressures in the northeast and southwest， and the clustering trajectories of the Nanjing air mass mainly came from the eastern and western directions. The average concentrations of PM2.5 and O3 in the trajectory were 83.48 μg·m-3 and 106.85 μg·m-3， respectively. In Type 2， Nanjing and its surroundings were at the edge of the high-pressure center， and the air mass cluster trajectories mainly came from the north and east. The average concentrations of PM2.5 and O3 in the trajectory were 94.47 μg·m-3 and 92.32 μg·m-3， respectively. Most of the two types of backward trajectories belonged to short and medium-distance regional transportation， indicating that the pollution of neighboring provinces was one of the main factors affecting the DHP in Nanjing. PSCF and CWT analysis showed that the distribution of the most important potential sources of PM2.5 and O3 in Type1 and Type2 were not completely consistent， which indicates that the two pollutants did not come from the same area in the DHP.

The Synoptic Characteristics of Icing Events on Transmission Lines in Southern China

This study utilizes the ECMWF ERA5 climate reanalysis database and data from the Southern China Transmission Lines Icing Observation System and applies the T-mode principal component analysis, an objective synoptic pattern classification method, to investigate synoptic characteristics associated with transmission line icing events in southern China between 2014 and 2021. The findings reveal that Southern China’s winter synoptic conditions can be categorized into four patterns, with the predominant pattern featuring a centrally located 850 hPa high-pressure system in Inner Mongolia’s western region. This pattern facilitates the convergence of northwesterly cold air from the north and southwesterly moisture from the south over southern China, resulting in balanced conditions conducive to transmission line icing. Furthermore, during a specific icing event in Zhaoqing City, Guangdong Province, in February 2022, the atmospheric stratification exhibited a distinctive “cold–warm–cold” structure with a pronounced inversion layer, characteristic of freezing and rainy weather conditions that create the requisite environment for transmission line icing. Within the dominant icing synoptic pattern, a northwesterly airflow transports cold air from central Siberia to southern China, accompanied by two primary low-level water vapor transport pathways: one originating as a southwest low-level jet carrying moisture from the Bay of Bengal to the Chinese mainland, and the other stemming from the South China Sea. These findings provide valuable insights into the synoptic conditions contributing to transmission line icing events in the region.

Statistical indicators based on mobile phone and street maps data for risk management in small urban areas

The use of new sources of big data collected at a high-frequency rate in conjunction with administrative data is critical to developing indicators of the exposure to risks of small urban areas. Correctly accounting for the crowding of people and for their movements is crucial to mitigate the effect of natural disasters, while guaranteeing the quality of life in a “smart city” approach. We use two different types of mobile phone data to estimate people crowding and traffic intensity. We analyze the temporal dynamics of crowding and traffic using a Model-Based Functional Cluster Analysis, and their spatial dynamics using the T-mode Principal Component Analysis. Then, we propose five indicators useful for risk management in small urban areas: two composite indicators based on cutting-edge mobile phone dynamic data and three indicators based on open-source street map static data. A case study for the flood-prone area of the Mandolossa (the western outskirts of the city of Brescia, Italy) is presented. We present a multi-dimensional description of the territory based on the proposed indicators at the level of small areas defined by the Italian National Statistical Institute as “Sezioni di Censimento” and “Aree di Censimento”.

The Dependence of Gales on Relevant Meteorological Elements in One of the Hottest Regions of China, the Turpan Basin

The Turpan Basin is one of the hottest regions in China, with high fire potential. The occurrence of gales could roll over trains as well as spread and expand the fire rapidly, posing adverse effects on traffic and fire protection. Therefore, it is important to discuss the frequency and mechanism of gales in Turpan. Based on the observational data of seven stations and ERA5 reanalysis data from 2015 to 2021, this study uses the t-mode principal component analysis using the oblique rotation (T-PCA) method to explore the seasonal differences and related synoptic patterns of gales in the Turpan Basin. The synoptic circulations are divided into nine categories. In types 1, 2, 3, 5, 7 and 9, there are a high-pressure center to the west and a lower-pressure center to the south of Turpan, while in types 4, 6 and 8, there is a strong high-pressure center to the south or northeast of Turpan. When the high-pressure system is located to the west of Turpan, gales are prone to occur, while to the south or northeast, gales seem to be less likely to occur, which is closely related to synoptic patterns and terrain. To the best of our knowledge, this study pioneered the frequency and mechanism of gales in Turpan, which could facilitate gale prevention in the area.

Circulation typing with fuzzy rotated T-mode principal component analysis: methodological considerations

Circulation typing with fuzzy rotated T-mode principal component analysis: methodological considerations

Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020

The 2020 Meiyu season has received extensive attention due to its record-breaking rainfall in the Yangtze–River Huai Basin (YHRB) region of China. Although its rainfall features have been well studied on various time scales, the sub-hourly/hourly rainfall features are unknown. In this study, a wavelet analysis was applied to 1 min rainfall data from 480 national rain gauges across the YHRB, and hourly synoptic patterns during the Meiyu season were grouped using an obliquely rotated principal component analysis in T-mode (PCT). The results suggest that variances on the sub-hourly and hourly scales contributed 63.4% of the 2020 Meiyu rainfall. The hourly synoptic variations in the Meiyu season can be categorized into three major patterns: weak synoptic forcing (P1), a convergence line (P2), and a vortex (P3). The rainfalls under P1 were spatially dispersed over the YHRB and on the shortest time scale, with a 70.4% variance from sub-hourly to hourly rainfalls. P2 had a peak wavelet variance around 30 min–1 h, with rainfalls concentrated to the south of the convergent line. The rainfalls under P3 were locally distributed with a longer duration of around 1–4 h. Compared with the climate mean, hourly rainfall frequencies are indispensable to understanding the 2020 accumulated Meiyu rainfall anomaly. This research highlights the dominant role of synoptic patterns on the temporal and spatial features of the Meiyu rainfall.

Classification of ozone pollution and analysis of meteorological factors in the Yangtze River Delta

ABSTRACT Serious regional ozone (O3) pollution often plagues the Yangtze River Delta (YRD). The formation mechanism of these regional pollution events, including the meteorological and emission factors leading to these pollution events and how to affect the distribution of O3, still needs further research and exploration. In this study, we first define the standard of O3 regional pollution in the YRD, and then select 248 regional pollution cases from 2015 to 2020 according to the defined standard. For the pollution cases in pollution months (May and June), PCT (principal component analysis in T-mode) classification method is used to classify the ozone concentration distribution in YRD area. The regional distribution of the O3 concentrations in the YRD is divided into five types, and the overall type (Type 1) accounts for 15%, which is related to the control of YRD area by high-pressure center. Under the control of high pressure, the weather is sunny with the high temperature, and this weather condition is favorable for ozone generation and intercity transmission, causing extensive pollution. The double center type (Type 2) accounts for 8%. This type of YRD is controlled by the front of the high pressure (the high-pressure center is located in North China), and the weather in the middle and north is conducive to the generation and transmission of O3. Inland type (Type 3) accounts for 24%. The main body of this type of high pressure is located in Mongolia. The easterly wind in YRD area is conducive to the inland transmission of O3 precursors. The northern coastal type (Type 4) accounts for 44%. This type of YRD area is mainly controlled by the weak pressure field. The weather in the northern coastal area is sunny and the solar radiation for a long time is conducive to the formation of O3. The southern coastal type (Type 5) accounts for 10%, the solar radiation is strong in the southern region mainly under the influence of the post-offshore high pressure. This study provides new insights into the relationship between O3 pollution distribution types and atmospheric circulation in YRD area, and reveals the difference of potential meteorological impacts of different O3 pollution distribution types.

Extreme large-scale atmospheric circulation associated with the “21·7” Henan flood

From July 19 to 21, 2021, Henan, a province in northern China (NC), was affected by severe flooding (referred to hereafter as “21·7”) caused by a prolonged record-breaking extreme precipitation (EP) event. Understanding the extremes of the large-scale circulation pattern during “21·7” is essential for predicting EP events and preventing future disasters. In this study, daily atmospheric large-scale circulations over NC in the summers from 1979 to 2021 were investigated using the circulation classification method of an obliquely rotated principal component analysis in T-mode (PCT). The geopotential height at 500 hPa and 925 hPa were applied successively in classification. Among the nine summer circulation patterns at 500 hPa were found, the 3 days of “21·7” belonged to the Type 8 pattern, which had the second highest probability of EP days among all patterns. It was characterized by a southeasterly wind toward North China Plain driven by a dipole geopotential height field, with the West Pacific subtropical high (WPSH) extending far north to 30°N and low to the south near NC. Tropical cyclones (TCs) occurred on 72.5% of EP days, in which larger amounts of precipitation and a longer duration of EP days were found along the mountains in NC, as compared with other patterns. The distribution of EP events under this pattern was mainly influenced by the location of the low at 925 hPa in the dipole. The subtype 8−3 circulation, with lows in the east of Taiwan Island, included “21·7” and accounted for 1.6% of all summer days. Typhoon In-fa, together with the WPSH, gave rise to intense column integrated moisture flux convergence (IMFC) via the southeasterly wind to Henan, which occurred continuously during the 3 days of “21·7”, resulting in the largest (second largest) mean IMFC among 3 consecutive EP days under type 8 (all types) during the past 43 summers in NC. Further analysis revealed that the large-scale dynamic process could not completely explain the record-breaking EP during “21·7”, indicating possible contributions of other dynamic processed related to meso-scale convective storms.

Analysis of Typical Weather Circulation Patterns of Heavy PM2.5 Pollution and the Transport Pattern in the Yangtze River Middle Basin

The dominant transportation and accumulation patterns of heavy PM2.5 pollution events over the Yangtze River middle basin were identified based on the obliquely rotated T-mode principal component analysis (PCT) method and the daily mean surface pressure. The heavy PM2.5 pollution events over the Yangtze River middle basin during 2015-2019 were divided into four patterns, namely, PCT1:high-pressure bottom transport pattern (number of days:41 d, accounting for 55.4% of the total heavy PM2.5 pollution days), PCT2:low-pressure convergence accumulation pattern (12 d, 16.2%), PCT3:high-pressure static stability accumulation pattern (11 d, 14.9%), and PCT4:high-pressure rear transport pattern (10 d, 13.5%). Regional transport patterns (PCT1 and PCT4) accounted for 69% of the total heavy PM2.5 pollution days and were the major pattern of heavy PM2.5 pollution in the Yangtze River middle basin. PCT1 occurred most frequently among the four patterns, accompanied with strong northerly winds, which could drive the rapid transportation of pollutants from the upstream areas and cause the explosive increase in PM2.5 over the Yangtze River middle basin. The PM2.5 pollution events in the transport corridor, including Xiangyang, Jingmen, and Jingzhou, exhibited a 12-hour lag feature. Most parts of northern China were the source of PM2.5, especially in central and northern Henan and western Shandong. The PCT4 transport pattern was featured by the low-level easterly winds, and the pollution level rose quickly. The PCT2 and PCT3 were characterized by the low ground wind speed, associated with the low-level horizontal convergence and subsidence. Such synoptic conditions were favorable for the accumulation of local PM2.5 pollution, and the pollution rise rate was slower, and the duration was longer than those of other patterns.

Identification of key controlling factors of ozone pollution in Jinan, northern China over 2013–2020

Urban ozone (O3) pollution has become a prominent environmental threat to public health while the relationship between O3 formation and driving factors remains elusive, particularly for megacities in the Shandong Peninsula of China. In this study, we use intensive ambient measurements of trace gases to comprehensively investigate the magnitude of O3 pollution in Jinan city from 2013 to 2020. Further, emission inventory and OMI NO2 columns are used for probing changes in precursor emissions. Ground-level measurements indicate degraded O3 air quality afterward in 2015 and depict city-wide elevated O3 levels (higher than 140 μg/m3 in the warm season). For precursor emissions, it is found that NOx emissions have decreased more than 30% due to successful regulation efforts, which is in excellent agreement with NO2 columns from OMI. The method of objective synoptic weather pattern classification [T-Mode principal component analysis (PCT)] is adopted to distinguish the associated meteorological parameters under various synoptic patterns which govern the variability in regional O3 levels. Among identified synoptic patterns, Type 2 and Type 8 featured by low sea level pressure (SLP), high temperature, and strong ultraviolet radiation are the most prevalent synoptic patterns in spring and summer, respectively, which are prone to the occurrence of O3 exceedances. This work provides a detailed view of long-term O3 levels and the relationship between precursors and meteorological conditions in a typical densely populated city in northern China, showing implications for developing O3 mitigation strategies.

Classification of synoptic weather clusters associated with dust accumulation over southeastern areas of the Caspian Sea (Northeast Iran and Karakum desert)

• Determination of weather clusters associated with high dust-AODs over northeast Iran/Karakum desert. • Six identified weather clusters from PCA with highest frequency in spring. • The dust hotpot areas are attributed to convergence of northerly and southwesterly winds over NE Iran. • The Siberian High and Qibla wind in central Iran modulate the dust accumulation. • Changes in position, intensity and expansion of the upper-level subtropical jet modulate the dust distribution. In this study, daily-mean total and dust aerosol optical depth (TAOD, DAOD, respectively) obtained from the Monitoring Atmospheric Composition and Climate (MACC) and meteorological fields from ERA-Interim reanalysis are used to identify spatial patterns of dust accumulation over northeast Iran and Karakum Desert during 2003–2012. The most dust-affected area is defined using highest variances of DAOD by S-mode and weather clusters by T-mode principal component analysis (PCA). Six weather clusters are classified via the statistical analysis, associated with high DAOD values, with larger frequency in spring, while PC1 (41 cases) dominates in summer. The results show that changes in the intensity and expansion of the Siberian/European high-pressures in spring modulate strong northeasterlies or northwesterlies over Central Asia, which are associated with frontal dust storms over the desert areas (Aralkum, Karakum). In addition, dynamic conditions associated with the sub-tropical jet stream and the Iranian trough, and combined with convective conditions at areas of thermal lows in east Iran, create a strong southwesterly wind – called Qibla – over the Iranian Plateau. These two contrasting wind regimes converge over northeast Iran/Karakum Desert, facilitating dust accumulation over the area. In summer, northerly winds dominate over Central Asia, but the absence of Qibla flow allows them to traverse till the north coast of the Arabian Sea, where they converge with the southwest monsoon flow. The accumulation of dust over northeast Iran/Karakum is lesser than that over Pakistan and Thar desert. Furthermore, the upper-level sub-tropical jet stream moves northward in summer, with core over Turkmenistan/Uzbekistan.

Synergistic Modulations of Large-Scale Synoptic Patterns and Local-Scale Urbanization Effects on Summer Rainfall in South China

Using the ERA5 (the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts) data and the T-PCA (Principal Component Analysis in T-mode) objective classification method to classify the 850-hPa geopotential height, we summarize four conceptual models of large-scale synoptic weather types over East Asia. By combining this with the daily precipitation observation data of 36 meteorological stations in Guangdong, South China, during summer (June to August) of 2014–2018, we found that summer precipitation in Guangdong Province is closely related to the position of the northwestern Pacific subtropical high and the strong upward motion of the warm airflow over the Pearl River Delta. It is further revealed the regulation effect of different weather patterns on summer precipitation in Guangdong Province and their urban–rural differences. More specifically, both urban and rural areas have a decreasing proportion of light rainfall and an increasing proportion of heavy and torrential rainfall, which are mainly regulated by the trend of frequency changes of four different weather types: Type 1 (47.39%) and Type 2 (32.39%) days are decreasing year by year, modulating the trend of light rainfall, while Type 3 (13.26%) and Type 4 (6.96%) days are steadily increasing, dominating the trend of heavy rainfall. In addition, it was further found that the frequency of light rainfall is decreasing more significantly in cities compared to that in rural areas, while the proportion of heavy and stormy rainfall is increasing more significantly, which is closely related to the effects of rapid urbanization.

Association between the Biophysical Environment in Coastal South China Sea and Large-Scale Synoptic Circulation Patterns: The Role of the Northwest Pacific Subtropical High and Typhoons

Synoptic weather conditions can modulate short-term variations in the marine biophysical environment. However, the impact of large-scale synoptic circulation patterns (LSCPs) on variations in chlorophyll-a (chl-a) and sea surface temperature (SST) in the South China Sea (SCS) remains unclear. Using a T-mode principal component analysis method, four types of LSCP related to the Northwest Pacific subtropical high are objectively identified over the SCS for the summers of 2015–2018. Type 1 exhibits a lower chl-a concentration of <0.3 mg m−3 offshore of southern Vietnam with respect to the other three types. For Type 2, the high chl-a concentration zone (>0.3 mg m−3) along the coast of Guangdong exhibits the widest areas of coverage. The offshore chl-a bloom jet (>0.3 mg m−3) formed in southern Vietnam is the most obvious under Type 3. Under Type 4, the high chl-a concentration zone along the coast of Guangdong is the narrowest, while the chl-a concentration in the middle of the SCS is the lowest (<0.1 mg m−3). These type differences are mostly caused by the various monsoon circulations, local ocean mesoscale processes and resultant differences in localized precipitation, wind vectors, photosynthetically active radiation and SST. In particular, precipitation over land helps to transport nutrients from the land to the shore, which is conducive to the increase of chl-a. However, precipitation over ocean will dilute the upper seawater and reduce chl-a. Typhoons pump the deeper seawater with nutrients to the surface, and therefore make a positive contribution to chl-a in most offshore areas; however, they also disturb shallower water and hinder the growth of phytoplankton, making a negative contribution near the coast of Guangdong. In general, our findings will provide a better understanding of wind pump impact: the responses of marine biophysical environments to LSCPs.

Characterization of Urban Heat Islands Using City Lights: Insights from MODIS and VIIRS DNB Observations

An urban heat island (UHI) is a phenomenon whereby the temperature in an urban area is significantly warmer than it a rural area. To further advance the characterization and understanding of UHIs within urban areas, nighttime light measured by the Day/Night Band (DNB) onboard the Visible Infrared Imaging Radiometer Suite (VIIRS) and the land surface temperature (LST) data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) combined with principal component analysis (PCA) are used here. Beijing (highly developed) and Pyongyang (less developed) are selected as the two case studies. Linear correlation analysis is first used, with higher correlations being found between DNB and LST data at nighttime than between population and LST data for both cities, although none of the correlation coefficients are particularly high because of noise. Principal component analysis (PCA), a method that can remove random noise, is used to extract more useful information. Two types of PCA are conducted, focusing on spatial (S) and temporal (T) patterns. The results of the S-mode PCA reveal that the typical temporal variation is a seasonal cycle for both LST and DNB data in Beijing and Pyongyang. Furthermore, there are monthly cycles for DNB data related to the moon phase in two cities. The T-mode PCA results show important spatial information, while the spatial pattern of the first mode explains over 50% of the variation. This study is among the first to demonstrate the advantages of using urban light to study the spatial variation of urban heat, especially for nighttime urban temperatures measured from space, at the street and neighborhood scales.

Large-scale synoptic drivers of co-occurring summertime ozone and PM<sub>2.5</sub> pollution in eastern China

Abstract. Surface ozone (O3) pollution during summer (June–August) over eastern China has become more severe in recent years, resulting in a co-occurrence of surface O3 and PM2.5 (particulate matter with aerodynamic diameters ≤ 2.5 µm in the air) pollution. However, the mechanisms regarding how the synoptic weather pattern (SWP) might influence this compound pollution remain unclear. In this study, we applied the T-mode principal component analysis (T-PCA) method to objectively classify the occurrence of four SWPs over eastern China, based on the geopotential heights at 500 hPa during summer (2015–2018). These four SWPs over eastern China were closely related to the western Pacific subtropical high (WPSH), exhibiting significant intra-seasonal and interannual variations. Based on ground-level air quality observations, remarkable spatial and temporal disparities of surface O3 and PM2.5 pollution were also found under the four SWPs. In particular, there were two SWPs that were sensitive to compound pollution (Type 1 and Type 2). Type 1 was characterized by a stable WPSH ridge with its axis at about 22∘ N and the rain belt located south of the Yangtze River Delta (YRD); Type 2 also exhibited WPSH dominance (ridge axis at ∼ 25∘ N) but with the rain belt (over the YRD) at a higher latitude compared to Type 1. In general, SWPs have played an important role as driving factors of surface O3–PM2.5 compound pollution in a regional context. Our findings demonstrate the important role played by SWPs in driving regional surface O3–PM2.5 compound pollution, in addition to the large quantities of emissions, and may also provide insights into the regional co-occurring high levels of both PM2.5 and O3 via the effects of certain meteorological factors.

Modulations of Synoptic Weather Patterns on Warm-Sector Heavy Rainfall in South China: Insights From High-Density Observations With Principal Component Analysis

Based on hourly high-density precipitation data in Guangdong Province, China, 134 warm-sector heavy rainfall (WSHR) events were selected from 2016 to 2018. The synoptic weather patterns of these WSHR events were objectively classified using T-mode principal component analysis. Six WSHR weather patterns were identified, as follows: Type 1-southwest (T1-SW), Type 2-southeast (T2-SE), Type 3-coastal jets I (T3-CJI), Type 4-coastal jets II (T4-CJ II), Type 5-western low vortex (T5-WL), and Type 6-high-pressure (T6-HP). Three high-occurrence WSHR centers were finally extracted: the areas of Yangjiang and Shanwei, and the urban agglomeration of Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Compared with the other five patterns, T6-HP is a newly identified WSHR weather pattern, which is related to a local/small-scale weather system in the context of anomalous northward movement of the western Pacific subtropical high. Notably, the precipitation area of the T6-HP type of WSHR event is smaller, which can only be captured by high-density observations. In addition, the occurrence locations of six large-scale extreme precipitation events were closely associated with the urban agglomerations in GBA, implying that urbanization plays an important role in extreme magnitudes of large-scale WSHR events and their occurrence centers.

Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran

Extraordinary dry conditions on the desert and arid areas in Iran, along with strong influences from surrounding dust sources in the Middle East and Arabia, have exposed the country to substantial amounts of dust aerosols with serious impacts on environment, health and socio-economic aspects. Considering this threat, daily aerosol optical depth (AOD) data over Iran obtained from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis during 2003–2012 were used to analyze the spatial and temporal patterns of total AOD (TAOD) and dust AOD (DAOD). This study identifies the areas mostly affected by TAOD and DAOD in terms of daily average values and the areas associated with distinct temporal patterns, utilizing S-mode and T-mode principal component analysis (PCA). The analysis reveals six distinct sub-regions in southeast, west-northwest, northeast, east, central and southwest of Iran, which are among the major centers influenced by TAOD and DAOD extremes. The main findings of the T-mode results, consistent with TAOD and DAOD S-mode patterns, are (i) the maximum dust loading over the eastern, southeastern and southwestern subregions in March and May, (ii) dust loading with peaks in November over the eastern and northeastern sub-regions; (iii) maximum number of dusty days in July and August over southwest, (iv) maximum dust in July over southeastern and Central Iran, (v) a dust pattern with identical extent over the west and northwest sub-region in March and October and, (vi) a prevailing dust loading over the dry areas (Lut desert, Sistan plain and southwest edge of the territory) in October. The spatiotemporal evolution of dust is a function of the growth and expansion of dust extremes originated from various sources in Iran and the Middle East. The PCA methodology, through simplification of aerosol distribution to simpler structures, was also incorporated to provide a geographical interpretation of the highly sensitive territory of Iran.

The impact of synoptic patterns on summertime ozone pollution in the North China Plain

Surface ozone pollution is a challenging environmental issue in most parts of China. In particular, the North China Plain (NCP) region suffers from the severest ozone pollution throughout the country. In addition to the emission of precursors, ozone concentration is closely related to meteorological conditions resulting from regional atmospheric circulation. In this study, we investigate the relationship between synoptic patterns and summertime ozone pollution in the NCP using the objective principal component analysis in T-mode (T-PCA) classification method. Four dominant synoptic patterns are identified during the summers of 2014–2018. The heaviest ozone pollution is found to be associated with a high pressure anomaly over the Northwest Pacific and a distinct low pressure center in Northeast China. The southwesterly wind surrounding the low pressure center brings dry, warm air from inland South China, resulting in a high temperature, low humidity environment in the NCP, which favors the chemical formation of surface ozone. Locally, this type is associated with a moderate planetary boundary layer height (PBLH) of ~860 m and a stronger warm anomaly within the boundary layer than the upper level. We also notice a non-linear relationship between surface ozone concentration and the PBLH, i.e., ozone concentration first increases with PBLH till ~0.9 km, and then remains stable. This initial increase may relate to enhanced mixing with upper levels where ozone concentration is typically higher than that near the surface. However, when PBLH further increases, this downward mixing effect is balanced with the stronger upward turbulent mixing so that surface ozone shows little change. The synoptic patterns identified here, however, is unlikely responsible for the observed increasing trend in ozone concentration over the NCP region. Our study sheds light on the meteorological contribution to surface ozone pollution in North China and provides a reference for the pollution control and prediction.