{"title":"An overview of spatiotemporal variation, chemical characteristics, source apportionment, and potential influential factors of PM2.5 in coastal regions and at islands of East Asia","authors":"Po-Hsuan Yen, Wen-Hsi Cheng, Yu-Lun Tseng, Chung-Shin Yuan, Kuo-Cheng Lo, Nian-Jie Li, Jia-Yi Zhao","doi":"10.1016/j.atmosres.2026.108759","DOIUrl":"https://doi.org/10.1016/j.atmosres.2026.108759","url":null,"abstract":"","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"46 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145962373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-08DOI: 10.1016/j.atmosres.2026.108761
Weihao Wang , Xuyang Ge , Melinda Peng
The processes on Tropical cyclones' (TCs) looping tracks (LTs) near an isolated terrain are investigated with numerical simulations. The large-scale environmental fields of observed TCs approaching Taiwan Island with and without LTs are compared. LT cases exhibit a monsoon gyre (MG)-like circulation on the southeast side of the TC, in contrast to the non-looping cases. This circulation serves as a key background difference of the two types of TC motions. Idealized simulations show that when a TC approaches the island's topography from the east, the channeling effect enhances the northerly flow, accelerating the TC southward. Meanwhile, the MG is blocked by the topography, preventing it from merging with the TC as it does in the absence of topography, contributing to a separation between their centers. As a result, the westerly flow from the southern flank of MG can subsequently steer the TC. Thereafter, the merger of MG and TC circulation completes the LT. In contrast, a TC in the absence of either an MG or topography only exhibits a southward or northward deflection, without undergoing a LT. This study highlights the interactions among the TC, MG and topography may induce unusual TC tracks.
{"title":"Unusual tropical cyclone looping tracks associated with monsoon gyre near an isolated high mountain","authors":"Weihao Wang , Xuyang Ge , Melinda Peng","doi":"10.1016/j.atmosres.2026.108761","DOIUrl":"10.1016/j.atmosres.2026.108761","url":null,"abstract":"<div><div>The processes on Tropical cyclones' (TCs) looping tracks (LTs) near an isolated terrain are investigated with numerical simulations. The large-scale environmental fields of observed TCs approaching Taiwan Island with and without LTs are compared. LT cases exhibit a monsoon gyre (MG)-like circulation on the southeast side of the TC, in contrast to the non-looping cases. This circulation serves as a key background difference of the two types of TC motions. Idealized simulations show that when a TC approaches the island's topography from the east, the channeling effect enhances the northerly flow, accelerating the TC southward. Meanwhile, the MG is blocked by the topography, preventing it from merging with the TC as it does in the absence of topography, contributing to a separation between their centers. As a result, the westerly flow from the southern flank of MG can subsequently steer the TC. Thereafter, the merger of MG and TC circulation completes the LT. In contrast, a TC in the absence of either an MG or topography only exhibits a southward or northward deflection, without undergoing a LT. This study highlights the interactions among the TC, MG and topography may induce unusual TC tracks.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108761"},"PeriodicalIF":4.4,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-08DOI: 10.1016/j.atmosres.2026.108768
Xin Liu , Jianing Feng , Lu Liu , Hongxiong Xu , Dajun Zhao , Hui Wang , Yike Zhou
Air pollution is strongly linked to local and synoptic-scale atmospheric conditions, and tropical cyclones (TCs) are recognized as high-wind systems that facilitate pollutant scavenging. A key question is whether TC-triggered Rossby wave trains exert direct or remote indirect influences on pollutant concentrations. Using multi-source reanalysis datasets, this study examined the dynamic impacts of the Rossby wave trains from two successive TCs in 2023 (Doksuri, TC1; Khanun, TC2) on central China's pollutant concentrations. Results showed a prominent Rossby wave train was excited by TC1; its alternating anticyclone (A) - cyclone (C) structure drove periodic high-low pressure oscillations in the study area. Pollutant concentrations correlated with wave train phases: cyclonic phases (TC1/TC2/C1) brought strong ascent, enhanced winds, and precipitation, reducing PM2.5 and CO rapidly; anticyclonic phases (A0/A1/A2) caused subsidence and weak winds, worsening diffusion and increasing pollutants. TC1 directly affected local pollution by passing through the area. TC2 propagated northward over the ocean with no direct impact on the study area, but its wave train blocked mid-latitude energy transport, forcing mid-latitude high-pressure energy southward and inducing secondary pollution. This study is the first to quantify TC-Rossby wave train effects on pollutant diffusion (direct/indirect), providing a novel perspective for TC-air pollution links.
{"title":"Impact of Rossby wave trains triggered by two successive typhoons in 2023 on local air pollutant concentrations in China","authors":"Xin Liu , Jianing Feng , Lu Liu , Hongxiong Xu , Dajun Zhao , Hui Wang , Yike Zhou","doi":"10.1016/j.atmosres.2026.108768","DOIUrl":"10.1016/j.atmosres.2026.108768","url":null,"abstract":"<div><div>Air pollution is strongly linked to local and synoptic-scale atmospheric conditions, and tropical cyclones (TCs) are recognized as high-wind systems that facilitate pollutant scavenging. A key question is whether TC-triggered Rossby wave trains exert direct or remote indirect influences on pollutant concentrations. Using multi-source reanalysis datasets, this study examined the dynamic impacts of the Rossby wave trains from two successive TCs in 2023 (Doksuri, TC1; Khanun, TC2) on central China's pollutant concentrations. Results showed a prominent Rossby wave train was excited by TC1; its alternating anticyclone (A) - cyclone (C) structure drove periodic high-low pressure oscillations in the study area. Pollutant concentrations correlated with wave train phases: cyclonic phases (TC1/TC2/C1) brought strong ascent, enhanced winds, and precipitation, reducing PM2.5 and CO rapidly; anticyclonic phases (A0/A1/A2) caused subsidence and weak winds, worsening diffusion and increasing pollutants. TC1 directly affected local pollution by passing through the area. TC2 propagated northward over the ocean with no direct impact on the study area, but its wave train blocked mid-latitude energy transport, forcing mid-latitude high-pressure energy southward and inducing secondary pollution. This study is the first to quantify TC-Rossby wave train effects on pollutant diffusion (direct/indirect), providing a novel perspective for TC-air pollution links.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108768"},"PeriodicalIF":4.4,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-08DOI: 10.1016/j.atmosres.2026.108766
Denise Pernigotti , Mario Marcello Miglietta
The COVID-19 lockdown in 2020 represented a unique opportunity to evaluate the way reduced traffic may influence air pollution levels. In the present study, this analysis is performed in the Veneto region, northeastern Italy, one of the most polluted areas in Europe, in the eastern Po Valley. During the first month of the COVID-19 lockdown period, the concentrations of fine particles (PM10) fell by 20–25% in the area, which corresponded to a 30–40% decrease in NO2 emissions, mostly attributed to lower traffic volumes.
In order to understand if the specific atmospheric conditions of the period affected the decrease in PM10 concentration, meteorological data from ground stations and radio-soundings, together with ERA5 reanalysis data, were analysed to better define the role of meteorology in the reduced pollution concentrations. The analysis does not identify significant changes in the meteorological conditions.
The improvement in the concentrations of PM10 during the lockdown period emphasizes the potential benefits of traffic reduction in achieving air quality goals. Unfortunately, current policy plans are insufficient, failing the 39% reduction in traffic emissions declared as necessary by the Veneto region to comply with EU standards. This consideration highlights the urgent need for significant changes in traffic management strategies in the region.
{"title":"Traffic and PM10 in Veneto region (northeastern Italy): The lesson of the 2020 lockdown","authors":"Denise Pernigotti , Mario Marcello Miglietta","doi":"10.1016/j.atmosres.2026.108766","DOIUrl":"10.1016/j.atmosres.2026.108766","url":null,"abstract":"<div><div>The COVID-19 lockdown in 2020 represented a unique opportunity to evaluate the way reduced traffic may influence air pollution levels. In the present study, this analysis is performed in the Veneto region, northeastern Italy, one of the most polluted areas in Europe, in the eastern Po Valley. During the first month of the COVID-19 lockdown period, the concentrations of fine particles (PM10) fell by 20–25% in the area, which corresponded to a 30–40% decrease in NO<sub>2</sub> emissions, mostly attributed to lower traffic volumes.</div><div>In order to understand if the specific atmospheric conditions of the period affected the decrease in PM10 concentration, meteorological data from ground stations and radio-soundings, together with ERA5 reanalysis data, were analysed to better define the role of meteorology in the reduced pollution concentrations. The analysis does not identify significant changes in the meteorological conditions.</div><div>The improvement in the concentrations of PM10 during the lockdown period emphasizes the potential benefits of traffic reduction in achieving air quality goals. Unfortunately, current policy plans are insufficient, failing the 39% reduction in traffic emissions declared as necessary by the Veneto region to comply with EU standards. This consideration highlights the urgent need for significant changes in traffic management strategies in the region.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108766"},"PeriodicalIF":4.4,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.atmosres.2026.108749
Huang Zheng , Weiwei Chen , Xiaohui Bi , Nan Chen , Cheng Wu , Mingming Zheng , Shaofei Kong
Differences in black carbon (BC) emissions and diverse climate zones in China result in significant spatial heterogeneity of BC levels. Understanding the roles of emissions, meteorological conditions, and other factors in BC variation is important for mitigating its adverse effects. This study conducted synchronous observations of BC in Changchun (CC), Tianjin (TJ), Wuhan (WH), and Guangzhou (GZ) during winter. Results showed that BC levels were highest in WH compared to the other cities (p < 0.001). Simulations using the Flexible Particle Dispersion (FLEXPART) model and BC emission inventories quantified the contributions from local transport and different sectors. Results indicated that local emissions were the dominant geographical source of observed BC levels at all four sites. BC from residential, commercial, and other sectors was the dominant source in TJ, WH, and GZ. Using the SHapley Additive exPlanations (SHAP) method, emissions were identified as the predominant factor influencing BC variation at the four sites. While changes in meteorological conditions were the most influential factor contributing to BC concentration increases as air quality worsened from clean to polluted in CC, TJ, and WH. Regarding the impacts of features on model outputs, emissions showed a linear relationship with simulated BC, while the effects of transport and meteorological conditions exhibited spatial heterogeneity. This study highlights the need for continuous reduction of BC emissions to decrease ambient BC levels, and this recommendation can be extended to other parts of the country.
{"title":"Understanding the spatial heterogeneity of black carbon variation drivers in China: Views from explainable machine learning","authors":"Huang Zheng , Weiwei Chen , Xiaohui Bi , Nan Chen , Cheng Wu , Mingming Zheng , Shaofei Kong","doi":"10.1016/j.atmosres.2026.108749","DOIUrl":"10.1016/j.atmosres.2026.108749","url":null,"abstract":"<div><div>Differences in black carbon (BC) emissions and diverse climate zones in China result in significant spatial heterogeneity of BC levels. Understanding the roles of emissions, meteorological conditions, and other factors in BC variation is important for mitigating its adverse effects. This study conducted synchronous observations of BC in Changchun (CC), Tianjin (TJ), Wuhan (WH), and Guangzhou (GZ) during winter. Results showed that BC levels were highest in WH compared to the other cities (<em>p</em> < 0.001). Simulations using the Flexible Particle Dispersion (FLEXPART) model and BC emission inventories quantified the contributions from local transport and different sectors. Results indicated that local emissions were the dominant geographical source of observed BC levels at all four sites. BC from residential, commercial, and other sectors was the dominant source in TJ, WH, and GZ. Using the SHapley Additive exPlanations (SHAP) method, emissions were identified as the predominant factor influencing BC variation at the four sites. While changes in meteorological conditions were the most influential factor contributing to BC concentration increases as air quality worsened from clean to polluted in CC, TJ, and WH. Regarding the impacts of features on model outputs, emissions showed a linear relationship with simulated BC, while the effects of transport and meteorological conditions exhibited spatial heterogeneity. This study highlights the need for continuous reduction of BC emissions to decrease ambient BC levels, and this recommendation can be extended to other parts of the country.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108749"},"PeriodicalIF":4.4,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.atmosres.2026.108752
Sadegh Kaboli , Ville Kankare , Ali Torabi Haghighi , Cintia Bertacchi Uvo , Elina Kasvi
The timing of the spring season in the boreal region is shifting under global warming, with profound impacts on ecosystems and hydrological processes. However, the mechanisms driving this transition and its considerable interannual variability are not well described, especially regarding the influence of large-scale atmospheric teleconnection patterns. This study examines the temporal variability of the observed thermal spring season across Finland, a boreal country warming faster than the global average. Key spring timing indices, including onset, end, duration, and growing season onset, were calculated and analyzed using high-resolution (1 km × 1 km) daily mean temperature data from 1961 to 2023. Spatial and temporal patterns were identified through Empirical Orthogonal Function (EOF) decomposition, and their associations with major atmospheric teleconnection patterns were examined. Results indicated that during the past six decades, the spring onset has advanced by 2–6 days/decade, with the most pronounced changes in the coastal and southwestern parts of the country. The duration of the spring season has extended by 3–6 days/decade in the northern areas and along the southwestern coast. The early spring onset was associated with a strong positive phase of the Arctic Oscillation (AO), and delayed spring end and growing season onset were linked to the positive phase of the East Atlantic–West Russia (EAWR) pattern. By contrast, an early growing season start was linked to the positive phase of the North Atlantic Oscillation (NAO). The duration of the thermal spring season showed a strong association with the Scandinavian (SCA) pattern.
在全球变暖的影响下，北方地区春季的时间正在发生变化，对生态系统和水文过程产生了深远的影响。然而，驱动这种转变的机制及其相当大的年际变率没有得到很好的描述，特别是关于大尺度大气遥相关型态的影响。本研究考察了芬兰观测到的温泉季节的时间变异性，芬兰是一个比全球平均变暖速度更快的北方国家。利用1961 ~ 2023年高分辨率（1 km × 1 km）日平均气温资料，计算并分析了春季开始、结束、持续时间和生长季节开始等关键时间指标。通过经验正交函数（EOF）分解确定了时空格局，并分析了它们与主要大气遥相关格局的相关性。结果表明：近60 a来，春季开始时间以2 ~ 6 d / a的速度提前，沿海和西南地区变化最为显著；在北部地区和西南沿海，春季的持续时间每十年延长3-6天。早春与北极涛动（AO）强正相相关，晚春结束和生长期开始与东大西洋-西俄罗斯（EAWR）型正相相关。相比之下，生长季节的提前开始与北大西洋涛动（NAO）的正相位有关。温泉季节的持续时间与斯堪的纳维亚（SCA）模式有很强的相关性。
{"title":"Associations between the thermal spring timing variability and atmospheric teleconnection patterns over the past six decades in Finland","authors":"Sadegh Kaboli , Ville Kankare , Ali Torabi Haghighi , Cintia Bertacchi Uvo , Elina Kasvi","doi":"10.1016/j.atmosres.2026.108752","DOIUrl":"10.1016/j.atmosres.2026.108752","url":null,"abstract":"<div><div>The timing of the spring season in the boreal region is shifting under global warming, with profound impacts on ecosystems and hydrological processes. However, the mechanisms driving this transition and its considerable interannual variability are not well described, especially regarding the influence of large-scale atmospheric teleconnection patterns. This study examines the temporal variability of the observed thermal spring season across Finland, a boreal country warming faster than the global average. Key spring timing indices, including onset, end, duration, and growing season onset, were calculated and analyzed using high-resolution (1 km × 1 km) daily mean temperature data from 1961 to 2023. Spatial and temporal patterns were identified through Empirical Orthogonal Function (EOF) decomposition, and their associations with major atmospheric teleconnection patterns were examined. Results indicated that during the past six decades, the spring onset has advanced by 2–6 days/decade, with the most pronounced changes in the coastal and southwestern parts of the country. The duration of the spring season has extended by 3–6 days/decade in the northern areas and along the southwestern coast. The early spring onset was associated with a strong positive phase of the Arctic Oscillation (AO), and delayed spring end and growing season onset were linked to the positive phase of the East Atlantic–West Russia (EAWR) pattern. By contrast, an early growing season start was linked to the positive phase of the North Atlantic Oscillation (NAO). The duration of the thermal spring season showed a strong association with the Scandinavian (SCA) pattern.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108752"},"PeriodicalIF":4.4,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1016/j.atmosres.2026.108746
Yi Lin , Honggang Lv , Kehan Chen , Peng Guo , Yifei Jiang , Lin Xiao , Tienan Zhao , Haiyan Wang , Yuanyuan Chen , Kunpeng Zang , Shuangxi Fang
Atmospheric carbon dioxide (CO₂), the primary anthropogenic greenhouse gas, is a critical tracer for understanding carbon-cycle–climate feedback. Despite intense industrialization and population density, the Yangtze River Delta (YRD) lacks high-frequency in situ CO₂ observations in its coastal and marine-influenced zones. In this study, the continuous atmospheric CO₂ measurements collected between December 2020 and December 2022 at an urban tower in Shanghai and a coastal background site in Shengsi were analyzed. Results reveal a distinct bimodal diurnal cycle in Shanghai, primarily driven by local anthropogenic emissions, whereas Shengsi exhibits a unimodal pattern more closely coupled to biospheric processes and marine dilution. Nighttime data from Shanghai station reliably represents urban background concentrations, as the stable concentration performance, less planetary boundary layer (PBL) and anthropogenic impacts. Wind and trajectory analyses link CO₂ enhancement at Shanghai to emissions from northern and northwestern sectors, whereas Shengsi concentrations are modulated by ocean-atmosphere carbon exchange—as evidenced by correlations with sea surface temperature, salinity, and pressure, alongside stronger negative links to normalized difference vegetation index (NDVI) and air temperature compared to Shanghai. Furthermore, partial least squares regression (PLSR) further highlights the dominance of local emissions at Shanghai (< 200 km scale) and oceanic/biospheric drivers at Shengsi, with regional transport amplifying variability across scales. These findings advance understanding of CO₂ spatiotemporal variability in coastal megaregions and provide an empirical basis for improving top-down carbon flux estimates and informing targeted climate mitigation strategies in eastern China.
{"title":"Atmospheric CO₂ concentration gradients at the coastal region of the Yangtze River Delta: Patterns and drivers","authors":"Yi Lin , Honggang Lv , Kehan Chen , Peng Guo , Yifei Jiang , Lin Xiao , Tienan Zhao , Haiyan Wang , Yuanyuan Chen , Kunpeng Zang , Shuangxi Fang","doi":"10.1016/j.atmosres.2026.108746","DOIUrl":"10.1016/j.atmosres.2026.108746","url":null,"abstract":"<div><div>Atmospheric carbon dioxide (CO₂), the primary anthropogenic greenhouse gas, is a critical tracer for understanding carbon-cycle–climate feedback. Despite intense industrialization and population density, the Yangtze River Delta (YRD) lacks high-frequency in situ CO₂ observations in its coastal and marine-influenced zones. In this study, the continuous atmospheric CO₂ measurements collected between December 2020 and December 2022 at an urban tower in Shanghai and a coastal background site in Shengsi were analyzed. Results reveal a distinct bimodal diurnal cycle in Shanghai, primarily driven by local anthropogenic emissions, whereas Shengsi exhibits a unimodal pattern more closely coupled to biospheric processes and marine dilution. Nighttime data from Shanghai station reliably represents urban background concentrations, as the stable concentration performance, less planetary boundary layer (PBL) and anthropogenic impacts. Wind and trajectory analyses link CO₂ enhancement at Shanghai to emissions from northern and northwestern sectors, whereas Shengsi concentrations are modulated by ocean-atmosphere carbon exchange—as evidenced by correlations with sea surface temperature, salinity, and pressure, alongside stronger negative links to normalized difference vegetation index (NDVI) and air temperature compared to Shanghai. Furthermore, partial least squares regression (PLSR) further highlights the dominance of local emissions at Shanghai (< 200 km scale) and oceanic/biospheric drivers at Shengsi, with regional transport amplifying variability across scales. These findings advance understanding of CO₂ spatiotemporal variability in coastal megaregions and provide an empirical basis for improving top-down carbon flux estimates and informing targeted climate mitigation strategies in eastern China.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108746"},"PeriodicalIF":4.4,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carbon satellites, as an essential means of obtaining atmospheric XCO2 concentration, play a key role in monitoring the global carbon cycle. However, the differences in observation platforms, resolutions, and inversion algorithms among different satellites lead to apparent inconsistencies among multi-source XCO2 data, which limits the joint application and comprehensive analysis of the data. In this paper, we develop a framework named MCF-XCO2 (Multi-source Consistency Fusion of XCO2) for correcting multi-source satellite XCO2 observations and performing uncertainty-weighted fusion. The method leverages high-precision satellite products as references, while minimizing the need for direct ground-based correction, to enhance the consistency and overall accuracy of multi-source observations. Based on this framework, multi-source satellite data, including GOSAT, GOSAT-2, OCO-2, and OCO-3, were integrated to construct a sparsely gridded global XCO2 fusion dataset at 0.01° × 0.02° nominal spatial resolution and nominal daily sampling, reflecting available observations. The findings indicate that the fused dataset shows improved coverage in grids with available observations compared to individual satellite products, improved accuracy, and better consistency over time. Independent validation against TCCON ground-based observations further confirms the method's effectiveness, with R2 = 0.91, RMSE = 1.09 ppm, bias = 0.07 ppm, and MRE = 0.2 %. The spatial and temporal dynamic analysis of the fused dataset reveals the typical spatial structure and seasonal variation of global carbon concentration, demonstrating the potential application of this dataset in studying the carbon cycle. The MCF-XCO2 framework is also designed to accommodate future satellite missions, supporting timely updates and extended temporal coverage.
{"title":"MCF-XCO2: A cross-mission consistency and fusion framework for integrating multi-satellite XCO2 observations","authors":"Yutang Yu , Wenjie Tian , Lili Zhang , Tao Yu , Yu Wu , Tianhai Cheng","doi":"10.1016/j.atmosres.2026.108747","DOIUrl":"10.1016/j.atmosres.2026.108747","url":null,"abstract":"<div><div>Carbon satellites, as an essential means of obtaining atmospheric XCO<sub>2</sub> concentration, play a key role in monitoring the global carbon cycle. However, the differences in observation platforms, resolutions, and inversion algorithms among different satellites lead to apparent inconsistencies among multi-source XCO<sub>2</sub> data, which limits the joint application and comprehensive analysis of the data. In this paper, we develop a framework named <strong>MCF-XCO</strong><sub><strong>2</strong></sub> (<strong>M</strong>ulti-source <strong>C</strong>onsistency <strong>F</strong>usion of <strong>XCO</strong><sub><strong>2</strong></sub>) for correcting multi-source satellite XCO<sub>2</sub> observations and performing uncertainty-weighted fusion. The method leverages high-precision satellite products as references, while minimizing the need for direct ground-based correction, to enhance the consistency and overall accuracy of multi-source observations. Based on this framework, multi-source satellite data, including GOSAT, GOSAT-2, OCO-2, and OCO-3, were integrated to construct a sparsely gridded global XCO<sub>2</sub> fusion dataset at 0.01° × 0.02° nominal spatial resolution and nominal daily sampling, reflecting available observations. The findings indicate that the fused dataset shows improved coverage in grids with available observations compared to individual satellite products, improved accuracy, and better consistency over time. Independent validation against TCCON ground-based observations further confirms the method's effectiveness, with R<sup>2</sup> = 0.91, RMSE = 1.09 ppm, bias = 0.07 ppm, and MRE = 0.2 %. The spatial and temporal dynamic analysis of the fused dataset reveals the typical spatial structure and seasonal variation of global carbon concentration, demonstrating the potential application of this dataset in studying the carbon cycle. The MCF-XCO<sub>2</sub> framework is also designed to accommodate future satellite missions, supporting timely updates and extended temporal coverage.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"334 ","pages":"Article 108747"},"PeriodicalIF":4.4,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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