Atmospheric Research最新文献

{"title":"Operational satellite cloud products need local adjustment – The Galapagos case of ecoclimatic cloud zonation","authors":"Nazli Turini ,&nbsp;Byron Delgado Maldonado ,&nbsp;Samira Zander ,&nbsp;Steve Darwin Bayas López ,&nbsp;Daniela Ballari ,&nbsp;Rolando Célleri ,&nbsp;Johanna Orellana - Alvear ,&nbsp;Benjamin Schmidt ,&nbsp;Dieter Scherer ,&nbsp;Jörg Bendix","doi":"10.1016/j.atmosres.2025.107918","DOIUrl":"10.1016/j.atmosres.2025.107918","url":null,"abstract":"<div><div>Like many small oceanic islands, the Galapagos archipelago, renowned for its unique geographic location and exceptional endemic biodiversity, faces significant challenges under climate change. In particular, the atmospheric water supply for the ecosystem and the local population is under threat, with clouds and rain playing an important role in ensuring freshwater availability under climate change. Better planning of adaptation measures would require climate data on clouds as a prerequisite for precipitation and rainfall at high spatio-temporal resolution, which are not available in this area. Operational products such as satellite derived cloud and precipitation products or reanalysis data are widely used to compensate for the lack of local data availability but are often poorly suited for regional applications. In the current study, we aim to generate high quality area-wide cloud information to distinguish ecoclimatic cloud zones that may require different adaptation measures to climate change. To address this issue, we have developed a new physical rule-based cloud mask retrieval specifically tailored for the Galapagos Archipelago, based on data from the third generation GOES-16 Advanced Baseline Imager (ABI) geostationary satellite. The new Galapagos Rainfall Retrieval (GRR) cloudmask was tested against independent observational data and compared to both the operational GOES-16 ACM (ABI Clear sky Mask) and the MODIS cloudmask benchmark cloud mask. Our test results confirm that the GRR-cloudmask (Probability of Detection POD = 0.94, Critical Success Index CSI = 0.92–0.93) clearly outperforms the operational ACM-cloudmask (POD = 0.56–0.68, CSI = 0.55–0.67). Area-wide tests against the MODIS cloud mask showed a CSI of 0.72 and a POD of 0.74 for the ACM, which is superior to the GOES-16 ACM-cloudmask. We produced cloud frequency maps for all months and day slots and analysed cloud frequency using ancillary meteorological data. In general, the cool season (Jun-Dec) / night shows much higher cloud frequencies than the warm season (Jan-May) / daytime. However, regional cloud patterns differ along a west-to-east and south-to-north gradient, depending on complex interactions of forcing parameters such as exposure to the main circulation, sea surface temperature zones, altitude and land cover. A k-mean cluster analysis resulted in nine ecoclimatic cloud zones over land, which are much more differentiated than the widely used four-zone classification. The results will help to develop more site-specific climate change adaptation planning for the iconic Galapagos National Park.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107918"},"PeriodicalIF":4.5,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi criteria evaluation of downscaled CMIP6 models in predicting precipitation extremes","authors":"Rishi Gupta,&nbsp;Prem Prakash,&nbsp;Vinay Chembolu","doi":"10.1016/j.atmosres.2025.107921","DOIUrl":"10.1016/j.atmosres.2025.107921","url":null,"abstract":"<div><div>The selection of general circulation models (GCMs) is primary information required for assessing climate change impacts on the hydrological vulnerability of any region. The uncertainties associated with GCMs at the regional scale are mostly attributable to coarser representation of climatic processes, making model ranking an essential step for improving multi-model ensemble (MME) performance. The present study evaluated 13 downscaled-bias-corrected CMIP6 GCMs for eight extreme precipitation indices over the flood-prone Brahmaputra River basin. Precipitation extremes from 1985 to 2014 were employed to evaluate model performance at a grid resolution of 0.25°, while projected events were assessed for the early future (2031–2060) and far future (2071–2100). Individual rankings for precipitation indices were determined using five multicriteria decision-making (MDCM) techniques: TOPSIS, VIKOR, EDAS, PROMETHEE-II, and Performance Matrix. The Criteria Importance Through Inter-criteria Correlation (CRITIC) technique was used to assign weights to each performance indicator for indices-wise ranking. The comprehensive ranking from the various MCDM techniques was further obtained using group decision-making method. The results show that different models are better at capturing different precipitation characteristics, necessitating indices-based rankings for future estimates. The study additionally indicates that Multi-Model Ensemble, MME8, and MME5 outperformed the other ensembles in reducing simulation uncertainty in downscaled GCMs. Future projections indicate an overall increase in precipitation extremes, with the best model ensembles predicting a wetter early future and a drier far future than all model ensembles.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107921"},"PeriodicalIF":4.5,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988146","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}

{"title":"Why have extreme low-temperature events in northern Asia strengthened since the turn of the 21st century?","authors":"Hongbo Hu ,&nbsp;Yanyan Huang ,&nbsp;Dapeng Zhang ,&nbsp;Botao Zhou ,&nbsp;Huijun Wang","doi":"10.1016/j.atmosres.2025.107919","DOIUrl":"10.1016/j.atmosres.2025.107919","url":null,"abstract":"<div><div>This study reveals that the intensity of cold-season (October–March) extreme low-temperature events (ELTs) during 1982–2022 strengthened after the year 2000 over northern Asia, along with a decrease in their frequency. Two significant interdecadal changes in cold-season atmospheric circulations after the year 2000 were found to be associated with these changes. Firstly, there has been an increased occurrence of extremely strong blocking highs over the North Atlantic, promoting anomalous meridional circulation. Secondly, the upper-level jet stream has weakened, reducing the polar vortex and strengthening the cold polar air that erupts southward. Statistical analysis and model experiments suggest that the positive phase of the Atlantic Multidecadal Oscillation after the year 2000 may have contributed to the strengthened ELTs by causing deep warming over the North Atlantic. The direct thermodynamic effects of deep warming intensify the blocking high over the North Atlantic. Simultaneously, an anomalous easterly wind appears in the upper troposphere due to thermal wind theory, and the weakened jet stream results in a stronger meridional flow, leading to an extremely strong blocking high.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107919"},"PeriodicalIF":4.5,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988144","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}

{"title":"Understanding equilibrium climate sensitivity changes from CMIP5 to CMIP6: Feedback, AMOC, and precipitation responses","authors":"Xinqi Wang ,&nbsp;Lijuan Li ,&nbsp;He Wang ,&nbsp;Ling Zuo ,&nbsp;Bin Wang ,&nbsp;Feng Xie","doi":"10.1016/j.atmosres.2025.107917","DOIUrl":"10.1016/j.atmosres.2025.107917","url":null,"abstract":"<div><div>To unravel the equilibrium climate sensitivity (ECS) changes of the models of the Coupled Model Intercomparison Project (CMIP) during the upgrade, 10 pairs of CMIP phase 5 (CMIP5) and phase 6 (CMIP6) models from different centers were categorized into high and low ECS groups according to their ECS and surface air temperature response to CO₂. Results showed that the higher ECS of the CMIP6 multimodel mean is derived primarily from five models of the high group, and is contributed by both stronger positive cloud feedback (CF) and stronger albedo feedback relative to the corresponding values in the CMIP5 models, and the spread of CF is associated with that of the ECS. Positive albedo feedback in the Arctic may be related to the relationship between weakening of the Atlantic Meridional Overturning Circulation (AMOC) and diminishing sea ice area (SIA). For example, the stronger albedo feedback in the CMIP6 high group is linked to the strongly weakening AMOC and sharply reducing SIA, further associated with their mean states compared with those of the CMIP5 models. The higher CF in the CMIP6 high group results from the greater reduction in both cloud area fraction (CAF) and ice water path (IWP) and the weaker increase in the liquid water path (LWP), leading to enhanced shortwave CF and reduced longwave CF. Furthermore, when the total precipitation response is dominated by only the convective or stratiform component, it is prone to substantial increase by the model upgrade, thereby notably affecting the changes in CAF, IWP, and LWP and the variation in CF and ECS in the high group.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107917"},"PeriodicalIF":4.5,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988145","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}

{"title":"Tornadic environments in Mexico","authors":"José Francisco León-Cruz","doi":"10.1016/j.atmosres.2025.107916","DOIUrl":"10.1016/j.atmosres.2025.107916","url":null,"abstract":"<div><div>Tornadoes represent a significant threat to society. In Mexico, these natural hazards are common, principally from the end of spring until autumn, with a mean of around 45 events yearly (2013−2022). Although there is no official tornado database in Mexico with a proper tornado classification, it is known that supercell and non-supercell tornadogenesis is possible in the country. In this context, the present investigation examines the environments under 298 confirmed and validated tornadoes formed in the Mexican territory. Such analysis was made using the proximity-sounding approach with the ERA5 reanalysis dataset. In addition, using the k-means clustering method, three Tornadic Environment Types were found, each with specific characteristics. The first type is the most common environment, documented throughout the year, particularly during summer and the beginning of autumn. Intermediate instability conditions, without wind shear, and high humidity near the surface characterize it. The second type is observed in high altitudes during the spring, with relatively dry conditions and low unstable environments. The previous examples may relate to non-supercell tornadogenesis in different geographical regions and seasons. In contrast, the third type can be associated with significant tornadoes, an environment rich in instability and wind shear, concentrated in the northern portions of Mexico during spring. The findings of this research provide insights into increasing understanding of tornadoes in Mexico. Furthermore, it can be helpful to generate improvements in tornado forecasting at the national level, offering a range of tornadic environment types under which these natural hazards can develop. The clustering method results offer an alternative option for the classification of tornadoes in countries with little capacity for the official classification of these phenomena.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107916"},"PeriodicalIF":4.5,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying the short-duration and long-duration types of summer soil moisture drought on the Loess plateau and their teleconnections","authors":"Jialan Hu ,&nbsp;Shuangshuang Li ,&nbsp;Xianfeng Liu ,&nbsp;Guangyao Gao","doi":"10.1016/j.atmosres.2025.107915","DOIUrl":"10.1016/j.atmosres.2025.107915","url":null,"abstract":"<div><div>Soil moisture drought poses a destructive effect on vegetation growth and water resource. Modeling event-based drought processes could serve as a pathway for better understanding how different types of soil moisture drought responds to larger-scale teleconnections in the monsoon and loess critical zone of China. Based on the daily soil moisture dataset named SMCI1.0 at top 1 m, we found that the Loess Plateau witnessed an aggravated summer soil moisture drought, with summer standardized soil moisture index (SSMI) decreasing by 1.5 % year⁻¹ from 2000 to 2020. According to the durations and spatial coverage of events, we classified 12 summer soil moisture drought events occurring on the Loess Plateau into short-duration (6–14 days) and long-duration (≥15 days) types, and further discussed their different large-scale teleconnections. Interestingly, we found the short-duration (long-duration) summer soil moisture drought was influenced by wave train (blocking) circulation anomalies. The short-duration summer soil moisture drought broke out with an eastward “− + − +” wave train over Eurasia, which was mainly attributed to a tripolar sea surface temperature (SST) mode over the North Atlantic and weakened South Asian high (SAH) with westward shift. Such a structure resulted in water vapor deficit of Loess Plateau, and thus favored shorter summer soil moisture drought on the Loess Plateau. For the long-duration summer soil moisture drought, consistently warm tropical Atlantic and North Sea-Baltic Sea favored the “+ − +” wave train, weaking the southward movement of cold air and maintaining prolonged water vapor deficit accompanied by downward prevails, which consequently provided a favorable condition for more long-lasting and enhanced summer soil moisture deficit. Insights into the large-scale teleconnections related to the different types of soil moisture drought event not only can provide drought early warning information, but also offer a scientific guidance for revegetation projects on the Loess Plateau or other Eurasian drylands.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107915"},"PeriodicalIF":4.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988431","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}

{"title":"Exploring the interconnections between total cloud water content and water vapor mixing ratio with other cloud microphysical variables in northward-moving typhoon precipitation via information entropy: A hybrid causal analysis approach using wavelet coherence and Liang–Kleeman information flow","authors":"Xianghua Wu ,&nbsp;Miaomiao Ren ,&nbsp;Linyi Zhou ,&nbsp;Yashao Li ,&nbsp;Jinghua Chen ,&nbsp;Wanting Li ,&nbsp;Kai Yang ,&nbsp;Weiwei Wang","doi":"10.1016/j.atmosres.2025.107914","DOIUrl":"10.1016/j.atmosres.2025.107914","url":null,"abstract":"<div><div>Causal analysis of cloud microphysical variables constitutes an effective means for characterizing the microphysical attributes and causal mechanisms of precipitation clouds. Causal analysis methods primarily rely on Granger causality tests based on lagged variables and linear regression. However, most cloud physical precipitation processes are nonlinear. Herein, a novel hybrid approach involving information entropy, wavelet decomposition, and Liang–Kleeman information flow is introduced to enhance the dependability and effectiveness of causal analysis for the self-organizing process of precipitation clouds in this paper. Based on the Weather Research and Forecasting (WRF) model, a case study is conducted of the northward-moving process of Typhoon Maysak in 2020. Gridded data with 30-min intervals and a 6 km × 6 km resolution is extracted. Through empirical analysis, using the total cloud water content (TWC) and water vapor mixing ratio (QV) as the principal variable and atmospheric vertical velocity (OMG), precipitable water (PW) and outgoing longwave radiation (OLR) as covariates, the hybrid causal analysis methodology is assessed. TWC and QV are direct and potential influencing factors of precipitation, respectively. Results indicate that the probability distributions of TWC and QV are significantly different at different stages. In the typhoon stage, typical self-organizing characteristics of high mean and low information entropy values are presented; in the tropical storm stage, information entropies increase, TWC increases, and QV decreases, with self-organizing characteristics weakening; in the tropical depression stage, both the mean and information entropies of TWC and QV show a significant decrease. Wavelet coherence analysis indicates that IEOLR and IEPW can better explain IETWC, and IEPW and IEOMG can better explain IEQV. There is a significant causal relationship between IETWC and IEPW at different time scales. At larger periodic scales, IEQV has significant causal relationships with IEOMG, IEPW and IEOLR. Overall, this approach provides insights into the complex causal relationships of cloud microphysical variables in a precipitation cloud system, broadening our understanding of these complex phenomena.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107914"},"PeriodicalIF":4.5,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939713","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}

{"title":"Synoptic patterns of hourly extreme precipitation events over the Yangtze-Huaihe River Basin in China","authors":"Ji Yang ,&nbsp;Mingjian Zeng ,&nbsp;Long Wen ,&nbsp;Kangyuan Sun ,&nbsp;Yuanyuan Zheng ,&nbsp;Wenru Shi","doi":"10.1016/j.atmosres.2025.107913","DOIUrl":"10.1016/j.atmosres.2025.107913","url":null,"abstract":"<div><div>The occurrence of disaster-producing hourly extreme precipitation events (HEPEs) is usually linked to certain atmospheric backgrounds. Using high-density automatic weather stations observations and ERA5 reanalysis, this study analyzed the synoptic patterns of HEPEs over the Yangtze-Huaihe River Basin with an objective classification method. Four primary atmospheric circulation patterns (accounted for over 71 % of HEPEs) are identified, including two mei-yu types differ in different temporal and spatial features, the deep trough type, and the post-mei-yu type. The two mei-yu types are responsible for nearly 50 % of all HEPEs with relatively large horizontal size, and the southwesterly low-level jets that influenced by the cyclone and Western North Pacific Subtropical High (WNPSH), are a representative feature of these two types during HEPEs. The deep trough type during HEPEs related to Northeast China Cold Vortex is characterized by a cold northerly flow collided with the warm southerly/southwesterly flows, resulting in a strong convergence. In contrast, the HEPEs in the post-mei-yu type exhibits an eastward WNPSH, with the convergence and updrafts over the study area are caused by the collision between the southerly cyclone flows and the northerly flows at low levels. During two mei-yu types and post-mei-yu type, the HEPEs (non-precipitation) showed a cyclone (an anticyclone) feature. Our findings demonstrate the significant impact of circulation types on HEPEs, highlighting the importance of understanding their characteristics and patterns, which would be helpful for disaster warning, forecasting, and management.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107913"},"PeriodicalIF":4.5,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939711","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}

{"title":"An assessment of GPM IMERG Version 7 rainfall estimates over the North West Himalayan region","authors":"Sreyasi Biswas ,&nbsp;Charu Singh ,&nbsp;Vidhi Bharti","doi":"10.1016/j.atmosres.2025.107910","DOIUrl":"10.1016/j.atmosres.2025.107910","url":null,"abstract":"<div><div>The latest Global Precipitation Mission (GPM) IMERG V07B Final Run (Hereafter IMERG) has been validated for rainfall estimates in the North West Himalayan (NWH) region during the Indian Summer Monsoon (ISM) season (June–September) of 2000–2022. The validation is assessed against daily 0.25^o x 0.25^o India Meteorological Department (IMD) gridded rainfall data. We found that IMERG inherently underestimates rainfall, particularly low-intensity (&lt; 50 mm day⁻¹) rainfall. However, an overestimation is evident in high-intensity rainfall (50 mm day⁻¹–200 mm day⁻¹). This is consistent across all elevation ranges, from &lt;1000 m to &gt;5000 m, with the most significant negative bias observed at lower elevations. The proportion of such underestimated rainfall events increases with elevation, while the proportion of overestimated rainfall events decreases. Conclusively, IMERG is negatively skewed (−0.94). The proportion of accurate estimation of rainfall intensity is low and lies between 3 mm day⁻¹ to 21 mm day⁻¹ for &lt;1000 m. IMERG performs the best in classifying a ‘rain event’ in Uttarakhand (UK) and Himachal Pradesh (HP), which is evident from near-optimal values of categorical metrics like False Alarm Ratio (FAR) (0.19 and 0.30 respectively), Probability of Detection (POD) (0.86 and 0.86 respectively), and Critical Success Index (CSI) (0.71 and 0.62 respectively). The classification of a “no rain event” by IMERG exhibits relatively low accuracy in the two states (Probability of False Detection (POFD) = 0.54 and 0.65 respectively). Overall, the Accuracy (ACC) in classifying a ‘rainfall event’, irrespective of it being a ‘rain event’ or a ‘no rain event’, is fairly good in UK (ACC = 0.75) and HP (ACC = 0.67) including the estimation of ‘rain event’ (Frequency Bias Index FBI = 1.07 and 1.23 respectively). The manifestation of stratiform rainfall in UK and HP could account for the underestimation of rainfall intensity and the discrepancies in the categorical metrics, owing to them being unrecognized by satellite due to warm cloud top temperatures. IMERG estimates are moderate over Jammu and Kashmir (JK) (FAR = 0.40, ACC = 0.1, CSI = 0.53, POFD = 0.64), while a large uncertainty in the performance of IMERG exists over Ladakh (LD) due to the paucity of IMD rain gauges (FAR = 0.62, ACC = 0.49, CSI = 0.34, POFD = 0.65).</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107910"},"PeriodicalIF":4.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939716","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}

{"title":"Exploring uncertainty reduction in high-resolution methane emissions in Gippsland through in-situ data: A Bayesian inverse modeling and variational assimilation method","authors":"Sougol Aghdasi ,&nbsp;Peter J. Rayner ,&nbsp;Nicholas M. Deutscher ,&nbsp;Jeremy D. Silver","doi":"10.1016/j.atmosres.2025.107911","DOIUrl":"10.1016/j.atmosres.2025.107911","url":null,"abstract":"<div><div>The paper investigates to what extent the assimilation of in-situ data over Gippsland, Victoria, Australia reduces uncertainties in methane emission sources on the regional scale. This was examined via a four-dimensional variational data assimilation system using the Community Multiscale Air Quality (CMAQ) transport-dispersion model. To evaluate the posterior error statistics of optimized monthly-mean methane emissions in Gippsland, we carried out a range of observing system simulation experiments. We ran the assimilations based on four selected months in 2019, employing a horizontal grid resolution of 2 km. The observation data are obtained based on three continuous observation instruments in the Gippsland region. As expected, the largest uncertainty reductions occur near observing sites. Also, our findings indicate that using a high-resolution model and in-situ observations provides detailed information on point sources but offers limited insight into area sources. The overall uncertainty for regional fluxes remains largely unchanged. Therefore, in-situ data is crucial for understanding point sources due to its detailed and localized nature. Finally, uncertainty reduction is much larger when the full concentration dataset is used rather than just the daytime data. This suggests the importance of model improvement to allow use of nighttime data, at least under conditions where the transport model can be expected to simulate atmospheric mixing well.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"315 ","pages":"Article 107911"},"PeriodicalIF":4.5,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}