Earth System Science Data最新文献

{"title":"A Global Daily High Spatial-temporal Coverage Merged Tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2","authors":"Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Jason Blake Cohen","doi":"10.5194/essd-2024-146","DOIUrl":"https://doi.org/10.5194/essd-2024-146","url":null,"abstract":"<strong>Abstract.</strong> Remote sensing based on satellites can provide long-term, consistent, and global coverage of NO₂ (an important atmospheric air pollutant) as well as other trace gases. However, satellite data often miss data due to factors including but not limited to clouds, surface features, and aerosols. Moreover, one of the longest continuous observational platforms of NO₂ observations from space, OMI, has suffered from missing data over certain rows since 2007, significantly reducing spatial coverage. This work uses the OMI based OMNO2 product, as well as an NO₂ product from GOME-2 in combination with machine learning (XGBoost) and spatial interpolation (DINEOF) method to produce a 16-year global daily high spatial-temporal coverage merged tropospheric NO₂ dataset (HSTCM-NO₂, https://doi.org/10.5281/zenodo.10968462, Qin et al., 2024), which increases the global spatial coverage of NO₂ by ~60 % compared to the original OMINO2 data. The HSTCM-NO₂ dataset is validated using upward looking observations of NO₂ (MAX-DOAS), other satellites (TROPOMI), and reanalysis products. The comparisons show that HSTCM-NO₂ maintains a good correlation with the magnitude of other observational datasets, except for under heavily polluted conditions (&gt;6×10¹⁵ molec.cm^-2). This work also introduces a new validation technique to validate coherent spatial and temporal signals (EOF) and validates that the HSTCM-NO₂ are not only consistent with the original OMNO2 data, but in some parts of the world effectively fill in missing gaps and yield a superior result when analyzing long-range atmospheric transport of NO₂. The few differences are also reported to be related to areas in which the original OMNO2 signal was very low, which has been shown elsewhere, but not from this perspective, further validating that applying a minimum cutoff to retrieved NO₂ data is essential. The reconstructed data product can effectively extend the utilization value of the original OMNO2 data, and the data quality of HSTCM-NO₂ can meet the needs of scientific research.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"357 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-Temporal Changes in China’s Mainland Shorelines Over 30 Years Using Landsat Time Series Data (1990–2019)","authors":"Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, Yong Ge","doi":"10.5194/essd-2024-123","DOIUrl":"https://doi.org/10.5194/essd-2024-123","url":null,"abstract":"<strong>Abstract.</strong> Continuous monitoring of shoreline dynamics is essential to understanding the drivers of shoreline changes and evolution. A long-term shoreline dataset can describe the dynamic changes in the spatio-temporal dimension and provide information on the influence of anthropogenic activities and natural factors on coastal areas. This study, conducted on the Google Earth Engine platform, analyzed the spatio-temporal evolution characteristics of China’s shorelines, including those of Hainan and Taiwan, from 1990 to 2019 using long time series of Landsat TM/ETM+/OLI images. First, we constructed a time series of the Modified Normalized Difference Water Index (MNDWI) with high-quality reconstruction by the harmonic analysis of time series (HANTS) algorithm. Second, the Otsu algorithm was used to separate land and water of coastal areas based on MNDWI value at high tide levels. Finally, a 30-year shoreline dataset was generated and a shoreline change analysis was conducted to characterize length change, area change, and rate of change. We concluded the following: (1) China’s shoreline has shown an increasing trend in the past 30 years, with varying growth patterns across regions; the total shoreline length increased from 24905.55 km in 1990 to 25391.34 km in 2019, with a total increase greater than 485.78 km, a rate of increase of 1.95 %, and an average annual increasing rate of 0.07 %; (3) the most visible expansion has taken place in Tianjin, Hangzhou Bay, and Zhuhai for the three economically developed regions of the Bohai Bay-Yellow River Estuary Zone (BHBYREZ), the Yangtze River Estuary-Hangzhou Bay Zone (YRE-HZBZ) and the Pearl River Estuary Zone (PREZ), respectively. The statistics of shoreline change rate for the three economically developed regions show that the average end point rates (EPR) were 43.59 m/a, 39.10 m/a, and 13.42 m/a, and the average linear regression rates (LRR) were 57.40 m/a, 43.85 m/a, and 10.11 m/a, respectively. This study presents an innovative and up-to-date dataset and comprehensive information on the status of China’s shoreline from 1990 to 2019, contributing to related research and policy implementation, especially in support of sustainable development.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"47 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiwavelength, aerosol lidars at Maïdo supersite, Reunion Island, France: instruments description, data processing chain and quality assessment","authors":"Dominique Gantois, Guillaume Payen, Michaël Sicard, Valentin Duflot, Nicolas Marquestaut, Thierry Portafaix, Sophie Godin-Beekmann, Patrick Hernandez, Eric Golubic","doi":"10.5194/essd-2024-93","DOIUrl":"https://doi.org/10.5194/essd-2024-93","url":null,"abstract":"<strong>Abstract.</strong> Understanding optical and radiative properties of aerosols and clouds is critical to reduce uncertainties in climate models. For over 10 years, the Observatory of Atmospheric Physics of La Réunion (OPAR) has been operating three active lidar instruments (named Li1200, LiO3S and LiO3T) providing time-series of vertical profiles from 3 to 45 km of the aerosol extinction and backscatter coefficients at 355 and 532 nm, as well as the linear depolarization ratio at 532 nm. This work provides a full technical description of the three systems, details about the methods chosen for the signal preprocessing and processing, and an uncertainty analysis. About 1737 night-time averaged profiles were manually screened to provide cloud-free and artifact-free profiles. Data processing consisted in Klett inversion to retrieve aerosol optical products from preprocessed files. The measurement frequency was lower during the wet season and the holiday periods. There is a good correlation between the Li1200 and LiO3S in terms of stratospheric AOD at 355 nm (0.001–0.107; R = 0.92 ± 0.01), and with the LiO3T in terms of Angström exponent 355/532 (0.079–1.288; R = 0.90 ± 0.13). The lowest values of the averaged uncertainty of the aerosol backscatter coefficient for the three time-series are 64.4 ± 31.6 % for the LiO3S, 50.3 ± 29.0 % for the Li1200, and 69.1 ± 42.7 % for the LiO3T. These relative uncertainties are high for the three instruments because of the very low values of extinction and backscatter coefficients for background aerosols above Maïdo observatory. Uncertainty increases due to SNR decrease above 25 km for the LIO3S and Li1200, and 20 km for the LiO3T. The LR is responsible for an uncertainty increase below 18 km (10 km) for the LiO3S and Li1200 (LiO3T). The LiO3S is the most stable instrument at 355 nm due to less technical modifications and less misalignments. The Li1200 is a valuable addition to fill in the gaps in the LiO3S time-series at 355 nm or for specific case-studies about the middle and low troposphere. Data described in this work are available at https://doi.org/10.26171/rwcm-q370 (Gantois et al., 2024).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"24 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015","authors":"Kanishka B. Narayan, Brian C. O'Neill, Stephanie Waldhoff, Claudia Tebaldi","doi":"10.5194/essd-16-2333-2024","DOIUrl":"https://doi.org/10.5194/essd-16-2333-2024","url":null,"abstract":"Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"45 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140942742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The SDUST2022GRA global marine gravity anomalies recovered from radar and laser altimeter data: Contribution of ICESat-2 laser altimetry","authors":"Zhen Li, Jinyun Guo, Chengcheng Zhu, Xin Liu, Cheinway Hwang, Sergey Lebedev, Xiaotao Chang, Anatoly Soloviev, Heping Sun","doi":"10.5194/essd-2023-484","DOIUrl":"https://doi.org/10.5194/essd-2023-484","url":null,"abstract":"<strong>Abstract.</strong> Global marine gravity anomaly models are predominantly recovered from along-track radar altimeter data. While remarkable advancements has been achieved in gravity anomaly modelling, the quality of gravity anomaly model remains constrained by the absence of across-track geoid gradients and the reduction of radar altimeter data, particularly in coastal and high-latitudes regions. ICESat-2 laser altimetry operates three-pair laser beams with a small footprint and near-polar orbit, enabling the determination of across-track geoid gradients and providing more valid observations in certain regions. The ICESat-2 altimeter data processing method is presented including the determination of across-track geoid gradients and the combination of along/across-track geoid gradients. A new global marine gravity model, SDUST2022GRA, is recovered from radar and laser altimeter data using different method for determining each altimeter data error. The accuracy and spatial resolution of SDUST2022GRA is assessed by published global gravity anomaly models (DTU17, V32.1, NSOAS22) and available shipborne gravity measurements. The accuracy of SDUST2022GRA is 4.43 mGal on a global scale, which is at least 0.22 mGal better than that of others models. Moreover, in local coastal and high-latitude regions, SDUST2022GRA achieves an accuracy improvement of 0.16–0.24 mGal compared to others models. The spatial resolution of SDUST2022GRA is approximately 20 km in a certain region, slightly better superior others models. These assessments suggests that SDUST2022GRA is a reliable global marine gravity anomaly model. By comparing SDUST2022GRA with incorporating ICESat-2 and SDUST2021GRA without ICESat-2, the percentage contribution of ICESat-2 to the improvement of gravity anomaly model accuracy is 13 % in the global ocean region, and it is increasing with an proportion of ICESat-2 altimeter data in high-latitude and coastal regions. The SDUST2022GRA are freely available at the site of https://doi.org/10.5281/zenodo.8337387 (Li et al., 2023).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"64 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140915019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive mapping of organic carbon stocks in surficial sediments of the Canadian continental margin","authors":"Graham Epstein, Susanna D. Fuller, Dipti Hingmire, Paul G. Myers, Angelica Peña, Clark Pennelly, Julia K. Baum","doi":"10.5194/essd-16-2165-2024","DOIUrl":"https://doi.org/10.5194/essd-16-2165-2024","url":null,"abstract":"Abstract. Quantification and mapping of surficial seabed sediment organic carbon have wide-scale relevance for marine ecology, geology and environmental resource management, with carbon densities and accumulation rates being a major indicator of geological history, ecological function and ecosystem service provisioning, including the potential to contribute to nature-based climate change mitigation. While global analyses can appear to provide a definitive understanding of the spatial distribution of sediment carbon, regional maps may be constructed at finer resolutions and can utilise targeted data syntheses and refined spatial data products and therefore have the potential to improve these estimates. Here, we report a national systematic review of data on organic carbon content in seabed sediments across Canada and combine this with a synthesis and unification of the best available data on sediment composition, seafloor morphology, hydrology, chemistry and geographic settings within a machine learning mapping framework. Predictive quantitative maps of mud content, dry bulk density, organic carbon content and organic carbon density were produced along with cell-specific estimates of their uncertainty at 200 m resolution across 4 489 235 km2 of the Canadian continental margin (92.6 % of the seafloor area above 2500 m) (https://doi.org/10.5683/SP3/ICHVVA, Epstein et al., 2024). Fine-scale variation in carbon stocks was identified across the Canadian continental margin, particularly in the Pacific Ocean and Atlantic Ocean regions. Overall, we estimate the standing stock of organic carbon in the top 30 cm of surficial seabed sediments across the Canadian shelf and slope to be 10.9 Gt (7.0–16.0 Gt). Increased empirical sediment data collection and higher precision in spatial environmental data layers could significantly reduce uncertainty and increase accuracy in these products over time.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"13 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140915008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence","authors":"Piers M. Forster, Chris Smith, Tristram Walsh, William Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard Betts, Tim Boyer, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, Panmao Zhai","doi":"10.5194/essd-2024-149","DOIUrl":"https://doi.org/10.5194/essd-2024-149","url":null,"abstract":"<strong>Abstract.</strong> Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11064126, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. This is below the 2023 observed record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.4 GtCO2e per year over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO₂ emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"162 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140890414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oceanographic monitoring in Hornsund fjord, Svalbard","authors":"Meri Korhonen, Mateusz Moskalik, Oskar Głowacki, Vineet Jain","doi":"10.5194/essd-2024-153","DOIUrl":"https://doi.org/10.5194/essd-2024-153","url":null,"abstract":"<strong>Abstract.</strong> Several climate-driven processes take place in the Arctic fjords. These include ice-ocean interactions, changes in biodiversity and ocean circulation patterns, as well as coastal erosion phenomena. Conducting long-term oceanographic monitoring in the Arctic fjords is, therefore, essential for better understanding and predicting global environmental shifts. Here we address this issue by introducing a new hydrographic dataset from Hornsund, a fjord located in south-western part of Svalbard archipelago. Hydrographic properties have been monitored with vertical temperature, salinity and depth profiles in several lo- cations across the Hornsund fjord from 2015 to 2023. From 2016 onward dissolved oxygen and turbidity data are available for the majority of casts. The dataset contributes to the so far infrequent observations especially in spring and autumn and extends the observations typically concentrated in the central fjord to the areas adjacent to the tidewater glaciers. Because sediment discharge from glaciers and land is an inseparable part of the glacier-ocean interactions, the suspended sediment concentration in the water column as well as the daily sedimentation rate adjacent to the tidewater glaciers are monitored with regular water sampling and bottom-moored sediment traps. Here we present the planning and execution of the monitoring campaign from the collection of the data to the post-processing methods. All datasets are publicly available at the repositories referred to in the Data availability section of this manuscript.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"32 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140890423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reanalysis of multi-year high-resolution X-band weather radar observations in Hamburg","authors":"Finn Burgemeister, Marco Clemens, Felix Ament","doi":"10.5194/essd-16-2317-2024","DOIUrl":"https://doi.org/10.5194/essd-16-2317-2024","url":null,"abstract":"Abstract. This paper presents an open-access data set of reanalysed radar reflectivities and rainfall rates at sub-kilometre spatial and minute temporal scales. Variability at these scales is a blind spot for both operational rain gauge networks and operational radar networks. In the urban area of Hamburg, precipitation measurements of a single-polarized X-band weather radar operating at high temporal (30 s), range (60 m), and azimuthal sampling (1°) resolutions are made available for a period of more than 8 years. We describe in detail the reanalysis of the raw radar data, outline the radar performance for the years 2013 to 2021, and discuss open issues and limitations of the data set. Several sources of radar-based errors were adjusted gradually, affecting the radar reflectivity and rainfall measurements, e.g. noise, alignment, non-meteorological echoes, radar calibration, and attenuation. The deployment of additional vertically pointing micro rain radars yields drop size distributions at the radar beam height, which effectively reduces errors concerning the radar calibration and attenuation correction and monitors the radar data quality. A statistical evaluation revealed that X-band radar reflectivities and rainfall rates are in very good agreement with the micro rain radar measurements. Moreover, the analyses of rainfall patterns shown for an event and accumulated rainfall of several months prove the quality of the data set. The provided radar reflectivities facilitate studies on attenuation correction and the derivation of further weather radar products, like an improved rainfall rate. The rainfall rates themselves can be used for studies on the spatial and temporal scales of precipitation and hydrological research, e.g. input data for high-resolution modelling, in an urban area. The radar reflectivities and rainfall rates are available at https://doi.org/10.26050/WDCC/LAWR_UHH_HHG_v2 (Burgemeister et al., 2024).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"56 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140845636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-year high time resolution measurements of fine PM at 13 sites of the French Operational Network (CARA program): Data processing and chemical composition","authors":"Hasna Chebaicheb, Joel F. de Brito, Tanguy Amodeo, Florian Couvidat, Jean-Eudes Petit, Emmanuel Tison, Gregory Abbou, Alexia Baudic, Mélodie Chatain, Benjamin Chazeau, Nicolas Marchand, Raphaele Falhun, Florie Francony, Cyril Ratier, Didier Grenier, Romain Vidaud, Shouwen Zhang, Gregory Gille, Laurent Meunier, Caroline Marchand, Véronique Riffault, Olivier Favez","doi":"10.5194/essd-2024-80","DOIUrl":"https://doi.org/10.5194/essd-2024-80","url":null,"abstract":"<strong>Abstract.</strong> This paper presents a first comprehensive analysis of long-term measurements of atmospheric aerosol components from Aerosol Chemical Speciation Monitor (ACSM) and multi-wavelength Aethalometer (AE33) instruments collected between 2015 and 2021 at 13 (sub)urban sites as part of the French CARA program. The datasets contain the mass concentrations of major chemical species within PM₁, namely organic aerosols (OA), nitrate (NO₃^-), ammonium (NH₄⁺), sulfate (SO₄^2-), non-sea-salt chloride (Cl^-), and equivalent black carbon (eBC). Rigorous quality control, technical validation, and environmental evaluation processes were applied, adhering to both the guidance from the French reference laboratory for air quality monitoring and the Aerosol, Clouds, and Trace gases Research Infrastructure (ACTRIS) standard operating procedures. Key findings include geographical differences in aerosol chemical composition, seasonal variations, and diel patterns, which are influenced by meteorological conditions, anthropogenic activities, and proximity to emission sources. Overall, OA dominates PM₁ at each site (43–60 %), showing distinct seasonality with higher concentrations (i) in winter, due to enhanced residential heating emissions, and (ii) in summer, due to increased photochemistry favoring secondary aerosol formation. NO₃ is the second most important contributor to PM₁ (15–30 %), peaking in late winter and early spring, especially in northern France, and playing a significant role during pollution episodes. SO₄ (8–14 %) and eBC (5–11 %) complement the major fine aerosol species, with their relative contributions strongly influenced by the origin of air masses and the stability of meteorological conditions, respectively. Such chemically-speciated multi-year datasets have significant value for the scientific community, offering opportunities for future research, including source apportionment studies, trend analyses, and epidemiological investigations. They are also vital for evaluating and validating regional air quality models. In this regard, a comparison with the CHIMERE Chemical Transport Model shows high correlations between simulations and measurements, albeit underestimating OA concentrations by 46–76 %. Regional discrepancies in NO₃ concentration levels emphasize the importance of these datasets in validating air quality models and tailoring air pollution mitigation strategies.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"12 1","pages":""},"PeriodicalIF":11.4,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140845765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}