Earth System Science Data Discussions最新文献

{"title":"High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 1: The plant functional type basemap for 2015","authors":"V. Reinhart, P. Hoffmann, D. Rechid, J. Böhner, B. Bechtel","doi":"10.5194/essd-2021-251","DOIUrl":"https://doi.org/10.5194/essd-2021-251","url":null,"abstract":"Abstract. The concept of plant functional types (PFTs) is shown to be beneficial in representing the complexity of plant characteristics in land use and climate change studies using regional climate models (RCMs). By representing land use and land cover (LULC) as functional traits, responses and effects of specific plant communities can be directly coupled to the lowest atmospheric layers. To meet the requirements of RCMs for realistic LULC distribution, we developed a PFT dataset forEurope (LANDMATE PFT Version 1.0 Reinhart et al., 2021b, ;). The dataset is based on the high-resolution ESA-CCI land cover dataset and is further improved through the the additional use of climate information. Within the LANDMATE PFT dataset, satellite-based LULC information and climate data are combined to achieve the best possible representation of the diverse plant communities and their functions in the respective regional ecosystems while keeping the dataset most flexible for application in RCMs. Each LULC class of ESA-CCI is translated into PFT or PFT fractions including climate information by using the Holdridge Life Zone concept. Through the consideration of regional climate data, the resulting PFT map for Europe is regionally customized. A thorough evaluation of the LANDMATE PFT dataset is done using a comprehensive ground truth database over the European Continent. A suitable evaluation method has been developed and applied to assess the quality of thenew PFT dataset. The assessment shows that the dominant LULC groups, cropland and woodland, are well represented within the dataset while uncertainties are found for some less represented LULC groups. The LANDMATE PFT dataset provides a realistic, high-resolution LULC distribution for implementation in RCMs and is used as basis for the LUCAS LUC dataset introduced in the companion paper by Hoffmann et al. (submitted) which is available for use as LULC change input for RCM experiment setups focused on investigating LULC change impact.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129908193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two decades of flask observations of atmospheric δO2/N2, CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland) plus 3 years from Halley station (Antarctica)","authors":"Linh N. T. Nguyen, H. Meijer, C. van Leeuwen, Bert A. M. Kers, B. Scheeren, A. Jones, N. Brough, Thomas Barningham, P. Pickers, A. Manning, I. Luijkx","doi":"10.5194/essd-2021-213","DOIUrl":"https://doi.org/10.5194/essd-2021-213","url":null,"abstract":"Abstract. We present 20-year flask sample records of atmospheric CO2, δO2/N2 and APO from the stations Lutjewad (the Netherlands) and Mace Head (Ireland) and a 3-year record from Halley station (Antarctica), including details of the extensive calibration procedure and its stability over time. The results of our inter-comparison involving gas cylinders from various research laboratories worldwide also show that our calibration is of high quality and compatible with the internationally recognised Scripps scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002–2018 of 2.31 ± 0.07 ppm yr−1 for CO2 and −21.2 ± 0.8 per meg yr−1 for δO2/N2 at Lutjewad, and 2.22 ± 0.04 ppm yr−1 for CO2 and −21.3 ± 0.9 per meg yr−1 for δO2/N2 at Mace Head. They also show a similar δO2/N2 seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while CO2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed trends and seasonal cycles are compatible with the measurements from various stations, especially the measurements from Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δO2/N2 and APO, which might in part be caused by sampling differences, but also by environmental effects, such as the North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δO2/N2 and APO, where especially APO agrees well with the continuous measurements at Halley by the University of East Anglia, while CO2 and δO2/N2 present slight disagreements, most likely caused by small leakages during sampling. From our 2002–2018 records, we find good agreement for the global ocean sink: 2.0 ± 0.8 PgC yr−1 and 2.2 ± 0.9 PgC yr−1, based on Lutjewad and Mace Head, respectively. The data presented in this work are available at https://doi.org/10.18160/qq7d-t060 (Nguyen et al., 2021).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122497614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A High-Accuracy Rainfall Dataset by Merging Multi-Satellites and Dense Gauges over Southern Tibetan Plateau for 2014–2019 Warm Seasons","authors":"Kun Li, F. Tian, Mohd Yawar Ali Khan, R. Xu, Zhihua He, Long Yang, Hui Lu, Yingzhao Ma","doi":"10.5194/ESSD-2021-179","DOIUrl":"https://doi.org/10.5194/ESSD-2021-179","url":null,"abstract":"Abstract. Tibetan Plateau (TP) is well known as the Asia’s water tower from where many large rivers originate. However, due to complex spatial variability of climate and topography, there is still a lack of high-quality rainfall dataset for hydrological modelling and flood prediction. This study, therefore, aims to establish a high-accuracy daily rainfall product through merging rainfall estimates from three satellites, i.e., GPM-IMERG, GSMaP, and CMORPH, based on the likelihood measurements of a high-density rainfall gauge network. The new merged daily rainfall dataset with a spatial resolution of 0.1°, focuses on warm seasons (June 10th–October 31st) from 2014 to 2019. Statistical evaluation indicated that the new dataset outperforms the raw satellite estimates, especially in terms of rainfall accumulation and the detection of ground-based rainfall events. Hydrological evaluation in the Yarlung Zangbo River Basin demonstrated high performance of the merged rainfall dataset in providing accurate and robust forcings for streamflow simulations. The new rainfall dataset additionally shows superiority to several other products of similar types, including MSWEP and CHIRPS. This new rainfall dataset is publicly accessible at https://doi.org/10.11888/Hydro.tpdc.271303 (Li et al.,2021).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122102533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water clarity annual dynamics (1984–2018) dataset across China derived from Landsat images in Google Earth Engine","authors":"H. Tao, K. Song, Ge Liu, Qiang Wang, Z. Wen, P. Jacinthe, Xiaofeng Xu, Jia Du, Y. Shang, Sijia Li, Zongming Wang, L. Lyu, Junbin Hou, Xiang Wang, Dong Liu, Kun Shi, Baohua Zhang, H. Duan","doi":"10.5194/ESSD-2021-227","DOIUrl":"https://doi.org/10.5194/ESSD-2021-227","url":null,"abstract":"Abstract. Water clarity provides a sensitive tool to examine spatial pattern and historical trend in lakes trophic status. Yet, this metric has insufficiently been explored despite the availability of remotely-sensed data. We used three Secchi disk depth (SDD) datasets for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red/blue band ratio algorithm was applied to map SDD for lakes (> 1 ha) based on the first SDD dataset, where R2 = 0.79, RMSE = 100.3 cm, rRMSE = 61.9 %, MAE = 57.7 cm. The other two datasets were used to validate the SDD estimation model, which were indicated the model had a stable performance of temporal transferability. The annual mean SDD of lakes were retrieved across China using Landsat top of air reflectance products in GEE from 1984 to 2018. The spatiotemporal dynamics of SDD were analysed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found that the lakes with SDDs < 2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total area of lakes with SDD between 0–0.5 m and > 4 m were the largest, accounting for 48.28 % of the total lakes. During 1984–2018, lakes in the Tibetan-Qinghai Plateau lake region (TQR) had the clearest water with an average value of 3.32 ± 0.38 m, while that in the Northeastern lake region (NLR) exhibited the lowest SDD (mean: 0.60 ± 0.09 m). Among the 10,814 lakes with SDD results more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia-Xinjiang lake region (MXR), more than half of the total lakes in every other lake region exhibited significant increasing trends. In the Eastern lake region (ELR), NLR and Yungui Plateau lake region (YGR), almost more than 50 % of the lakes that displayed an increase or decrease in SDD were mainly distributed in an area of 0.01–1 km2, whereas that in the TQR and MXR were primarily concentrated in large lakes (> 10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset can now be accessed through the website of the National Tibetan Plateau Data Center (http://data.tpdc.ac.cn): DOI: 10.11888/Hydro.tpdc.271571.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124408162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global soil NO emissions for Atmospheric Chemical Transport Modelling: CAMS-GLOB-SOIL v2.2","authors":"D. Simpson, S. Darras","doi":"10.5194/ESSD-2021-221","DOIUrl":"https://doi.org/10.5194/ESSD-2021-221","url":null,"abstract":"Abstract. We present a dataset of global soil NO emissions comprising gridded monthly data and the corresponding 3-hourly weight factors, suitable for atmospheric chemistry modelling. Data are provided globally at 0.5° × 0.5° degrees horizontal resolution, and with monthly time resolution over the period 2000–2018. Emissions are provided as total values and also with separate data for soil NO emissions from background biome values, and those induced by fertilizers/manure, pulsing effects, and atmospheric deposition, so that users can include, exclude or modify each component if wanted. This paper presents the emission algorithms and their data-sources, some comments on the availability of soil NO emissions in other inventories (and how to avoid double-counting), and finally some preliminary modelling results and comparison with observed data. This dataset was constructed as part of the Copernicus Atmosphere Monitoring Service (CAMS), with the dataset referred to as CAMS-GLOB-SOIL v2.2. These data are available through the Copernicus Atmosphere Data Store (ADS) system, (https://doi.org/10.24380/kz2r-fe18, last access June 2021, Simpson 2021a) or through the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access June 2021). For review purposes, ECCAD has set up an anonymous repository where a subset of the CAMS-GLOB-SOIL v2.2 data can be accessed directly (https://eccad.aeris-data.fr/essd-surf-emis-cams-soil/, Last access July 2021, Simpson 2021b).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115235641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fish and cephalopods monitoring on the Bay of Biscay and Celtic Sea continental shelves","authors":"P. Laffargue, D. Delaunay, Vincent Badts, O. Berthelé, Anne-Sophie Cornou, F. Garren","doi":"10.5194/ESSD-2021-146","DOIUrl":"https://doi.org/10.5194/ESSD-2021-146","url":null,"abstract":"Abstract. The demersal fish and cephalopod communities of the continental shelves of the Bay of Biscay and the Celtic Sea have been monitored for more than 30 years by the EVHOE series of fisheries surveys. Since 1987, a total of 4247 stations have been sampled in the fall with a GOV bottom trawl in a depth range of 15 to 600 m. The main objective of these surveys is to monitor 22 benthic fish stocks and 10 cephalopods but also to provide a description of the distribution of a total of 250 fish and 50 commercial invertebrate taxa. The dataset (https://doi.org/10.17882/80041) provides abundance and biomass information by station for all observed taxa. Size distributions for a selection of species are also available. These data are part of a larger set of standardized European surveys that provide essential information for monitoring demersal communities in the Northeast Atlantic. We propose here a critical analysis of the dataset especially in terms of the evolution of the sampling effort and strategy as well as the taxonomic precision.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131321811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-definition spatial distribution maps of on-road transport exhaust emissions in Chile, 1990–2020","authors":"M. Osses, N. Rojas, Cecilia Ibarra, Victoria C. Valdebenito, Ignacio Laengle, Nicolás Pantoja, Darío Osses, Kevin Basoa, Sebastián Tolvett, N. Huneeus, L. Gallardo, Benjamín Gómez","doi":"10.5194/essd-2021-218","DOIUrl":"https://doi.org/10.5194/essd-2021-218","url":null,"abstract":"Abstract. This description paper presents a detailed and consistent estimate and analysis of exhaust pollutant emissions generated by Chile's road transport activity for the period 1990–2020. The complete database for the period 1990–2020 is available at doi: http://dx.doi.org/10.17632/z69m8xm843.2. Emissions are provided at high-spatial resolution (0.01° × 0.01°) over continental Chile from 18.5 S to 53.2 S, including local pollutants (CO, VOC, NOx, MP2.5), black carbon (BC) and greenhouse gases (CO2, CH4). The methodology considers 70 vehicle types, based on ten vehicle categories, subdivided into two fuel types and seven emission standards. Vehicle activity was calculated based on official databases of vehicle records and vehicle flow counts. Fuel consumption was calculated based on vehicle activity and contrasted with fuel sales, to calibrate the initial dataset. Emission factors come mainly from COPERT 5, adapted to local conditions in the 15 political regions of Chile, based on emission standards and fuel quality. While vehicle fleet has grown fivefold between 1990 and 2020, CO2 emissions had followed this trend at a lower rate and emissions of local pollutants have decreased, due to stricter abatement technologies, better fuel quality and enforcement of emission standards. In other words, there has been decoupling between fleet growth and emissions’ rate of change. Results were contrasted with EDGAR datasets, showing similarities in CO2 estimations and striking differences in PM, BC and CO; in the case of NOx and CH4 there is coincidence only until 2008. In all cases of divergent results, EDGAR estimates higher emissions.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125225818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HydroSat: a repository of global water cycle products from spaceborne geodetic sensors","authors":"M. Tourian, O. Elmi, Yasin Shafaghi, Sajedeh Behnia, P. Saemian, Ron Schlesinger, N. Sneeuw","doi":"10.5194/ESSD-2021-174","DOIUrl":"https://doi.org/10.5194/ESSD-2021-174","url":null,"abstract":"Abstract. Against the backdrop of global change, both in terms of climate and demography, there is a pressing need for monitoring the global water cycle. The publicly available global database is very limited in its spatial and temporal coverage worldwide. Moreover, the acquisition of in situ data and their delivery to the database are in decline since the late 1970s, be it for economical or political reasons. Given the insufficient monitoring from in situ gauge networks, and with no outlook for improvement, spaceborne approaches have been under investigation for some years now. Satellite-based Earth observation with its global coverage and homogeneous accuracy has been demonstrated to be a potential alternative to in situ measurements. This paper presents HydroSat as a repository of global water cycle products from spaceborne geodetic sensors. HydroSat provides time series and their uncertainty of: water level from satellite altimetry, surface water extent from satellite imagery, terrestrial water storage anomaly from satellite gravimetry, lake and reservoir water storage anomaly from a combination of satellite altimetry and imagery, and river discharge from either satellite altimetry or imagery. These products can contribute to understanding the global water cycle within the Earth system in several ways. They can act as inputs to hydrological models, they can play a complementary role to current and future spaceborne observations, and they can define indicators of the past and future state of the global freshwater system. The repository is publicly available through http://hydrosat.gis.uni-stuttgart.de.\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114445815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of soil and land cover databases for use in the Soil Water Assessment Tool from Irish National Soil Maps and CORINE Land Cover Maps for Ireland","authors":"Bidroha Basu","doi":"10.5194/ESSD-2021-169","DOIUrl":"https://doi.org/10.5194/ESSD-2021-169","url":null,"abstract":"Abstract. Soil Water Assessment Tool (SWAT) are being extensively used by hydrologists and environmentalists to simulate river discharge and water quality at watershed/basin scale across the world. The SWAT is a physically based semi-distributed rainfall runoff model and require watershed related characteristics (elevation, land cover, and soil information for the entire river basin) and meteorological variables (rainfall, temperature, relative humidity, solar radiation and windspeed) information to simulation runoff and water quality data at the basin outlet. One drawback of SWAT is that the default database for the model is available for United States and the modeller needs to develop a separate database to implement the model at river basins located outside the USA. This study generates soil and landcover database that can be used for the SWAT modelling for river basins located in Ireland. The soil database has been created based on soil testing experiments conducted during the STRIVE programme by Teagasc and Environmental Protection Agency Ireland. The landcover database has been created by relating the landcover data obtained from the CORINE database with the default SWAT landcover database. Furthermore, detailed information on the five meteorological data covering Ireland has been provided. A newly created SWAT geodatabase has been generated that can be used as a replacement from the default SWAT database for simulating runoff and water quality at river basins in Ireland. The database contains digital elevation model, soil and landcover maps along with river network and river subbasins for Ireland and is publicly available at: https://doi.org/10.5281/zenodo.4767926 (Basu, 2021).\u0000","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122886244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive dataset for global, regional and national greenhouse gas emissions by sector 1970–2019","authors":"J. Minx, W. Lamb, R. Andrew, J. Canadell, M. Crippa, Niklas Döbbeling, P. Forster, D. Guizzardi, J. Olivier, G. Peters, J. Pongratz, A. Reisinger, M. Rigby, M. Saunois, Steven J. Smith, E. Solazzo, H. Tian","doi":"10.5281/ZENODO.5053056","DOIUrl":"https://doi.org/10.5281/ZENODO.5053056","url":null,"abstract":"Abstract. To track progress towards keeping warming well below 2 °C, as agreed upon in the Paris Agreement, comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions (GHG) is required. Here we provide a dataset on anthropogenic GHG emissions 1970–2019 with a broad country and sector coverage. We build the dataset from recent releases of the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases, and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with data on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three bookkeeping models. We provide an assessment of the uncertainties in each greenhouse gas at the 90 % confidence interval (5th–95th percentile) by combining statistical analysis and comparisons of global emissions inventories with an expert judgement informed by the relevant scientific literature. We identify important data gaps: CH4 and N2O emissions could be respectively 10–20 % higher than reported in EDGAR once all emissions are accounted. F-gas emissions estimates for individual species in EDGARv5 do not align well with atmospheric measurements and the F-gas total exceeds measured concentrations by about 30 %. However, EDGAR and official national emission reports under the UNFCCC do not comprehensively cover all relevant F-gas species. Excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are larger than the sum of the reported species. GHG emissions in 2019 amounted to 59 ± 6.6 GtCO2eq: CO2 emissions from FFI were 38 ± 3.0 Gt, CO2 from LULUCF 6.6 ± 4.6 Gt, CH4 11 ± 3.3 GtCO2eq, N2O 2.4 ±1.5 GtCO2eq and F-gases 1.6 ± 0.49 GtCO2eq. Our analysis of global, anthropogenic GHG emission trends over the past five decades (1970–2019) highlights a pattern of varied, but sustained emissions growth. There is high confidence that global anthropogenic greenhouse gas emissions have increased every decade. Emission growth has been persistent across different (groups of) gases. While CO2 has accounted for almost 75 % of the emission growth since 1970 in terms of CO2eq as reported here, the combined F-gases have grown at a faster rate than other GHGs, albeit starting from low levels in 1970. Today, F-gases make a non-negligible contribution to global warming – even though CFCs and HCFCs, regulated under the Montreal Protocol and not included in our estimates, have contributed more. There is further high confidence that global anthropogenic GHG emission levels were higher in 2010-2019 than in any previous decade and GHG emission levels have grown across the most recent decade. While average annual greenhouse gas emissions growth slowed between 2010–2019 compared to 2000–2009, the absolute increase in average decadal GHG emissions from the 2000s to the 2010s has been the largest","PeriodicalId":326085,"journal":{"name":"Earth System Science Data Discussions","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115962797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}