V. Reinhart, P. Hoffmann, D. Rechid, J. Böhner, B. Bechtel
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.
摘要植物功能类型(pft)的概念在利用区域气候模式(RCMs)进行土地利用和气候变化研究时有助于反映植物特征的复杂性。通过将土地利用和土地覆盖(LULC)表示为功能特征，特定植物群落的响应和影响可以直接耦合到最低大气层。为了满足rcm对真实LULC分布的要求，我们开发了一个欧洲PFT数据集(LANDMATE PFT Version 1.0 Reinhart et al.， 2021b，;)。该数据集基于ESA-CCI高分辨率土地覆盖数据集，并通过额外使用气候信息进一步改进。在LANDMATE PFT数据集中，基于卫星的LULC信息和气候数据相结合，以尽可能地代表不同的植物群落及其在各自区域生态系统中的功能，同时保持数据集在rcm应用中的灵活性。ESA-CCI的每个LULC类别都通过使用Holdridge生命区概念转换为包含气候信息的PFT或PFT分数。通过考虑区域气候数据，得到的欧洲PFT图是区域定制的。对LANDMATE PFT数据集的全面评估是使用欧洲大陆的综合地面真值数据库完成的。开发了一种合适的评价方法，并将其应用于评价新的PFT数据集的质量。评估结果表明，耕地和林地的优势土地利用效率在数据集中得到了很好的体现，而一些代表性较差的土地利用效率则存在不确定性。LANDMATE PFT数据集为在RCM中实现提供了一个真实的、高分辨率的LULC分布，并被用作Hoffmann等人(已提交)在配套论文中引入的LUCAS LUC数据集的基础，该数据集可作为专注于调查LULC变化影响的RCM实验设置的LULC变化输入。
{"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}
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
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).
摘要我们提供了Lutjewad站(荷兰)和Mace Head站(爱尔兰)20年的大气CO2、δO2/N2和APO的烧瓶样本记录，以及哈雷站(南极洲)3年的记录，包括广泛校准程序的细节及其随时间的稳定性。我们对来自世界各地不同研究实验室的气瓶进行了相互比较，结果也表明我们的校准是高质量的，并且与国际公认的斯克里普斯刻度兼容。Lutjewad和Mace Head的测量记录显示，2002-2018年期间，Lutjewad的CO2和δO2/N2的长期趋势相似，分别为2.31±0.07 ppm yr - 1和- 21.2±0.8 / meg yr - 1, Mace Head的CO2和δO2/N2的长期趋势为2.22±0.04 ppm yr - 1和- 21.3±0.9 / meg yr - 1。它们也表现出相似的δO2/N2季节循环，Lutjewad的振幅为54±4 / meg, Mace Head的振幅为61±5 / meg，而Lutjewad的CO2季节振幅(16.8±0.5 ppm)略高于Mace Head的(14.8±0.3 ppm)。我们发现，观测到的趋势和季节周期与各个站点的测量结果是一致的，特别是来自英国韦伯恩大气观测站的测量结果。然而，Mace Head和Lutjewad记录的δO2/N2和APO的年趋势进展存在显著差异，这部分可能是采样差异造成的，但也可能是环境影响造成的，例如Mace Head对北大西洋氧通变化更为敏感。哈雷记录显示δO2/N2和APO有明显的变化趋势和季节性，特别是APO与东安格利亚大学在哈雷的连续测量结果吻合得很好，而CO2和δO2/N2则略有差异，这很可能是采样过程中的小泄漏造成的。从我们2002-2018年的记录中，我们发现全球海洋汇的一致性很好:分别基于Lutjewad和Mace Head，分别为2.0±0.8 PgC yr - 1和2.2±0.9 PgC yr - 1。这项工作提供的数据可在https://doi.org/10.18160/qq7d-t060上获得(Nguyen et al.， 2021)。
{"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}
Kun Li, F. Tian, Mohd Yawar Ali Khan, R. Xu, Zhihua He, Long Yang, Hui Lu, Yingzhao Ma
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).
摘要青藏高原(TP)以亚洲水塔而闻名，许多大河都发源于此。然而，由于气候和地形的复杂空间变异性，目前仍缺乏用于水文建模和洪水预测的高质量降雨数据集。因此，本研究的目标是在高密度雨量计网似然测量的基础上，通过合并GPM-IMERG、GSMaP和CMORPH三颗卫星的降雨估计，建立一个高精度的日降雨产品。新合并的日降雨量数据集空间分辨率为0.1°，重点关注2014 - 2019年温暖季节(6月10日- 10月31日)。统计评估表明，新数据集优于原始卫星估计值，特别是在降雨积累和地面降雨事件检测方面。雅鲁藏布江流域的水文评估表明，合并的降雨数据集在为径流模拟提供准确和稳健的强迫方面具有很高的性能。与MSWEP和CHIRPS等其他类似类型的产品相比，新的降雨数据集也具有优势。这个新的降雨数据集可以在https://doi.org/10.11888/Hydro.tpdc.271303上公开访问(Li et al.，2021)。
{"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}
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
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.
{"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}
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).
摘要我们提出了一个全球土壤NO排放数据集，包括网格化的月度数据和相应的3小时权重因子，适用于大气化学建模。全球数据以0.5°× 0.5°水平分辨率提供，每月时间分辨率为2000-2018年。排放以总价值的形式提供，同时还提供了来自背景生物群落值的土壤NO排放的单独数据，以及由肥料/粪肥、脉冲效应和大气沉积引起的土壤NO排放的数据，以便用户可以根据需要包括、排除或修改每个组成部分。本文介绍了排放算法及其数据来源，对其他清单中土壤NO排放的可用性(以及如何避免重复计算)进行了一些评论，最后给出了一些初步的建模结果以及与观测数据的比较。该数据集是作为哥白尼大气监测服务(CAMS)的一部分构建的，数据集称为CAMS- glob - soil v2.2。这些数据可通过哥白尼大气数据存储(ADS)系统(https://doi.org/10.24380/kz2r-fe18，最后一次访问于2021年6月，Simpson 2021a)或通过大气化合物排放和辅助数据汇编(ECCAD)系统(https://eccad.aeris-data.fr/，最后一次访问于2021年6月)获得。为了审查目的，ECCAD已经建立了一个匿名存储库，其中CAMS-GLOB-SOIL v2.2数据的一个子集可以直接访问(https://eccad.aeris-data.fr/essd-surf-emis-cams-soil/， Last access July 2021, Simpson 2021b)。
{"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}
P. Laffargue, D. Delaunay, Vincent Badts, O. Berthelé, Anne-Sophie Cornou, F. Garren
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.
{"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}
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
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.
{"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}
M. Tourian, O. Elmi, Yasin Shafaghi, Sajedeh Behnia, P. Saemian, Ron Schlesinger, N. Sneeuw
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.
{"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}
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).
{"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}
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
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
{"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}
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