Earth System Science Data最新文献

{"title":"GloSVeT: a global 0.05° monthly mean surface soil and vegetation component temperature dataset (2003–2023)","authors":"Xiangyang Liu,Zhao-Liang Li,Chen Ru,Si-Bo Duan,Pei Leng","doi":"10.5194/essd-18-6885-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6885-2026","url":null,"abstract":"Current satellite-derived land surface temperature (LST) products represent a mixed radiative signal that integrates soil and vegetation contributions, obscuring the physical mechanisms controlling surface energy partitioning and ecosystem functioning. To overcome this limitation, this study developed the Global Soil and Vegetation Temperature dataset (GloSVeT), the first global product that simultaneously provides surface soil and vegetation component temperatures at 0.05° spatial resolution for the period 2003–2023. GloSVeT was generated using the multisource data fusion-based global surface soil and vegetation temperature retrieval (FuSVeT) method, which integrates multi-temporal MODIS observations with ERA5-Land reanalysis to improve spatial completeness, retrieval accuracy, and computational efficiency. Its performance was extensively assessed through a comprehensive evaluation framework combining internal closure check, flux-tower validation at 72 representative sites, triple collocation (TC) analysis, and physical consistency assessments. Results show that GloSVeT largely preserves the original MODIS mixed-pixel LST constraint, and achieves reliable accuracy with coefficients of determination mostly at or above 0.9 and root mean square errors generally around 2 K for both components. TC analysis further demonstrates globally consistent performance, with advantages in humid tropics and transitional ecosystems compared with reanalysis products. In addition, soil temperature anomalies are predominantly negatively correlated with soil moisture whereas vegetation temperature aligns with solar-induced fluorescence along a clear gradient from energy-limited to water-limited biomes, indicating the physical consistency of GloSVeT. Over pixels where soil and vegetation temperatures are simultaneously available, both components exhibit evident warming trends during 2003–2023, with rates of 0.44 ± 0.04 K per decade for soil temperature and 0.39 ± 0.04 K per decade for vegetation temperature. In summary, GloSVeT provides a physically consistent, observation-driven depiction of surface thermal dynamics, offering new opportunities for quantifying land–atmosphere energy exchange, monitoring ecosystem hydrothermal responses, and improving the representation of land surface processes in Earth system models. GloSVeT is publicly available at https://doi.org/10.11888/RemoteSen.tpdc.303317 (Liu and Li, 2026a) and https://doi.org/10.5281/zenodo.22724289 (Liu and Li, 2026b).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"4 1","pages":"6885-6911"},"PeriodicalIF":11.4,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149021469","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":"FAO estimates of net forest emissions and removals, 1990–2025","authors":"Francesco N. Tubiello,Anne Branthomme,Griffiths Obli-Laryea,Michelle Piccoli,Nidal Ramadan,Rocio Danica Condor,Nathan Wanner,Rachele Brivio,Örjan Jonsson,Giulia Conchedda,Anssi Pekkarinen","doi":"10.5194/essd-18-6799-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6799-2026","url":null,"abstract":"FAO officially collects, analyzes and disseminates forest data by country via the Forest Resources Assessment (FRA) program since the late 1950s. Since 2015, FAO uses a subset of the FRA data, namely forest area and carbon stocks, to compute and disseminate in FAOSTAT net forest emissions/removals estimates, as part of its efforts to assess emissions from agrifood systems. This paper presents the most recent update of the FAO net emission/removal estimates, based on estimates of carbon stock change from all pools, i.e., above- and below-ground living biomass, litter, dead wood and soils, covering over 200 countries and territories for the period 1990–2025. Results show that forests acted globally as net carbon sinks since the 2000s, on average ranging from −1.0 to -2.3GtCO2yr-1 over the most recent decade 2015–2025. This net flux was a result of substantial carbon removals on forest land over the same period, ranging from −3.8 to -6.1GtCO2yr-1, only partially counterbalanced by emissions from net forest loss of 2.8–3.8 Gt CO 2  yr −1  – used herein as a proxy of deforestation. Annex I (AI) and non-Annex I (NAI) countries contributed equally to the estimated forest removals, whereas 90 % of emissions from net forest loss were generated in NAI countries. Comparisons of the FAO estimates with data submitted independently by countries to the United Nations Framework Convention (UNFCCC), as well as with output from the Global Carbon Budget, showed good agreement at global, AI and NAI levels, including for major forest countries. At the same time, important discrepancies between FAO, UNFCCC and global carbon model data were identified in about a dozen countries. Improved convergence of evidence is achievable through dedicated statistical development programs in specific countries, to support international implementation and monitoring of effective climate mitigation actions. The FAO estimates and country data collected from UNFCCC were disseminated in FAOSTAT for 194 countries and 42 territories, with regional and global aggregates, in annual time-series covering the period 1990–2025. They were made available as open access at https://doi.org/10.5281/zenodo.20085666 (Tubiello and Obli-Laryea, 2026).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"38 1","pages":"6799-6813"},"PeriodicalIF":11.4,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149021471","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":"OceanTACO: a multi-sensor global ocean sea surface state dataset","authors":"Nils Lehmann,Cesar Aybar,Ando Shah,Marcello Passaro,Jonathan L. Bamber,Xiao Xiang Zhu","doi":"10.5194/essd-18-6815-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6815-2026","url":null,"abstract":"We present OceanTACO, a harmonised global collection of sea surface state datasets designed to support reproducible Earth system research. The collection integrates satellite altimetry, sea surface temperature, salinity, surface winds, reanalysis fields, and Argo in situ observations within a unified cloud-optimised specification based on Transparent Access to Cloud-optimised datasets (TACO). It includes Level-3 observations, Level-4 gap-filled products, and reanalysis outputs while preserving native spatial and temporal resolution. The core dataset spans 29 March 2023 to 1 August 2025, covering the Surface Water and Ocean Topography (SWOT) mission, with an extended record from 1 January 2015 until 29 March 2023 for non-SWOT sources. Datasets are harmonised through standardised metadata, spatial referencing, and temporal indexing, enabling consistent spatiotemporal queries across sensors and processing levels. The contribution is not a new regridding or compression method, but a sample-invariant, provenance-preserving organisation that allows the same data-access routines to be applied across regions, sensors, and studies. This supports Earth system analysis workflows such as validation against in situ observations, comparisons between observation and mapped products, observation system experiments, and multivariate sensor analyses. Example applications demonstrate cross-product collocation with Argo, analysis of sea surface height variability during extreme events, and relationships between surface variables relevant for data-driven reconstruction. OceanTACO improves accessibility to coordinated multi-source analyses while preserving data provenance and native observation characteristics, and can be extended with new missions without restructuring the dataset. The core and extended dataset are available at https://doi.org/10.57967/hf/8171 (Lehmann and Aybar, 2026a) and https://doi.org/10.57967/hf/8172 (Lehmann and Aybar, 2026b) respectively.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"10 1","pages":"6815-6840"},"PeriodicalIF":11.4,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149021470","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 Global Database of Soil Methane Uptake (SMUD)","authors":"Jiawei Jiang,Zhifeng Yan,Jinshi Jian,Jesper Riis Christiansen,Xinchu Wang,Ren-Min Yang,Zhen Zhang,Philippe Ciais","doi":"10.5194/essd-18-6783-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6783-2026","url":null,"abstract":"Soil methane uptake (SMU), an important biological sink for atmospheric methane (CH 4 ) in terrestrial ecosystems, represents an important component of the global CH 4 budget. Although field SMU observations have been conducted since the 1980s, they have not yet been systematically compiled into a unified and openly available database. Here, we present the global Soil Methane Uptake Database (SMUD), which includes 2427 site-level records from 920 peer-reviewed publications spanning 1986 to 2025. SMUD contains SMU measurements at multiple temporal scales, including daily ( n =1425), monthly ( n =2001), seasonal ( n =1720), and annual ( n =1098), together with associated soil moisture and soil temperature data at daily and monthly scales where available. The collected datasets cover all major climatic zones and ecosystem types and reveal pronounced spatial and temporal variability in SMU. Our analyses show that seasonal- and biome-specific patterns are important for understanding intra-annual variability in SMU. In particular, quantitative classification showed that the relationships of SMU with soil temperature and moisture differed among biomes, resulting in four response types: temperature-dominated, moisture-dominated, jointly regulated by temperature and moisture, and no clear dominant control. Overall, SMUD provides a comprehensive basis for characterizing global SMU patterns, investigating underlying mechanisms, and improving estimates of the global SMU budget. The database, associated data, and code for reproducing the results are available at https://doi.org/10.5281/zenodo.20735332 (Jiang et al., 2026). We aim to maintain SMUD as a collaborative, community-supported, and regularly updated resource for the research community.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"30 1","pages":"6783-6797"},"PeriodicalIF":11.4,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149021500","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 benchmark dataset for half-hourly evapotranspiration estimation in China from 2000 to 2024","authors":"Long Qian,Xingjiao Yu,Lifeng Wu,Yaokui Cui,Zhitao Zhang,Junying Chen,Sumeng Ye,Xuqian Bai,Xiaogang Liu,Sien Li,Rangjian Qiu","doi":"10.5194/essd-18-6707-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6707-2026","url":null,"abstract":"Latent heat flux ( L E ) provides a direct representation of terrestrial evapotranspiration (ET) and plays a critical role in hydrological cycle studies, land surface model development, and the evaluation of remotely sensed evapotranspiration products. Although flux observations based on the eddy covariance technique are widely regarded as essential benchmark data for evapotranspiration estimation, existing ChinaFlux observations are generally limited by short observation periods and extensive data gaps, which substantially constrain their applicability in long-term change analyses and multi-scale studies. To address these limitations, we developed a gap-filling and temporal prolongation framework specifically designed for half-hourly  L E and established a continuous ground-based benchmark dataset covering China for the period 2000–2024 based on observations from 50 ChinaFlux sites. The framework is built upon an automated machine learning approach (AutoML) and integrates ERA5-Land reanalysis data with MODIS vegetation indices, enabling accurate gap-filling within observation periods and reliable prolongation beyond observation intervals. Comprehensive evaluations demonstrate that the AutoML framework achieves high accuracy at the half-hourly scale across different gap-length scenarios, with an overall correlation coefficient (CC) of 0.862 and a root mean square error (RMSE) of 33.75 W m −2 , and it substantially outperforms conventional methods under long-gap conditions (i.e., 7 and 30 d) introduced in the artificial gap experiments. The forward and backward prolongation results show high consistency (CC values of 0.902 and 0.896, respectively) and exhibit robust temporal stability under varying training data lengths. Multi-timescale validations further indicate that the prolonged L E  data reasonably reproduce diurnal variations, seasonal cycles, and interannual variability from half-hourly to daily and monthly scales. Comparisons with ChinaFlux observations under strict quality control (half-hourly  L E observations with QA/QC = 0) reveal good consistency across different temporal scales, underlying surface types, and climate zones. Interpretability analysis based on Shapley Additive Explanations (SHAP) indicates that energy supply consistently dominates L E  variability, while vegetation state and water availability modulate their relative importance under different environmental conditions. Overall, we present the first continuous half-hourly ground-based L E  benchmark dataset covering China for the period 2000–2024. This dataset provides essential data support for the evaluation of remotely sensed ET products, land surface model validation, and studies of regional water–energy cycles and climate change, and it is freely available via the following repository: https://doi.org/10.5281/zenodo.18194590 (Qian et al., 2026).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"66 1","pages":"6707-6740"},"PeriodicalIF":11.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933434","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":"Global and national lime process emissions and carbonation sink from 1930 to 2024","authors":"Longfei Bing,Xiaoyu Zhang,Le Niu,Zhi Cao,Jiaoyue Wang,Jiajie Li,Xue Jiang,Fengming Xi","doi":"10.5194/essd-18-6741-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6741-2026","url":null,"abstract":"Accurate quantification of lime process emissions and subsequent carbonation uptake is needed to represent the lime carbon cycle in global carbon-budget assessments. We developed a source-prioritized and internally cross-checked dataset for 1930–2024 by harmonizing USGS statistics, national statistical yearbooks, industrial records, and explicitly identified proxy-based reconstructions. The framework resolves 11 major lime-producing countries, collectively representing 78.9 % of global lime production, and derives country-specific process-emission factors from sectoral lime-use structures and CaO-content requirements. Annual global lime carbonation uptake increased from 4.1 Mt CO 2  yr −1 (95 % CI: 3.5–4.8 Mt CO 2  yr −1 ) in 1930 to 136.1 Mt CO 2  yr −1 (95 % CI: 107.9–171.5 Mt CO 2  yr −1 ) in 2024, corresponding to a compound annual growth rate of 3.8 %. Cumulative process emissions reached 11.3 Gt CO 2 (95 % confidence interval (CI): 10.7–11.9 Gt CO 2 ), of which construction and metallurgy contributed 3.9 Gt CO 2 (34.5 %) and 3.8 Gt CO 2 (33.5 %), respectively. Cumulative carbonation uptake reached 4.8 Gt CO 2 (95 % CI: 3.9–5.8 Gt CO 2 ), offsetting 42.2 % of process emissions, 3.4 % higher than the 38.8 % estimate for 1930–2020 reported by Bing et al. (2023). China contributed 5.5 Gt CO 2 of process emissions (48.3 % of the global total) and 1.9 Gt CO 2 of carbonation uptake (40.7 %). Uncertainties associated with data sources, historical reconstruction, and material parameters were propagated through 10 000 Monte Carlo iterations. Metallurgical by-products and construction materials dominated cumulative uptake. Country-level trajectories indicate that most developed economies have passed their lime process-emission peaks, whereas China remains on a growth trajectory and Brazil retains substantially higher emissions than its early historical levels despite a modest decline after its 2013 peak. This dataset provides a consistent empirical basis for representing lime-related carbon sources and sinks in global carbon-cycle assessments and is archived in the Science Data Bank at https://doi.org/10.57760/sciencedb.45314 (Bing et al., 2026).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"32 1","pages":"6741-6762"},"PeriodicalIF":11.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933433","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 19-year record of atmospheric sulphur dioxide (SO\u0000 2\u0000 ) derived from IASI measurements","authors":"Lieven Clarisse,Bruno Franco,Lorenzo Fabris,Nicolas Theys,Juliette Hadji-Lazaro,Daniel Hurtmans,Cathy Clerbaux,Pierre Coheur","doi":"10.5194/essd-18-6667-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6667-2026","url":null,"abstract":"Over the past decades, satellite measurements of atmospheric sulphur dioxide (SO 2 ) have served a wide range of applications, from volcanology to air quality monitoring and climate assessment. In this paper, we present a 2007–2026 record of twice-daily global SO 2 vertical column abundances and SO 2 plume altitudes derived from measurements by the three Infrared Atmospheric Sounding Interferometer (IASI) instruments onboard the Metop platforms. Building upon earlier work, the algorithm has been refined and complemented with several new components. Most notably, the sensitivity of the algorithm to low SO 2 abundances and low-altitude plumes has been improved and the plume altitude retrieval now features enhanced performance for large SO 2 columns. Special care was taken to maximize consistency of the product over time and across the IASI instruments. In addition to SO 2 at the retrieved altitude, the dataset also includes SO 2 column retrievals assuming plume altitudes ranging from 1 to 60 km. These allow the construction of averaging kernels that can be used in model assimilation or to obtain more accurate column estimates when the plume altitude is constrained by independent information. The first part of the paper details the retrieval methodology and presents sensitivity and uncertainty analyses. The latter indicate that the retrieval uncertainty is smallest for plumes above 8 km and increases gradually toward lower altitudes, particularly within the first few kilometres and in atmospheres with a high water vapour content. Detailed comparisons with measurements from the CALIOP lidar indicate that plume altitudes are generally accurate to within 1–2 km. Column comparisons with TROPOMI in fresh volcanic plumes indicate reasonable agreement. In the second part of the paper, we present an overview of the 19-year dataset, providing detailed time series of SO 2 column abundances and mass-altitude profiles, with a focus on volcanic SO 2 . For each eruption with a plume mass exceeding 30 kt, we report the maximum atmospheric SO 2 mass, the mass below and above 8 km altitude, the peak plume altitude, and the altitude range containing 75 % of the mass. When available, the maximum mass is compared with estimates reported in the literature. The SO 2 altitude and column data from IASI/Metop-A, -B, and -C are available at https://doi.org/10.25326/870 (Clarisse and Franco, 2026a), https://doi.org/10.25326/869 (Clarisse and Franco, 2026b), and https://doi.org/10.25326/868 (Clarisse and Franco, 2026c), respectively.","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"39 1","pages":"6667-6706"},"PeriodicalIF":11.4,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933451","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":"Circum-Arctic Sediment PROvenance Database (CASPROD): a database of mineralogy and geochemistry for the Circum-Arctic surface sediments","authors":"Zhengquan Yao,Han Feng,Ruediger Stein,Yanguang Liu,Xuefa Shi,Yuri Vasilenko,Seung-Il Nam,Linsen Dong,Fengdeng Shi,Kunshan Wang,Zhihua Chen,Shuqing Qiao,Qiuling Li,Song Zhao,Xinyue Pei,Huiyu Guo,Yaru Liu","doi":"10.5194/essd-18-6649-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6649-2026","url":null,"abstract":"Arctic amplification is fundamentally reshaping the cryosphere, leading to accelerated sea-ice retreat, permafrost thaw, and intensified riverine discharge. These shifts collectively modify sediment source-to-sink dynamic processes in the Arctic Ocean. While surface sediments in this semi-enclosed basin integrate complex signals from diverse Eurasian and North American source regions, disentangling these provenance signatures requires a robust, multi-proxy framework that has historically been hampered by fragmented, heterogeneous datasets. Here, we present CASPROD (Circum-Arctic Sediment PROvenance Database), a standardized and high-resolution mineralogical and geochemical synthesis of Arctic surface sediments. The dataset integrates multi-proxy records from a broad spatial network, comprising 4308 sampling stations, including bulk sediment Sr-Nd isotopes ( n =175 stations), detrital zircon U-Pb ages ( n =4671 grains from 21 key stations), clay mineral assemblages ( n =1647 stations), and detrital mineral proportions ( n =2465 stations). These integrated proxies provide cross-validated sediment provenance constraints: Sr-Nd isotopes discriminate between ancient cratonic shields and juvenile orogenic belts; detrital zircon geochronology yields diagnostic age spectra distinguishing Eurasian versus North American crustal affinities; and clay and detrital mineralogy reflect different circum-Arctic sediment provenances, lithologies and transport processes. By synthesizing these diverse datasets, CASPROD delineates robust pan-Arctic spatial provenance domains and transport pathways. This database thus provides a critical benchmark for reconstructing palaeoceanographic, glacial, and sedimentary dynamics over geological timescales. CASPROD is freely available online (https://doi.org/10.6084/m9.figshare.31926927; Yao et al., 2026) in multiple machine-readable formats (e.g., tabular tables, GIS shapefiles, and GEOTIFF).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"59 1","pages":"6649-6665"},"PeriodicalIF":11.4,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933435","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 global hourly ISIMIP3 climate forcing dataset for impact modeling","authors":"Michel Bechtold,Benjamin Poschlod,Christian Otto,Jan Volkholz,Matthias Büchner,Florian Zabel","doi":"10.5194/essd-18-6637-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6637-2026","url":null,"abstract":"Sub-daily climate data are increasingly important for climate-impact assessments because many processes, such as heat stress, hydrological extremes, land–surface energy balance, and renewable-energy production, respond non-linearly to intra-day variability. Daily data miss short-duration events and obscure sub-daily inter-variable interactions, creating biases in impact estimates. To address these limitations and provide consistent forcing across sectors, we generated a global hourly climate dataset by temporally disaggregating the Inter-Sectoral Impact Model Intercomparison Project Phase 3 (ISIMIP3) daily climate archives using the Temporal Disaggregation Tool (Teddy). The approach uses analogue-based hourly profiles from the bias-corrected WFDE5 (WATCH Forcing Data methodology applied to ERA5) reanalysis, preserves daily mass and energy, and maintains temporal coherence between variables. We illustrate the utility of the hourly data with four applications using the MPI Earth System Model (MPI-ESM) under ScenarioMIP pathway SSP3–7.0: (1) the fraction of wet hours, revealing rainfall intermittency not captured by daily wet-day metrics; (2) the number of hours with dangerous heat-index values, capturing joint diurnal cycles of temperature and humidity; (3) hours with wind speeds suitable for onshore wind-power generation; and (4) photovoltaic power potential calculated from radiation, temperature, and wind speed at hourly resolution. We discuss the benefits of preserving inter-variable timing, along with limitations such as reduced spatial coherence at sub-daily scales and potential constraints under strong climate-change signals. The resulting hourly ISIMIP3 dataset provides a harmonized foundation for more realistic sub-daily climate-impact modeling across sectors. The dataset is openly available through the ISIMIP repository under the following DOIs: https://doi.org/10.48364/ISIMIP.736682 (Bechtold et al., 2026a) and https://doi.org/10.48364/ISIMIP.170328 (Bechtold et al., 2026b).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"15 1","pages":"6637-6648"},"PeriodicalIF":11.4,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933452","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":"Satellite-based inversion of global methane fluxes: capabilities and implications of GOSAT-2 measurements","authors":"Makoto Saito,Yosuke Niwa,Yukio Yoshida,Hiroshi Suto,Kei Shiomi,Akihide Kamei,Fumie Kataoka,Isamu Morino,Hibiki M. Noda,Hirofumi Ohyama,Tazu Saeki,Yu Someya,Hisashi Yashiro,Tsuneo Matsunaga","doi":"10.5194/essd-18-6565-2026","DOIUrl":"https://doi.org/10.5194/essd-18-6565-2026","url":null,"abstract":"Methane (CH 4 ) is a key greenhouse gas with a strong climate impact and a relatively short atmospheric lifetime, making accurate monitoring essential for mitigation strategies. Satellite observations provide global coverage and independent constraints on CH 4 emission estimates, and GOSAT-2, launched in 2018 as the successor to GOSAT, was designed to improve retrieval accuracy and enhance flux estimation. This study presents an evaluation of the GOSAT-2 Level 4 (G2L4) CH 4 flux product, supported by analysis of the underlying Level 2 (L2) XCH 4 retrievals, and summarizes key findings on global and regional CH 4 budgets. Using an atmospheric inversion framework, we generated G2L4 posterior CH 4 fluxes and assessed their consistency by comparing them with inversions constrained by alternative observational datasets, including GOSAT L2 retrievals and ground-based and aircraft measurements. GOSAT-2 achieved substantial improvements in observational coverage and data density compared to its predecessor, particularly in tropical and high-latitude regions. Posterior flux estimates derived from G2L4 are broadly consistent with global CH 4 budgets reported in synthesis studies, while prior-to-posterior differences reveal positive corrections in tropical regions and negative adjustments in several mid-latitude industrial areas. A preliminary sector-focused assessment further demonstrates the potential of GOSAT-2 to inform anthropogenic CH 4 emission evaluations in regions where such sources dominate. These findings highlight the value of GOSAT-2 observations for improving regional and global CH 4 emission estimates and underscore priorities for future improvements in retrieval algorithms, observation strategies, and integration with complementary datasets. The analysis-ready subsets of the GOSAT and GOSAT-2 data used in this study are available from Zenodo (https://doi.org/10.5281/zenodo.18883060, Saito, 2026).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"39 1","pages":"6565-6588"},"PeriodicalIF":11.4,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933436","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}