Geoscience Data Journal最新文献_第7页

Weather Rescue at Sea: Recovering Historical Weather Observations From 19th Century British Naval Ships 海上天气救援：恢复19世纪英国海军舰艇的历史天气观测

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-03-06 DOI: 10.1002/gdj3.70056

Praveen Teleti, Ed Hawkins, Clive Wilkinson

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引用次数: 0

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-03-06

引用次数: 0

Weather Rescue at Sea: Recovering Historical Weather Observations From 19th Century British Naval Ships 海上天气救援：恢复19世纪英国海军舰艇的历史天气观测

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-03-06 DOI: 10.1002/gdj3.70056

Praveen Teleti, Ed Hawkins, Clive Wilkinson

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引用次数: 0

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25

引用次数: 0

The Arctic Boreal Burned Area (ABBA) Product 北极北方森林烧伤区（ABBA）产品

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25 DOI: 10.1002/gdj3.70060

Dong Chen, Joanne V. Hall, Amanda Hoffman-Hall, Varada Shevade, Fernanda Argueta, Xiaoyu Liang, Tatiana Loboda

{"title":"The Arctic Boreal Burned Area (ABBA) Product","authors":"Dong Chen, Joanne V. Hall, Amanda Hoffman-Hall, Varada Shevade, Fernanda Argueta, Xiaoyu Liang, Tatiana Loboda","doi":"10.1002/gdj3.70060","DOIUrl":"10.1002/gdj3.70060","url":null,"abstract":"The Arctic Boreal Burned Area (ABBA) product is a region-specific burned area product designed for high northern latitudes (HNL), including boreal forests and Arctic tundra. Developed to address limitations of global products like MODIS MCD64A1, ABBA uses MODIS data to calculate the differenced Normalised Burn Ratio (dNBR) and incorporates vegetation cover thresholds to identify burned areas. It includes a spring composite modification for high-latitude tiles to capture late-season fires obscured by snow. ABBA achieves higher accuracy (87.2%) compared to MCD64A1 (82.7%), with lower commission and omission errors, enabling more reliable detection of burned areas. Between 2002 and 2022, ABBA mapped over 2 million km2 of burned area, significantly more than MCD64A1. Its applications include improving wildfire emission estimates, studying climate feedbacks like albedo changes and assessing ecological impacts such as permafrost thaw and vegetation regrowth. ABBA is available via the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"13 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Arctic Boreal Burned Area (ABBA) Product 北极北方森林烧伤区（ABBA）产品

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25 DOI: 10.1002/gdj3.70060

Dong Chen, Joanne V. Hall, Amanda Hoffman-Hall, Varada Shevade, Fernanda Argueta, Xiaoyu Liang, Tatiana Loboda

{"title":"The Arctic Boreal Burned Area (ABBA) Product","authors":"Dong Chen, Joanne V. Hall, Amanda Hoffman-Hall, Varada Shevade, Fernanda Argueta, Xiaoyu Liang, Tatiana Loboda","doi":"10.1002/gdj3.70060","DOIUrl":"https://doi.org/10.1002/gdj3.70060","url":null,"abstract":"The Arctic Boreal Burned Area (ABBA) product is a region-specific burned area product designed for high northern latitudes (HNL), including boreal forests and Arctic tundra. Developed to address limitations of global products like MODIS MCD64A1, ABBA uses MODIS data to calculate the differenced Normalised Burn Ratio (dNBR) and incorporates vegetation cover thresholds to identify burned areas. It includes a spring composite modification for high-latitude tiles to capture late-season fires obscured by snow. ABBA achieves higher accuracy (87.2%) compared to MCD64A1 (82.7%), with lower commission and omission errors, enabling more reliable detection of burned areas. Between 2002 and 2022, ABBA mapped over 2 million km2 of burned area, significantly more than MCD64A1. Its applications include improving wildfire emission estimates, studying climate feedbacks like albedo changes and assessing ecological impacts such as permafrost thaw and vegetation regrowth. ABBA is available via the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"13 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DASNordicSLR—A Regional Dataset of Sea Level Projections for Northern Europe dasnordicslr -北欧海平面预估区域数据集

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25 DOI: 10.1002/gdj3.70065

Corinna Jensen, Frank Janssen, Tim Kruschke

{"title":"DASNordicSLR—A Regional Dataset of Sea Level Projections for Northern Europe","authors":"Corinna Jensen, Frank Janssen, Tim Kruschke","doi":"10.1002/gdj3.70065","DOIUrl":"10.1002/gdj3.70065","url":null,"abstract":"Sea level rise is an inevitable consequence and one of the most significant threats posed by climate change, increasing the risk of flooding in low-lying areas along the German coast. Based on the IPCC 6th Assessment Report (AR6) projections, we aimed to deliver improved projections of relative sea-level change for Northern Europe's coastal regions. These projections are available as spatial data up to 2150. While most drivers of sea level change operate on a continental or global scale, vertical land motion is a regional factor—particularly relevant in Northern Europe—resulting from glacial isostatic adjustment and local processes. By combining the IPCC projections of absolute sea level change with a new, high-resolution vertical land motion model for Fennoscandia, an optimised set of projections for relative sea level change for the North Sea and Baltic Sea was developed. In this context, the spatial resolution changes from the 1 × 1 grid commonly used in AR6 datasets to the finer 1/6 × 1/12 grid of the regional land motion model. This results in local differences in sea level rise by 2100 up to −200 mm to +500 mm within the domain. This dataset represents a contribution to the DAS core service ‘climate and water’, the operational climate service operated by four federal authorities under the umbrella of the German Federal Ministry of Transport.","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"13 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25

引用次数: 0

DASNordicSLR—A Regional Dataset of Sea Level Projections for Northern Europe dasnordicslr -北欧海平面预估区域数据集

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-25 DOI: 10.1002/gdj3.70065

Corinna Jensen, Frank Janssen, Tim Kruschke

{"title":"DASNordicSLR—A Regional Dataset of Sea Level Projections for Northern Europe","authors":"Corinna Jensen, Frank Janssen, Tim Kruschke","doi":"10.1002/gdj3.70065","DOIUrl":"10.1002/gdj3.70065","url":null,"abstract":"Sea level rise is an inevitable consequence and one of the most significant threats posed by climate change, increasing the risk of flooding in low-lying areas along the German coast. Based on the IPCC 6th Assessment Report (AR6) projections, we aimed to deliver improved projections of relative sea-level change for Northern Europe's coastal regions. These projections are available as spatial data up to 2150. While most drivers of sea level change operate on a continental or global scale, vertical land motion is a regional factor—particularly relevant in Northern Europe—resulting from glacial isostatic adjustment and local processes. By combining the IPCC projections of absolute sea level change with a new, high-resolution vertical land motion model for Fennoscandia, an optimised set of projections for relative sea level change for the North Sea and Baltic Sea was developed. In this context, the spatial resolution changes from the 1 × 1 grid commonly used in AR6 datasets to the finer 1/6 × 1/12 grid of the regional land motion model. This results in local differences in sea level rise by 2100 up to −200 mm to +500 mm within the domain. This dataset represents a contribution to the DAS core service ‘climate and water’, the operational climate service operated by four federal authorities under the umbrella of the German Federal Ministry of Transport.","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"13 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset DCENT-I：温度数据集动态一致集合的全局填充扩展

IF 2.4 3区地球科学

Geoscience Data Journal Pub Date : 2026-02-12 DOI: 10.1002/gdj3.70054

Duo Chan, Steven C. Chan, Joseph T. Siddons, Archie Cable, Agnieszka Faulkner, Richard C. Cornes, Elizabeth C. Kent, Geoffrey Gebbie, Peter Huybers

{"title":"DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset","authors":"Duo Chan, Steven C. Chan, Joseph T. Siddons, Archie Cable, Agnieszka Faulkner, Richard C. Cornes, Elizabeth C. Kent, Geoffrey Gebbie, Peter Huybers","doi":"10.1002/gdj3.70054","DOIUrl":"10.1002/gdj3.70054","url":null,"abstract":"A spatially infilled Dynamically Consistent Ensemble of surface Temperature (DCENT-I) has been created by infilling land-air and sea-surface temperatures from DCENT using ordinary kriging with anisotropic and heterogeneous kernels. By incorporating air temperature anomalies over sea-ice areas, DCENT-I provides spatially complete monthly temperature fields at 5° resolution from 1850 to the present (currently the end of 2024) as a 200-member ensemble. Uncertainty estimates that account for the need to infill for missing observations are made using a Multivariate Gaussian Process, and these are consistent with estimates derived from masking climate model simulations. The use of anisotropic and heterogeneous kernels leads to a reconstruction of El Niño variability whose spatial pattern and temporal variance are generally consistent throughout the record. As compared with taking the unfilled average, infilling increases the global mean surface temperature (GMST) warming estimate over 2005–2024 relative to a 1850–1900 baseline from 1.09 [0.96, 1.18] (95% range across members) to 1.17 [1.05, 1.26]°C, largely because of infilling in rapidly warming high-latitude regions. Compared with HadCRUT5, GISTEMP v4, NOAA Global Temp v6, and Berkeley Earth, DCENT-I shows a steadier and slightly faster GMST warming trend, reflecting the bias-adjustments inherited from DCENT.","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"13 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146216990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0