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ShareScore release 0.9.0
Dataset results
29 results for “global wetlands”
LPJ-EOSIM L2 Global Simulated Daily Wetland Methane Flux Low Latency V001
The Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model estimates global wetland methane (CH4) emissions using simulated wetland extent and characteristics including soil moisture, temperature, and carbon content. For this dataset, wetlands are defined as land areas that are either permanently or seasonally saturated, excluding small ponds, lakes, and coastal wetlands. These wetland CH4 flux data will be used to support the United States Greenhouse Gas Center ([GHGC](https://earth.gov/ghgcenter)) and its mission to study natural GHG fluxes. The model will also be used to facilitate improved rapid detection and attribution of climate-carbon feedback and help with strategic placement of measurement campaigns and monitoring systems as they relate to predicted biogeochemical hotspots. The LPJ-EOSIM Level 2 Global Simulated Daily Wetland Methane Flux Low Latency (LPJ_EOSIM_L2_DCH4E_LL) Version 1 data product provides simulated daily wetland CH4 flux globally at a spatial resolution of 0.5 degrees. The daily data are presented in four Cloud Optimized GeoTIFF (COG) files: two based on the forcing datasets Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5), and two containing the mean and standard deviation values. Due to the latency of global carbon dioxide (CO2) concentration estimates required for computation of LPJ-EOSIM simulated daily CH4 flux data products, low latency (LPJ_EOSIM_L2_DCH4E_LL) and high latency ([LPJ_EOSIM_L2_DCH4E](https://doi.org/10.5067/Community/LPJ-EOSIM/LPJ_EOSIM_L2_DCH4E.001)) collections are available. Low latency data are delivered on a two-month cadence throughout the year. Granules will also be updated as new CO2 input data become available. Please refer to Section 2.0.1 of the User Guide for a more detailed explanation of CO2 estimate inputs and timing for scheduled updates to the collections.
LPJ-EOSIM L2 Global Simulated Daily Wetland Methane Flux V001
The Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model estimates global wetland methane (CH4) emissions using simulated wetland extent and characteristics including soil moisture, temperature, and carbon content. For this dataset, wetlands are defined as land areas that are either permanently or seasonally saturated, excluding small ponds, lakes, and coastal wetlands. These wetland CH4 flux data will be used to support the United States Greenhouse Gas Center ([GHGC](https://earth.gov/ghgcenter)) and its mission to study natural GHG fluxes. The model will also be used to facilitate improved rapid detection and attribution of climate-carbon feedback and help with strategic placement of measurement campaigns and monitoring systems as they relate to predicted biogeochemical hotspots. The LPJ-EOSIM Level 2 Global Simulated Daily Wetland Methane Flux (LPJ_EOSIM_L2_DCH4E) Version 1 data product provides simulated daily wetland CH4 flux globally at a spatial resolution of 0.5 degrees. The daily data are presented in four Cloud Optimized GeoTIFF (COG) files: two based on the forcing datasets Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5), and two containing the mean and standard deviation values. Due to the latency of global carbon dioxide (CO2) concentration estimates required for computation of LPJ-EOSIM simulated daily CH4 flux data products, low latency ([LPJ_EOSIM_L2_DCH4E_LL](https://doi.org/10.5067/Community/LPJ-EOSIM/LPJ_EOSIM_L2_DCH4E_LL.001)) and high latency (LPJ_EOSIM_L2_DCH4E) collections are available. High latency data in this collection will be delivered around May of each year when National Oceanic and Atmospheric Administration’s (NOAA) Global Monitoring Laboratory (GML) publishes the previous year’s CO2 concentration and will have a lag of at least 5 months (January-May), and at most 17 months (January of the current year to May of the next year). Please refer to Section 2.0.1 of the User Guide for a more detailed explanation of CO2 estimate inputs and timing for scheduled updates to the collections.
Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016
This dataset contains four alternative digital elevation models (DEMs) at 1 m resolution and model performance statistical metrics for the Global Change Research Wetland (GCReW) site on the Rhode River, a tributary of the Chesapeake Bay in Maryland, USA, for the year 2016. Three DEMs were created by using different strategies for correcting positive biases in Light Detection and Ranging (LiDAR)-based DEMs that are common in tidal wetlands. These included (1) applying a single average offset based on a literature review, (2) using the LiDAR Elevation Correction with NDVI (LEAN)-method, and (3) applying plant community-specific offsets using a local vegetation cover map. Existing LiDAR data at 1 m resolution collected in 2011 was the basis for these DEMs. The fourth DEM was created by using Empirical Bayesian Kriging to extrapolate between measured ground points. The elevation is provided in meters relative to the North American Vertical Datum of 1988 (NAVD 88). To calibrate the four approaches, the elevation of the entire marsh complex was surveyed at 20 m x 20 m resolution to document the distribution of elevation relative to tidal datums from a single year. Two Trimble R8 real-time kinematic (RTK) GPS receivers were used to survey 525 points over the complex from July 26, 2016, to August 15, 2016. Relative plant cover was also documented. Tidal datums were calculated from the nearby Annapolis, MD tidal gauge located 13 km from GCReW.
LPJ-EOSIM L2 Global Simulated Monthly Wetland Methane Flux Low Latency V001
The Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model estimates global wetland methane (CH4) emissions using simulated wetland extent and characteristics including soil moisture, temperature, and carbon content. For this dataset, wetlands are defined as land areas that are either permanently or seasonally saturated, excluding small ponds, lakes, and coastal wetlands. These wetland CH4 flux data will be used to support the United States Greenhouse Gas Center ([GHGC](https://earth.gov/ghgcenter)) and its mission to study natural GHG fluxes. The model will also be used to facilitate improved rapid detection and attribution of climate-carbon feedback, and in strategic placement of measurement campaigns and monitoring systems as they relate to predicted biogeochemical hotspots. The LPJ-EOSIM L2 Global Simulated Monthly Wetland Methane Flux Low Latency (LPJ_EOSIM_L2_MCH4E_LL) Version 1 data product provides simulated monthly wetland CH4 flux globally at a spatial resolution of 0.5 degrees. The monthly simulation data contains aggregate versions of the daily LPJ-EOSIM L2 Global Simulated Daily Wetland Methane Flux Low Latency ([LPJ_EOSIM_L2_DCH4E_LL](https://doi.org/10.5067/Community/LPJ-EOSIM/LPJ_EOSIM_L2_DCH4E_LL.001)) Version 1 data. The monthly data are presented in four Cloud Optimized GeoTIFF (COG) files: two based on the aggregated daily forcing datasets Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5), and two containing the mean and standard deviation values calculated from the monthly aggregate data. Due to the latency of global carbon dioxide (CO<sub>2</sub>) concentration estimates required for computation of LPJ-EOSIM simulated monthly CH4 flux data products, low latency (LPJ_EOSIM_L2_MCH4E_LL) and high latency ([LPJ_EOSIM_L2_MCH4E](https://doi.org/10.5067/Community/LPJ-EOSIM/LPJ_EOSIM_L2_MCH4E.001)) collections are available. Low latency data are delivered on a two-month cadence throughout the year. Granules will also be updated as new CO2 input data become available. Please refer to Section 2.0.1 of the User Guide for a more detailed explanation of estimated CO2 inputs and timing for scheduled updates to the collections.
CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.0)
This data set provides global monthly wetland methane (CH4) emissions and uncertainty data products derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies. The data are at 0.5 by 0.5-degree resolution. Two model output data products are included in WetCHARTs v1.0: an output from the full ensemble for 2009-2010 and an output from a limited subset for 2001-2015. The intended use of the products is as a process-informed wetland CH4 emission and uncertainty data set for atmospheric chemistry and transport modelling (WetCHARTs).
CMS: Global 0.5-deg Wetland Methane Emissions and Uncertainty (WetCHARTs v1.3.3)
This dataset provides global monthly wetland methane (CH4) emissions estimates at 0.5 by 0.5-degree resolution for the period 2001-01-01 to 2022-08-31 that were derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies that encompass the main sources of uncertainty in wetland CH4 emissions. There are 18 model configurations. WetCHARTs v1.3.3 is an updated product of WetCHARTs v1.3.1 dataset. The intended use of this product is as a process-informed wetland CH4 emission data set for atmospheric chemistry and transport modeling. Users can compare estimates by model configuration to explore variability and sensitivity with respect to ensemble members. The data are provided in netCDF format.
Historical and Future Global Wetland Methane Emissions from 1979 to 2100
<p>This dataset supports the manuscript "Quantifying Global Wetland Methane Emissions with In Situ Methane Flux Data and Machine Learning Approaches" currently under review. Before reusing this data, please contact the first author (chen4371@purdue.edu) for citations and recent updates.</p>
Global wetland CH4 emissions for 2000-2021
<p>This repository contains all the data needed to reproduce the results in Zhang et al., 2023. Zhang Z., Poulter, B., Feldman A., Ying Q., Ciais P., Peng S., Li X., 2023. Recent intensification of wetland methane feedback, in revision in Nature Climate Change. The files are two estimates for global wetland methane emissions simulated by LPJ-wsl model for the period of 2000-2021 and a mask used for defining regions. The ground-based input dataset is a monthly climatic observation based on meteorological stations developed by Climatic Research Unit (CRU), University of East Anglia. The reanalysis-based climate dataset is a daily climatic dataset from 1 hourly reanalysis Modern-Era Retrospective analysis for Research and Applications Version2 (MERRA2). The unit of wetland CH4 emissions is g CH4 mon-1 per 0.5deg cell area. For more details about LPJ-wsl model, see Zhang et al., (2017, 2018).</p> <p>References:</p> <p>Zhang, Z., Zimmermann, N.E., Stenke, A., Li, X., Hodson, E.L., Zhu, G., Huang, C., Poulter, B., 2017. Emerging role of wetland methane emissions in driving 21st century climate change. Proceedings of the National Academy of Sciences 114, 9647–9652. <a href="https://doi.org/10.1073/pnas.1618765114">https://doi.org/10.1073/pnas.1618765114</a></p> <p>Zhang, Z., Zimmermann, N.E., Calle, L., Hurtt, G., Chatterjee, A., Poulter, B., 2018. Enhanced response of global wetland methane emissions to the 2015–2016 El Niño-Southern Oscillation event. Environmental Research Letters 13, 074009. <a href="https://doi.org/10.1088/1748-9326/aac939">https://doi.org/10.1088/1748-9326/aac939</a></p>
A water-table-dependent net warming effect of global wetlands from potent greenhouse gases
<p>A database of the annual greenhouse gase fluxes across global wetlands. In total, the database comprised 2,455 observations of annual net ecosystem exchange of CO<sub>2 </sub>(NEE; net gaseous CO<sub>2</sub> exchange between land and atmosphere), 2,342 observations of annual CH<sub>4 </sub>fluxes and 850 observations of annual N<sub>2</sub>O fluxes.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.