12 research outputs found

    Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

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    The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

    Spark experiments and photochemical simulations to identify lightning signatures in planetary atmospheres (dataset)

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    This dataset includes the data underlying the publication "The effect of lightning on the atmospheric chemistry of exoplanets and potential biosignatures" (Barth et al. 2024, Astronomy & Astrophysics) and consists of 3 parts: (1) Experimental results from spark discharge experiments performed in the St Andrews Isotope Geochemistry lab (StAIG): The experimental set up was built by Patrick Barth and Eva E. Stüeken, the experiments were conducted by Patrick Barth, the analysis was conducted by Patrick Barth and Jon Telling, and the data was analysed by Patrick Barth, Eva E. Stüeken, Christiane Helling, and Jon Telling. Analysis of most gaseous products was carried out with a quadrupole mass spectrometer (Hiden Analytical ExQ Quantitative Gas Analyser) in St Andrews. N2O and CH4 were analysed with a Thermo Fisher gas chromatograph (Trace Ultra) in St Andrews. Analysis of CO was performed with an SRI 8610C gas chromatograph at the School of Natural and Environmental Sciences, Newcastle University. Aqueous nitrite and nitrate were analysed with a Thermo Scientific Dionex ICS-6000 ion chromatograph; ammonium, urea, and cyanide were analysed with colorimetric methods; all in St Andrews. (2) Equilibrium chemistry calculations for the gas-mixtures in the spark experiments, performed (with GGChem) and analysed by Patrick Barth. (3) Photochemical simulations of the atmospheres of terrestrial exoplanets with lightning-produced NO and CO (with ATMOS) and simulated spectra (with SMART): Performed by Edward W. Schwieterman, analysed by Edward W. Schwieterman, Patrick Barth, and Christiane Helling

    Worldwide variations in artificial skyglow

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    Despite constituting a widespread and significant environmental change, understanding of artificial nighttime skyglow is extremely limited. Until now, published monitoring studies have been local or regional in scope, and typically of short duration. In this first major international compilation of monitoring data we answer several key questions about skyglow properties. Skyglow is observed to vary over four orders of magnitude, a range hundreds of times larger than was the case before artificial light. Nearly all of the study sites were polluted by artificial light. A non-linear relationship is observed between the sky brightness on clear and overcast nights, with a change in behavior near the rural to urban landuse transition. Overcast skies ranged from a third darker to almost 18 times brighter than clear. Clear sky radiances estimated by the World Atlas of Artificial Night Sky Brightness were found to be overestimated by ~25%; our dataset will play an important role in the calibration and ground truthing of future skyglow models. Most of the brightly lit sites darkened as the night progressed, typically by ~5% per hour. The great variation in skyglow radiance observed from site-to-site and with changing meteorological conditions underlines the need for a long-term international monitoring program

    FLUXNET-CH4: A global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands (Appendix B and Figure 3)

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    This dataset contains metadata for methane flux sites in Version 1.0 of FLUXNET-CH4. The dataset also has seasonality parameters for select freshwater wetlands, which were extracted from the raw datasets published at https://fluxnet.org/data/fluxnet-ch4-community-product/. These data are used to analyze global methane flux seasonality patterns in the paper "FLUXNET-CH4: A global, multi-ecosystem dataset and analysisof methane seasonality from freshwater wetlands" by Delwiche et al

    Multi-laboratory compilation of atmospheric carbon dioxide data for the year 2024; obspack_co2_1_NRT_v10.0_2024-09-30

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    This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products

    Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957-2023; obspack_co2_1_GLOBALVIEWplus_v10.0_2024-09-26

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    This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products. This product includes 625 atmospheric carbon dioxide datasets derived from observations made by 79 laboratories from 28 countries. Data for the period 1957-2023 (where available) are included

    Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957-2023; obspack_co2_1_GLOBALVIEWplus_v10.0_2024-09-26

    No full text
    This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products. This product includes 625 atmospheric carbon dioxide datasets derived from observations made by 79 laboratories from 28 countries. Data for the period 1957-2023 (where available) are included

    Multi-laboratory compilation of atmospheric carbon dioxide data for the year 2023-2024; obspack_ch4_1_NRT_v6.2_2024-06-27

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    This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products

    Multi-laboratory compilation of atmospheric carbon dioxide data for the years 2023-2024; obspack_co2_1_NRT_v9.3_2024-06-27

    No full text
    This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products
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