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climatologyMeteorologyAtmosphere

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  • Isoprene flux and concentration measurements made from Auchencorth Moss during the summer of 2015. Isoprene concentrations were measured using a proton transfer reaction mass spectrometer (PTR-MS) and fluxes were calculated using the eddy covariance technique. The dataset includes the supporting meteorology including air temperature, photosynthetically active radiation, wind speed, wind direction, friction velocity, sensible heat flux. Full details about this dataset can be found at https://doi.org/10.5285/f78b0f29-3df4-4a6c-a096-a1c73828b0a0

  • Data for Figure 3.2 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.2 shows changes in surface temperature for different paleoclimates. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has three subpanels, the data provided for all panels in subdirectories named panel_a, panel_b, panel_c --------------------------------------------------- List of data provided --------------------------------------------------- For panel (a): - PMIP3 global temperature anomalies over continents and oceans reconstruction sites - PMIP4 CMIP6 global temperature anomalies over continents and oceans reconstruction sites - PMIP4 non-CMIP6 global temperature anomalies over continents and oceans reconstruction sites - Tierney 2020 reconstructions of marine temperature - Cleator 2020 reconstructions of continental temperature For panel (b): - CMIP5 temperature data for paleoclimate periods - CMIP6 temperature data for paleoclimate periods - non-CMIP temperature data for paleoclimate periods - Instrumental observational and observations from reconstructions For panel (c): - Volcanic forcing from TS17, CU12, GRA08 - CMIP6 GMST anomaly with respect to 1850-1900 modelled with TS17 volcanic forcing - CMIP5 GMST anomaly with respect to 1850-1900 modelled with CU12 volcanic forcing - CMIP5 GMST anomaly with respect to 1850-1900 modelled with GRA08 volcanic forcing --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/temperature_anomalies_scatter_points.csv relates to the scatter points and their standard deviation for panel (a) - For panel (b) the datasets are stored as following panel_b/temperature_{color}_{marker}_{period}_{model_group}_{additional_info}.csv and relates to the scatter points for panel (b). - For panel (c) the data is stored in panel_c/gmst_changes_paleo_volcanic_forcings.csv and relates to red, green, blue and black lines on the panel as well as grey shadings. Additional information about data provided in relation to figure in files headers. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. CMIP5 is the fifth phase of the Coupled Model Intercomparison Project. PMIP4 is the Paleoclimate Modelling Intercomparison Project phase 4 PMIP3 is the Paleoclimate Modelling Intercomparison Project phase 3 --------------------------------------------------- Temporal Range of Paleoclimate Data --------------------------------------------------- This dataset covers a paleoclimate timespan from 3.3Ma to 6ka (3.3 million years ago to 6 thousand years ago). --------------------------------------------------- Notes on reproducing the figure from the provided data. --------------------------------------------------- For panel (a) the error bar should be plotted as anomalies from columns 2/4 +/- standard deviation. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo.

  • The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. Snowf or snowfall is the snowfall rate based on the GPCC bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Snowf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this snowfall dataset is available from the EIDC. These snowfall datasets contain snowfall data only and need to be combined with the respective WFD rainfall datasets to obtain precipitation data.

  • These files represent the model build used to generate postcode level concentrations to estimate Aspergillus fumigatus exposure from outdoor composting activities in England between 2005 and 2014. Each file, named after the nearest SCAIL-Agriculture validated meteorological station used to model the outputs, contains modelled concentrations at composting sites within 4km of each composting site. These files, presented as.txt, are the .APL files used to model bioaerosol dispersion from every composting site in England, using ADMS 5. To use this file, please convert the .txt file extension to .APL and upload into ADMS. From there, press run. Model runs are likely to generate over 40GB of data per model run. The work was supported by the Natural Environment Research Council grants ((NE/P010806/1 and NE/M011631/1). Full details about this dataset can be found at https://doi.org/10.5285/9f1b307b-9b47-4a11-8e5b-e14008ad0032

  • Data comprise relative humidity measured at an automatic monitoring buoy located in Blelham Tarn, UK. Data are provided from January 2012 to December 2019. Hourly averages are given, calculated from measurements taken every four minutes. All data is given in GMT (Greenwich Mean Time). This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/3df05e85-2c56-4bd9-9918-44b760e20b2e

  • Hydrological and meteorological data were collected for three plots (each 50 x 50 m in size) near Andasibe village in the Corridor Ankeniheny-Zahamena (CAZ) in eastern Madagascar. The plots differ in terms of land cover: semi-mature forest, reforested tree fallow (i.e., young secondary forest), and degraded grassland. The plots are located within 2.5 km from each other. See the supporting documentation for detailed information on the plots. Data collection continued for one year (October 2014-September 2015) at each plot and included micrometeorological data (rainfall, temperature, relative humidity, wind speed), soil moisture and overland flow, and for the two forested plots also throughfall, stemflow and sapflow. Full details about this dataset can be found at https://doi.org/10.5285/5d080fef-613a-4f24-a613-b249ccdd12bf

  • Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1961 to 2012. [1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre doi:10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902 [2] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. Full details about this dataset can be found at https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f

  • [THIS DATASET HAS BEEN WITHDRAWN]. Gridded potential evapotranspiration calculated from HadUK-Grid gridded observed meteorological data at 1 km resolution over the United Kingdom for the years 1969-2020. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2 d-1) and daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1). The units kg m-2 d-1 are equivalent to mm d-1. The data are provided in gridded netCDF files. There is one file for each variable, for each calendar month. These data were generated as part of NERC grant NE/S017380/1 (Hydro-JULES: Next generation land surface and hydrological prediction.) Full details about this dataset can be found at https://doi.org/10.5285/470d9bf9-8c82-487c-956e-f15f9d8aac64

  • This dataset includes six sets of model output from JULES/IMOGEN simulations. Each set includes output from JULES (the Joint UK Land Environment Simulator) run with 34 climate change patterns from 2000-2099. The outputs provide carbon stocks and variables related to the surface energy budget to understand the implications of land-based climate mitigation. Full details about this dataset can be found at https://doi.org/10.5285/333eb066-be07-4209-9dfe-2d9d18560de6

  • This dataset presents nationally consistent simulations of available precipitation (rainfall + snowmelt) for Great Britain. These include simulations driven by observational data covering January 1961 – December 2018 and simulations driven by Regional Climate Model (RCM) projections covering December 1980 - November 2080. Both are provided as gridded data at 1km resolution. The observed input data was HadUK-Grid 1km daily precipitation and temperature. The RCM input data was a 12-member perturbed parameter ensemble from the UK Climate Projections 2018 (UKCP18), provided at a ‘Regional’ 12km resolution aligned with the GB national grid. A simple snowmelt module was used to transform these time-series of precipitation and temperature into available precipitation. This data was developed for, and used within, the Enhanced Future Flows and Groundwater (eFLaG) project (Hannaford et al., 2022). The eFLaG project was established through a partnership project funded by the Met Office led component of the Strategic Priorities Fund Climate Resilience Programme under contract P107493 (CR19_4 UK Climate Resilience). Full details about this dataset can be found at https://doi.org/10.5285/755e0369-f8db-4550-aabe-3f9c9fbcb93d