Centre for Environmental Data Analysis (CEDA)
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WCRP CMIP5: The EC-EARTH Consortium's EC-EARTH model output for the 10-year hindcast/prediction initialized in year 2000 (decadal2000) experiment. These data cover the following realms: atmos, land, ocean and seaIce; at the following frequencies: day and mon. The runs included the ensemble members: r10i1p1, r10i2p1, r1i1p1, r2i1p1, r3i1p1, r4i1p1, r5i1p1, r6i1p1, r7i1p1, r8i1p1, r8i2p1 and r9i1p1. The WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5). For details of the EC-EARTH Consortium members please see the linked reference to the EC-EARTH Consortium website on this record.
The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing daily estimates of surface air temperature since 1850 across the globe for the first time, by combining surface and satellite data using novel statistical techniques. The data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data.
This dataset contained a variety of forecast data from ECMWF, which supported observation campaigns. The variables, geo-temporal extent and other aspects were different for each campaign supported. The project supported were: adient, catlin, cloudmap2, crose, troccinox, itop, plume, slimcat, torch and vintersol. These data are no longer relevant, and were not reusable due the very specific access conditions that applied to each project.
This dataset contains zonal-mean atmospheric diagnostics computed from reanalysis datasets on pressure levels. Primary variables include temperature, geopotential height, and the three-dimensional wind field. Advanced diagnostics include zonal covariance terms that can be used to compute, for instance, eddy kinetic energy and eddy fluxes. Terms from the primitive zonal-mean momentum equation and the transformed Eulerian momentum equation are also provided. This dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP) project. The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future.
This dataset contains zonal-mean model-generated and diagnosed heating rates as potential temperature tendencies on pressure levels. The model-generated heating rates consist of total heating rates due to parameterized physics along with heating rates due to long-wave and short-wave radiative transfer, as generated during the model forecast step. The diagnosed heating rates are calculated from the zonal-mean atmospheric diagnostics (Zonal-mean reanalyses on pressure levels dataset) according to the zonal-mean thermodynamic equation. All heating rates are provided 6-hourly on identical horizontal and vertical grids as the dynamical variables included in Zonal-mean reanalyses on pressure levels dataset. However, the time axis of this dataset lags that of Zonal-mean reanalyses on pressure levels dataset by three hours. This dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP). The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future.
The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1) This project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. This dataset contains measurements from the Aerodyne Aerosol Chemical Speciation Monitor operated by Universidade de Sao Paulo (USP-ACSM)
The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1) This project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. This dataset contains humidity and aerosol measurements from the Manchester Hygroscopicity Tandem Differential Mobility Analyser (man-htdma)
This project was funded by the Natural Environment Research Council (NERC) with the grant reference - NE/I021012/1 - and was led by Dr Christopher Holloway (University of Reading). This dataset collection contains MetUM model data and observed convective aggregation data for the Tropics. This project aimed to clearly identify processes important for self-aggregation of convection in idealized models and then to test whether these processes, or different processes, are active in convective organization in nature. The second part of this goal was an open question in the field, and this fellowship has the potential to connect a rapidly expanding theoretical research area with ongoing efforts to improve the understanding and prediction of tropical variability. The focus on the Unified Model benefited weather and climate prediction in the UK by exchanging ideas with Met Office scientists who were directly involved in testing and improving the model.
The BT Tower is a 190-m-tall telecommunications tower situated in central London, UK (51°31′17.4″N, 0°8′20.04″W). Mean building height is 8.8 ± 3.0 m within 1−10 km of the tower and 5.6 ± 1.8 m for suburban London beyond this. This dataset collection contains O3 and NOx measurements made at the BT tower (T35 level) sampled from a height of approx 180 metres above the ground. The measurements were made using a TEI 49i analyser and TEI 42CTL analyser.
This dataset contains voltage data taken from the Canadian Riometer Array (CRA). The provided tables and datasets can be used to determine if the voltage time series of CRA riometers have characteristic spectral features. In addition, datasets are provided which have been collected from the Solar Wind Electron Proton Monitor (SWEPAM) and Magnetic Field Experiment (MAG) instruments aboard the Atmospheric Composition Explorer (ACE).