The GBS (Global Broadcast Service) dataset is a series of radio attenuation measurements made at three sites in the UK: Chilbolton and Sparsholt, both in southern UK, and Dundee in Scotland. The aim of the experiment was to make long term measurements of the signal strength received from a 20.7GHz beacon on the US Department of Defense satellite UFO-9 at multiple sites, in order to determine whether the use of site diversity as a fade mitigation technique would be effective. The dataset spans a period of 3 years, from August 2003 to August 2006 with signal attenuation sampled once per second. This dataset is cited in: S. A. Callaghan, J. Waight, J.L.Agnew, C. J. Walden, C.L.Wrench , S. Ventouras “The GBS dataset: measurements of satellite site diversity at 20.7 GHz in the UK”, Geoscience Data Journal, 17 March 2013, DOI: 10.1002/gdj3.2

Data from the CSIRO Mark 3.0 simulations

This dataset comprises of model output from 25 runs (5 case studies, with 5 runs in each case study) of the Met Office Unified Model (MetUM) in realistic limited-area one-way nesting mode. The output data include values for model fields (e.g. temperature, humidity, winds, pressure) at model grid points over regularly spaced time intervals. These runs were used in a paper on convective aggregation: Holloway (2017, Journal of Advances in Modeling Earth Systems). All runs use the ""New Dynamics"" dynamical core, MetUM version 7.5, as described in Holloway (2017). The simulations are run with 4-km horizontal grid spacing. They all have a horizontal domain size of 20 degrees latitude X 20 degrees longitude (or 574 X 574 grid points, although the grid points in the outer 8 points on all sides, the ""rim"", should be discarded before analysis), with 70 vertical levels. All runs are initialised from operational analyses from the European Centre for Medium-Range Weather Forecasting (ECMWF) taken from actual cases. Lateral boundary conditions are comprised of 6-hourly ECMWF analyses, and the model is relaxed to these conditions in and near the outer rim as described in Holloway (2017). Sea surface temperatures (SST) are taken from the initial ECMWF analysis and are held constant in time for the 15 days (but are not constant in space). There are small land regions in four of the case studies which include an interactive land surface model. Each simulation was run for 15 days. The model output includes hourly model-level prognostic variables (temperature, specific humidity, pressure, wind components, liquid water, ice water) as well as some model-level increments to temperature and specific humidity. There are also many fields containing surface variables and fluxes (averaged over each hour or every 15 minutes). Note that the ""control"" simulations have slightly more available data than the other four runs in each of the five case studies. The five case studies are centred on the equator and occur between 2008 and 2010. See Holloway (2017) for further details: http://onlinelibrary.wiley.com/doi/10.1002/2017MS000980/full For each case, there are five runs: 1) control (interactive radiation, interactive surface fluxes) 2) constant radiative cooling run (radiative cooling over sea points is prescribed from domain-time mean of control run) 3) constant surface flux run (surface latent and sensible heat fluxes over sea points are prescribed from domain-time mean of control run) 4) constant radiative cooling and constant surface flux run (combination of 2 and 3 above) 5) no rain evaporation run (rain is prevented from evaporating in the atmosphere)"

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 Shoeburyness Field Trial: Investigation of Meteorological Effects on the Sound Propagation from a Helicopter Operating Near a Land Sea Interface Project was a QinetiQ applied research programme 3G23, funded by Ministry of Defence (MOD). The project duration was from April 2004 to March 2007 and had the aim to investigate noise modelling of helicopters with regard to long range sound propagation. The trial sought to understand more fully the meteorological effects on sound propagation over a land sea interface. This dataset collection contains measurements from the automatic weather station, which was used to gather standard meteorological measurements. The Universities Facility for Atmospheric Measurement (UFAM) automatic weather station was operated by the University of Salford.

Large data sets used to study the impact of anthropogenic climate change on the 2013/14 floods in the UK are provided. Data consists of perturbed initial conditions simulations using the Weather@Home regional climate modelling framework. Two different base conditions, Actual, including atmospheric conditions (anthropogenic greenhouse gases and human induced aerosols) as at present and Natural, with these forcings all removed are available. The data set is made up of 13 different ensembles (2 actual and 11 natural) with each having more than 7500 members. The data is available as NetCDF V3 files with their content representing an individual month of simulation. Data within that includes diagnostics written at daily, weekly and monthly within the period of interest (1st Dec 2013 to 15th February 2014) for both a specified European region at a 50km horizontal resolution and globally at N96 resolution. The data were generated in support of the European FP7 project - EUropean CLimate and weather Events: Interpretation and Attribution (EUCLEIA). Full details are available within Sparrow et al 2017, Nature Scientific Data.

Data for Figure 3.7 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.7 shows regression coefficients and corresponding attributable warming estimates for individual CMIP6 models. --------------------------------------------------- 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 four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains information on global temperature attributable warming (2010-2019 relative to 1850-1900) from CMIP6 models:  - Regression coefficients for two way regression (2010-2019 relative to 1850-1900) - Regression coefficients for three way regression (2010-2019 relative to 1850-1900) - Attributable warming for two way regression (2010-2019 relative to 1850-1900) - Attributable warming for three way regression (2010-2019 relative to 1850-1900) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- - panel_a/regression_coeff_two_way_regression.csv has data for brown and green crosses - panel_b/regression_coeff_three_way_regression.csv has data for grey, green and blue crosses - panel_c/attributable_warming_two_way_regression.csv has data for brown and green crosses - panel_d/attributable_warming_three_way_regression.csv has data for grey, green and blue crosses Details about the data provided in relation to the figure in the header of every file. CMIP6 is the sixth phase of the Coupled Model Intercomparison Project. --------------------------------------------------- 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 Global Ozone Monitoring Experiment (GOME) was an instrument aboard ERS-2. The main scientific objective of the GOME mission is to measure the global distribution of ozone and several trace gases which play an important role in the ozone chemistry of the Earth's stratosphere and troposphere, for example, NO2, BrO, OClO, and SO2. This dataset contains version 1.2 ozone profiles derived by the Remote Sensing Group (RSG) at the STFC Rutherford Appleton Laboratory, Oxfordshire, UK, as part of the National Centre for Earth Observation (NCEO). These were derived from radiances measured by the GOME on-board ERS-2. The collection also includes total column ozone, column BrO, and column NO2 as well as cloud heights derived from the Along Track Scanning Radiometer (ATSR), which are included to aid interpretation of the ozone profiles.

Cloud base and backscatter data from the Met Office's Exeter Cl31 ceilometer located at Exeter, Devon. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

"To what extent was the Little Ice Age a result of a change in the thermohaline circulation?" project. This was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Joint International Round - NE/C509507/1 - Duration 1 Aug 2005 - 31 Jul 2008) led by Dr Tim Osborn of the University of East Anglia, with co-investigators at the University of East Anglia and Royal Netherlands Meteorology Institute. The dataset contains fresh water hosing model output from the CMIP experiment run by the HadCM3 model. The freshwater was added to the North Atlantic basin between latitudes 50°N and 70°N.