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.

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.

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.

Computed air parcel trajectory used for campaign support during the Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) programme.

This dataset contains measurements from the Micro Rain Radar (MRR2), manufactured by Meteorologische Messtechnik GmbH (Metek) installed onboard the NATO Research Vessel Alliance during the Iceland Greenland Seas Project. The MRR2 is a frequency modulated (FM), continuous wave (CW) Radar (Radio Detection and Ranging) that obtains doppler spectral density at each range gate with a time resolution of 10 s. The terminal velocity of the precipitation targets (vT) is the primarily retrieved variable from these doppler spectral density observations. Additionally, drop size distribution and the corresponding moments, for example liquid water content (LWC), rain rate (RR) and Radar Reflectivity (Ze) are retrieved with post processing. The initial installation location from 03-13 Feb 2018 was midship on the weatherdeck. At Reykjavik harbour the MRR2 worked as expected, while at sea artificial signals at three elevations appeared. The artificial signals were due to an interference on the power cable or power source. On 11 Feb 2018, a separate power source for the MRR2 could be secured, and it subsequently operated without interferences after ~12 UTC that day. For further details and figures on the MRR2 and its operation in the cruise please read the attached documentation.

This dataset contains about 5 years of analysed observations regarding the degree of convective aggregation, or clumping, across the tropics - these are averaged onto a large-scale grid. There are also additional variables which represent environmental fields (e.g. sea surface temperature from satellite data, or humidity profiles averaged from reanalysis data) averaged onto the same large-scale grid. The main aggregation index is the Simple Convective Aggregation Index (SCAI) originally defined in Tobin et al. 2012, Journal of Climate. The data were created during the main years of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data so that they could be compared with vertical cloud profiles from this satellite data, and the results of this analysis appear in Stein et al. 2017, Journal of Climate. Each file is one year of data (although the year may not be complete). Each variable is an array: var(nlon, nlat, [nlev], ntime) longitude, latitude, pressure, time are variables in each file units are attributes of each variable (except non-dimensional ones) missing_value is 3.0E20 and is an attribute of each variable Time is in days since 19790101:00Z and is every 3hours at 00z, 03z, ... The actual temporal frequency of the data is described for each variable below. The data is for each 10deg X 10deg lat/lon box, 30S-30N (at outer edges of box domain), with each box defined by its centre coordinates and with boxes overlapping each other by 5deg in each direction. In general, each variable is a spatial average over each box, with the value set to missing if more than 15% of the box is missing data. Exceptions to this are given below. The most important exception is for the brightness temperature data, used in aggregation statistics, which is filled in using neighborhood averaging if no more than 5% of the pixels are missing, but otherwise is considered to be all missing data. The percentage of missing pixels is recorded in 'bt_miss_frac'.

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)"

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)

Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1. This dataset contains measurements of atmospheric electricity and electric potential gradient made using a EFM-100 Atmospheric Electric Field Monitor at Tripura University, India.

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 Manchester UV-LIF spectrometer data (fluorine and chlorine number concentration and particle size distribution) processed with "MUTANT data processing toolkit (MAN-WIBS3M)