This is version 2.0.1.2016f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.0.2015p to span 1931-2016 and includes an increase in the number of stations and an updated methodology and is the final version of the 2016 data. The quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. The data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format "station_code"_HadISD_HadOBS_19310101-20151231_v2-0-1-2016p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height. To keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS. For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/ References: When using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference) : Dunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016. Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012 Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1 For a homogeneity assessment of HadISD please see this following reference Dunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. "Pairwise homogeneity assessment of HadISD." Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.

The NERC-funded Microphysics of Antarctic Clouds (MAC) project was centred on an aircraft campaign measuring clouds, aerosols, and boundary layer properties over the Weddell Sea, Antarctica. These data are simulations of the Polar-optimised Weather Research and Forecasting (PWRF) model for 5 configurations of the model's Morrison microphysics scheme, produced for a case study of two separate flights over the same region during the campaign (British Antarctic Survey MASIN twin-otter aircraft flights 218 an 219 on 27th November 2015). Each simulation contains data from two domains - a parent domain with 5km grid size and a nest with a 1km grid size. The control simulation used default physics options in the PWRF model's Morrison microphysics scheme. For the no-threshold, 2xHM, 5xHM, 10xHM simulations, thresholds restricting Hallett-Mossop secondary ice production in the PWRF model's Morrison microphysics scheme were removed, and for the 2xHM, 5xHM, and 10xHM cases the corresponding ice multiplication factor was increased by a factor of 2, 5 or 10. In all simulations, an approximation of the DeMott et al., 2010 (PNAS) parametrization used for primary ice nucleation. Methodology and further details can be found in Young et al., 2019 (Geophysical Research Letters): Radiative effects of secondary ice enhancement in coastal Antarctic clouds.

The data are projected future still water return levels. The data were produced by the Met Office using projections of future mean sea level change prepared at the Met Office and estimates of present-day still water return levels which were provided by the Environment Agency. The data were produced as a simple indication of the relative sizes and uncertainties in present day extreme water levels and projected future mean sea level change. The data were produced by combining projections of mean sea level change with best estimates of present day extreme still water levels. The data in marine strand 4.09 cover the period from 2020 to 2100 and are available for 46 UK tide gauge locations. Further information on this dataset and UKCP18 can be found in the documentation section.

The data are projected future still water return levels. The data were produced by the Met Office using projections of future mean sea level change prepared at the Met Office and estimates of present-day still water return levels which were provided by the Environment Agency. The data were produced as a simple indication of the relative sizes and uncertainties in present day extreme water levels and projected future mean sea level change. The data were produced by combining projections of mean sea level change with best estimates of present day extreme still water levels. The data in marine strand 4.10 cover the period from 2100 to 2300 and are available for 46 UK tide gauge locations. Further information on this dataset and UKCP18 can be found in the documentation section.

The University of Bath's meteor radar located at the King Edward Point Magnetic Observatory (KEP, 54.2820 S, 36.4930 W) on South Georgia island in the South Atlantic , is an all-sky VHF (Very High Frequency) meteor radar commercially produced Skiymet system. It has been operational since 2016 providing meteor detection and derived wind data in support of the NERC funded South Georgia Wave (SG-WEX) and DRAGON-WEX: The Drake Passage and Southern Ocean Wave Experiments (see linked Project records for further details). The radar detects radio scatter from the ionised trails of individual meteors drifting with the winds of the upper mesosphere, mesopause and lower thermosphere. A low-gain transmitter antenna is used to provide broad illumination of the sky. An array of five receiver antennas act as an interferometer to determine the azimuth and zenith angles of individual meteor echoes. Doppler measurements from each meteor determine the radial drift velocity and the meteor is assumed to be a passive tracer of atmospheric flow. The radar typically detects of order a few thousand meteors per day. These observations can be used to determine zonal and meridional winds in the mesosphere, mesopause and lower thermosphere at heights of about 80 – 100 km and with height and time resolutions of ~ 3 km and 2 hours. The radar produces daily “meteor position data” data files (mpd files) recording the details of each individual meteor echo. In normal operation a few thousand individual meteors are detected per day. See parameter list for details of available data. Recordings are made for each individual meteor detected allowing measurements of zonal and meridional wind speeds in the mesosphere and lower thermosphere to be obtained. Meteor count rates vary diurnally and with season, but are usually up to a few thousand meteors per day.

The University of Bath's meteor radar located at the British Antarctic Survey's Rothera base on Rothera Point, Adelaide Island, Antartica (67.57 S, 68.13 W), is an all-sky VHF (Very High Frequency) meteor radar commercially produced Skiymet system. Meteor detection and derived wind data from this instrument are available from 2005. These were collected in support of a number of research projects - see linked Project records for further details. The radar detects radio scatter from the ionised trails of individual meteors drifting with the winds of the upper mesosphere, mesopause and lower thermosphere. A low-gain transmitter antenna is used to provide broad illumination of the sky. An array of five receiver antennas act as an interferometer to determine the azimuth and zenith angles of individual meteor echoes. Doppler measurements from each meteor determine the radial drift velocity and the meteor is assumed to be a passive tracer of atmospheric flow. The radar typically detects of order a few thousand meteors per day. These observations can be used to determine zonal and meridional winds in the mesosphere, mesopause and lower thermosphere at heights of about 80 – 100 km and with height and time resolutions of ~ 3 km and 2 hours. The radar produces daily “meteor position data” data files (mpd files) recording the details of each individual meteor echo. In normal operation a few thousand individual meteors are detected per day. See parameter list for details of available data. Recordings are made for each individual meteor detected allowing measurements of zonal and meridional wind speeds in the mesosphere and lower thermosphere to be obtained. Meteor count rates vary diurnally and with season, but are usually up to a few thousand meteors per day. Note - there are additional data from 20040728 in the archive. No other data were obtained between that date and the start date for the dataset (20050212). The start date of 20050212 has been chosen in order to avoid potential confusion about missing data prior to that date.

The University of Bath's Bear Lake Observatory (BLO) meteor radar (42 N, 114 W), Utah, is an all-sky VHF (Very High Frequency) meteor radar commercially produced Skiymet system. The system has been operational from March 2008, providing meteor detection and derived wind data. Note, however, that there have been with some significant gaps in the data coverage. The data have been produced in support of a number of research projects - see linked Project records for further details. Meteor detection and derived wind data from this instrument are available from July 2000 to June 2018. These were collected in support of a number of research projects - see linked Project records for further details. The radar detects radio scatter from the ionised trails of individual meteors drifting with the winds of the upper mesosphere, mesopause and lower thermosphere. A low-gain transmitter antenna is used to provide broad illumination of the sky. An array of five receiver antennas act as an interferometer to determine the azimuth and zenith angles of individual meteor echoes. Doppler measurements from each meteor determine the radial drift velocity and the meteor is assumed to be a passive tracer of atmospheric flow. The radar typically detects of order a few thousand meteors per day. These observations can be used to determine zonal and meridional winds in the mesosphere, mesopause and lower thermosphere at heights of about 80 – 100 km and with height and time resolutions of ~ 3 km and 2 hours. The radar produces daily “meteor position data” data files (mpd files) recording the details of each individual meteor echo. In normal operation a few thousand individual meteors are detected per day. See parameter list for details of available data. Recordings are made for each individual meteor detected allowing measurements of zonal and meridional wind speeds in the mesosphere and lower thermosphere to be obtained. Meteor count rates vary diurnally and with season, but are usually up to a few thousand meteors per day.

This data file contains two sets of optimised global surface fluxes of ethane (C2H6), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. Emissions were produced using an iterative method of optimisation, known as 4D-Var, which minimised the model-observation differences. These surface fluxes are produced as monthly mean values on the (approximately) 5.6 degree horizontal model grid. The associated uncertainty for the flux from each gridcell is also included. The fluxes and uncertainties are global, and cover the period Jan 2008 - Dec 2014. There are two alternative emissions sets, labelled EMIS_ALL and EMIS_ANTH, whilst the uncertainties are labelled ERROR_ALL and ERROR_ANTH, respectively. The two optimised emission estimates are produced through iterative minimisation of model-observation error in INVICAT. In all cases the observations are surface flask samples of ethane produced by by the National Oceanic and Atmospheric Administration’s Global Monitoring Division (NOAA GMD) and the University of Colorado’s Institute of Arctic and Alpine Research (INSTAAR). Whole air samples in flasks are collected weekly to bi-weekly at each site and C2H6 is measured using gas chromatography with a flame ionization detection method. The EMIS_ALL fluxes are produced through variation of all surface emission types (anthropogenic, biomass burning, oceanic and biospheric), whilst the EMIS_ANTH fluxes are produced by only allowing the surface anthropogenic emissions to vary, with prior estimates of other emission types then added back on. Flux and uncertainty units are kg(C2H6)/m2/s, and time units are days since January 1st 2008. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in the PDF documentation stored along side this data, as well as in Monks et al., 2018.

This data set consisting of initial conditions, boundary conditions and forcing profiles for the Single Column Model (SCM) version of the European Centre for Medium-range Weather Forecasts (ECMWF) model, the Integrated Forecasting System (IFS). The IFS SCM is freely available through the OpenIFS project, on application to ECMWF for a licence. The data were produced and tested for IFS CY40R1, but will be suitable for earlier model cycles, and also for future versions assuming no new boundary fields are required by a later model. The data are archived as single time-stamp maps in netCDF files. If the data are extracted at any lat-lon location and the desired timestamps concatenated (e.g. using netCDF operators), the resultant file is in the correct format for input into the IFS SCM. The data covers the Tropical Indian Ocean/Warm Pool domain spanning 20S-20N, 42-181E. The data are available every 15 minutes from 6 April 2009 0100 UTC for a period of ten days. The total number of grid points over which an SCM can be run is 480 in the longitudinal direction, and 142 latitudinally. With over 68,000 independent grid points available for evaluation of SCM simulations, robust statistics of bias can be estimated over a wide range of boundary and climatic conditions. The initial conditions and forcing profiles were derived by coarse-graining high resolution (4 km) simulations produced as part of the NERC Cascade project, dataset ID xfhfc (also available on CEDA). The Cascade dataset is archived once an hour. The dataset was linearly interpolated in time to produce the 15-minute resolution required by the SCM. The resolution of the coarse-grained data corresponds to the IFS T639 reduced gaussian grid (approx 32 km). The boundary conditions are as used in the operational IFS at resolution T639. The coarse graining procedure by which the data were produced is detailed in Christensen, H. M., Dawson, A. and Holloway, C. E., 'Forcing Single Column Models using High-resolution Model Simulations', in review, Journal of Advances in Modeling Earth Systems (JAMES). For full details of the parent Cascade simulation, see Holloway et al (2012). In brief, the simulations were produced using the limited-area setup of the MetUM version 7.1 (Davies et al, 2005). The model is semi-Lagrangian and non-hydrostatic. Initial conditions were specified from the ECMWF operational analysis. A 12 km parametrised convection run was first produced over a domain 1 degree larger in each direction, with lateral boundary conditions relaxed to the ECMWF operational analysis. The 4 km run was forced using lateral boundary conditions computed from the 12 km parametrised run, via a nudged rim of 8 model grid points. The model has 70 terrain-following hybrid levels in the vertical, with vertical resolution ranging from tens of metres in the boundary layer, to 250 m in the free troposphere, and with model top at 40 km. The time step was 30 s. The Cascade dataset did not include archived soil variables, though surface sensible and latent heat fluxes were archived. When using the dataset, it is therefore recommended that the IFS land surface scheme be deactivated and the SCM forced using the surface fluxes instead. The first day of Cascade data exhibited evidence of spin-up. It is therefore recommended that the first day be discarded, and the data used from April 7 - April 16. The software used to produce this dataset are freely available to interested users; 1. "cg-cascade"; NCL software to produce OpenIFS forcing fields from a high-resolution MetUM simulation and necessary ECMWF boundary files. https://github.com/aopp-pred/cg-cascade Furthermore, software to facilitate the use of this dataset are also available, consisting of; 2. "scmtiles"; Python software to deploy many independent SCMs over a domain. https://github.com/aopp-pred/scmtiles 3. "openifs-scmtiles"; Python software to deploy the OpenIFS SCM using scmtiles. https://github.com/aopp-pred/openifs-scmtiles

Daily global cloud droplet number concentrations (Nd) have been calculated at 1x1 degree resolution from pixel-level MODIS (MODerate Imaging Spectroradiometer) Collection 5.1 Joint Level-2 (Aqua satellite) optical depth (tau) and the 3.7 micron effective radius (reff) data (and other supporting data) using the adiabatic cloud assumption (liquid water content increases linearly with height, Nd is constant throughout the cloud depth and the ratio of the volumne mean radius to the effective radius is assumed constant). The Nd data is contained in separate NetCDF files for each year for the period 2003-2015. Nd is contained in the "Nd" variable and has units of cm^{-3}. This is a 360x180xNdays (lon x lat x Ndays) sized array, where Ndays is the number of days in the year. The lon x lat grid is a regular 1x1 degree grid. The time is provided as both a 1D array of size Ndays ("time") with units of days since 1st Jan, 1970 and an array of size Ndays x 3 ("time_vec") that contains numbers for the year month and day for each of the Ndays entries. A number of filters have been applied to the data in order to remove retrievals that are likely to be problematic, or to violate the adiabatic cloud assumptions. Data is only included if: 1) Pixels are determined to be liquid pixels by MODIS. 2) The 1x1 degree mean cloud top height (calculated using the MODIS cloud top temperature and the sea surface temperature) is below 3.2km. 3) The 1x1 degree liquid cloud fraction was larger than 80%. 4) The 1x1 degree mean solar zenith angle was 65 degrees or less to avoid biases at high angles (Grosvenor and Wood, 2014). Note, that the filtering is different to that described in Grosvenor, AMTD, 2018 in the following ways :- 1) 1km resolution tau and reff are used to calculate Nd, which is then aggregated to 1x1 degree resolution (rather than using 1x1 degree tau and reff). 2) Only Nd based on the 3.7 micron reff retrieval is provided here. 3) No filtering for the presence of sea-ice is done here - it is recommended that this is done if using for high latitudes. 4) The data here is not restricted to tau>5. Also note that the vertical penetration bias correction described in Grosvenor, AMTD, 2018 is NOT applied here. In addition, as described in the latter paper, further pixel-level screening is performed in order to select high quality data. Details on the reasons for restricting to low solar zenith angles can be found in Grosvenor and Wood, ACP, 2014. Information on the pixel level filtering applied can be found in Grosvenor et al., AMTD, 2018 (noting the differences explained above). A comparison of this dataset with others can be found in Grosvenor et al., Reviews of Geophysics, 2018. This dataset calculates a product that is not provided as standard by MODIS. It uses improved optical depth and effective radius data compared to the standard MODIS Level-3 data since situations (e.g., high solar zenith angles, broken clouds) that have been shown to cause retrieval issues have been filtered out at the Level-2 stage before being averaged into Level-3 droplet concentration data.