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  • Radio propagation measurements at 20 GHz at Chilton, Oxfordshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal.

  • HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2019, but the start time is dependent on climate variable and temporal resolution. The gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost. This data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation). For this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added. The primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project "Analysis of historic drought and water scarcity in the UK". The dataset is provided under Open Government Licence.

  • Estimated annual burned area and uncertainties for three global satellite-derived burned area products. Each estimate is provided at 1° spatial resolution for the years 2001-2013. Theoretical annual uncertainties in burned area (standard errors) products are generated according to a multiplicative triple collocation error model and annualised according to a sampling of the 16-day burned area estimates from each product. The approach provides unique uncertainties at 1° for the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 burned area product (MCD64); the MODIS Collection 5.1 MCD45 product and the FireCCI50 product. Please note that due to limitations in the available sampling for the error model, around 40% of cells do not have uncertainty estimates.

  • 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.

  • This dataset includes the MPI-ESM-LR model output prepared for SPECS soilMoistureInit (1981-2012). These data were prepared by the Max Planck Institute for Meteorology (MPI-M), as part of the SPECS project. Model id is MPI-ESM-LR (MPI-ESM-LR 2015; atmosphere: ECHAM6 v6.3.01p2 (REV: 3904), T63L47; land: JSBACH (REV: 3904); ocean: MPIOM v1.6.1p1 (REV: 3753) marine biogeochemistry HAMOCC included, GR15L40; sea ice (REV: 3753). Frequency is daily and monthly. Daily Atmospheric variables are: clt hfls hfss pr prc psl rlds rlut rsds tas uas vas Monthly atmos variables: hus pr psl ta tas ua va zg Monthly ocean variables: mlotst tos uo vo Monthly land variables: mrro mrso Monthly sea ice variable: sit

  • An international long-term collaboration to study the climatic and environmental feedback mechanisms involved in the African monsoon, and in some of its consequences on society and human health. The programme, which started in 2004, has developed a network of ground-based observation stations over Sub-Saharan West Africa to measure heat flux and, for some stations, CO2 and H2O vapour fluxes. Files also include concomitant meteorological measurements (wind, temperature, pressure, humidity, rainfall) and soil physics parameters (soil temperature and moisture). The UK branch of AMMA makes use of several instruments provided by the UK Universities Facility for Atmospheric Measurement (UFAM) which are centred on the Niamey meso-site. The Facility for Airbourne Atmospheric Measurements (FAAM) aircraft was used during the July-August 2006 campaign.

  • This dataset contains halocarbon measurements made from whole air samples collected on board the FAAM (Facility for Airborne Atmospheric Measurements) aircraft during the NERC (National Environmental Research Council) South West Asian Aerosol Monsoon Interactions (SWAAMI) project and the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) project - both of which were funded under the 'Drivers of Variability in the South Asian Monsoon' programme. Whole air samples were collected in 3 L stainless steel cylinders (WAS flasks) aboard the FAAM aircraft during 11 flights (b957, b959, b963, b966, b968, b969, b971, b972, b974, b975, b976). In total, 176 samples were collected above India and the Indian Ocean, from the 12th June - 10th July 2016. Samples were returned to the University of Bristol for analysis by Medusa Gas Chromatography Mass Spectrometry, resulting in concentration (mole fraction) data for chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and chlorocarbons (e.g. dichloromethane). Each sample was analysed three times in total, with the reported mole fraction taken to be the average of these three analyses. Samples were collected by Daniel Say, with significant input from Anita Ganesan (flight planning) and Simon O'Doherty (interpretation of measurements).

  • This dataset contains momentum budget snow removal experiment model data from Dudh Koshi Valley in the Nepalese Himalaya. The Weather Research and Forecasting (WRF) model was run for two months, July 2013 and January 2014, to investigate the momentum budget components of the winds in the Dudh Koshi Valley. All the permanent snow and ice in the model has been changed to rock. This data was collected as part of the Dynamical drivers of the local wind regime in a Himalayan valley project (NE/L002507/1). The WRF model has been modified to output the momentum budget components. There are four nested domains, of 27 km, 9 km, 3 km and 1 km resolution. The inner 1 km is 130 km by 130 km, centred on 27.98N, 86.76E.

  • Wind profiles from a Galion G4000 Doppler lidar for the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project, derived from conical scans at 30 degree and 50 degree beam elevation angles. The University of Leeds participation in the project- MOSAiC Boundary Layer -was funded by the Natural Environment Research Council (NERC, grant: NE/S002472/1) and involved instrumentation from the Atmospheric Measurement and Observations Facility of the UK's National Centre for Atmospheric Science (NCAS AMOF). This was a year-long project on the German icebreaker Polarstern to study Arctic climate focused on measurements of atmospheric boundary layer dynamics and turbulent structure. The Galion wind profiler provides high resolution (~15m vertical and 5 minute temporal) measurements of wind profiles. Data are only available where sufficient particles are available to backscatter the laser light - in the clean arctic environment, this requires cloud or precipitation.

  • This is version v3.2.0.2021f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological 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_19310101-20220101_v3.2.1.2021f.nc. The station codes can be found under the docs tab. 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 informed about 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., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note. 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.