Data are netCDF formatted

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  • The Meteorological Research Flight (MRF) was a Met Office facility, which flew a well-instrumented C-130 Hercules aircraft for atmospheric research purposes. This dataset contains ARIES measurements taken onboard on board the Met Office C-130 Hercules aircraft.

  • Data from the Canadian Centre for Climate Modelling & Analysis CGCM3-1-T63 simulations

  • This dataset contains WACCM-X model results under RCP8.5 (Representative Concentration Pathway) carbon dioxide increases and high solar activity (F10.7 = 200 sfu). These cover ground level to a pressure level of 4e-10 hPa (~300 km altitude) on a global 144x96 longitude-latitude grid . Data is given in daily instantaneous (.h2.) and monthly average (.h0.) files in the netCDF format. Default WACCM-X outputs remain, along with the following additional variables: 'PS' - Surface Pressure 'Z3' - Geopotential Height (above sea level) 'T' - Temperature 'U' - Zonal Wind 'V' - Meridional Wind 'CO2' - Carbon Dioxide Concentration 'CO' - Carbon Monoxide Concentration 'NO' - Nitric Oxide Concentration 'H2O' - Water Vapour Concentration 'O' - Atomic Oxygen Concentration More detail on each variable is given within the netCDF files and the readme file. 64 month runs from edited initial files at 10 year intervals from 2015 to 2095 under RCP8.5. There is also a 28 month 1975 run and 64 month 2000 run. All of these cyclically repeat the initial year. These are separated into individual folders with the RCP8.5 CO2 concentration listed. The first 4 months of each of these datasets have been ignored in processing as the model spins up, but are included here for completeness. This data was collected to understand the density drop at low earth orbit altitudes as carbon dioxide concentrations increase.

  • Cloud base and backscatter data from the Met Office's Nottingham Cl31 ceilometer located at Nottingham, Nottinghamshire. 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 LAR experiment run by the HadCM3 model. The freshwater was added to the North Atlantic basin to a larger area north of the CMIP (between latitudes 50°N and 70°N) area.

  • This dataset contains Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) Quasi-global pentadal satellite and observation based precipitation estimates over land from 1981 to near-real time. Spanning 50°S-50°N (and all longitudes), starting in 1981 to near-present, CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring.

  • Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). This dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data. There are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files.

  • Cloud base and backscatter data from the Met Office's Eskdalemuir Cl31 ceilometer located at Eskdalemuir, Dumfriesshire, Scotland. 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.

  • This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. The SCFG time series provides daily products for the period 1982-2019. The product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. The retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 630 nm and 1.61 µm (channel 3a or the reflective part of channel 3b), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. The following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground. The SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology. The Remote Sensing Research Group of the University of Bern is responsible for the SCFG product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. The SCFG AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 38 years.