ARSF project 04/26: Detecting hydrocarbon induced geobotanical anomalies using hyperspectral imagery in Aberdeenshire. PI: M. Williams. Site: Aberdeen Pipeline .

This dataset contains Fire Radiative Power (FRP) data over Africa from Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data. Fires are detected by applying Roberts and Wooster's (2008) detection algorithm to SEVIRI data. FRP is estimated using the Middle InfraRed (MIR) radiance method (Wooster et al., 2003). The dataset was produced by Gareth Roberts and Martin Wooster (National Centre for Earth Observation (NCEO), Kings College London).

Topsat images acquired by the Landmap project from Infoterra are available for selected areas in the following countries and locations: Albania, Argentina, Armenia, Botswana, Cameroon, China, Croatia, Egypt, Farasan Islands, Ghana, Honduras, Iraq, Kazakhstan, Krakatau, Mali, Mexico, Nigeria, Nile Delta, Palestine, Patagonia, Russia and Santa Cruz Island. Data are available as panchromatic or multispectral, in Tiff, ecw (Enhanced Compression Wavelet) and JPEG formats. The Joint Information Systems Committee (JISC) funded Landmap service which ran from 2001 to July 2014 collected and hosted a large amount of earth observation data for the majority of the UK. After removal of JISC funding in 2013, the Landmap service is no longer operational, with the data now held at the NEODC.

Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. This classification system is designed to identify cirrus clouds by the cloud formation mechanism. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and synoptic. Comparisons with convection-permitting model simulations and back-trajectory based analysis have shown that this classification can provide useful information on the cloud scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes (see description paper). This classification is designed to be easily implemented in global climate models - the observational classification results are made available make this comparison easier. The classification has been generated globally for the years 2003-2013 inclusive. Making use of the moderate resolution imaging spectrometer (MODIS) on-board the Aqua satellite, the classification exists only at 13:30 local solar time each day. The regimes used within this classification are defined as follows (further details are given in the description paper) Orographic - proximity to regions of large-scale topography variation Frontal - satellite detected cirrus clouds that intersect to atmospheric fronts determined from reanalysis data Convective - satellite detected cirrus clouds in regions of large scale ascent determined from reanalysis data Synoptic - Not assigned as one of the other regimes. Data are gridded NetCDF V4 files, provided on a regular longitude-latitude grid at a 1 by 1 degree resolution across the whole globe. The files provide the classification at 13:30 local solar time (the satellite overpass time) and are at a daily resolution, within a folder defining the year. The filename structure is: {year}/IC-CIR.{year}.{day_of_year}.v1.nc where {year} is the year of the data and {doy of year} starts with 001 on the first of January. Further details about the data, including comparisons to convection-resolving model simulations can be found in the description paper (Gryspeerdt et al., ACP, 2018).

The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.

Extreme short-duration precipitation changes, derived from the UKCP Local projections at 5km resolution (Kendon et al 2021) have been estimated using a spatial statistical model as part of the NERC-funded Future-Drainage project. Future changes ("uplifts") are estimated for 2050 and 2070 for RCP8.5 compared to the baseline of 1990 for precipitation durations of 1-, 3-, 6-, 12-, 24-hours. 2070 is the central year for 2060-2080 ("UKCP Local TS3") time-slice, and 2050 value is an interpolation between TS3 and 2020-2040 ("UKCP Local TS2") time-slice. 2050 is an important date for the UK water industry in its delivery of Drainage and Wastewater Management Plans (DWMPs; Water UK, 2019). Return level changes are provided for 2, 30, and 100-year return periods. The data is on the OSGB 1936/EPSG:27700 projection at 5km resolution. The underlying statistical model is described in Youngman (2018, 2020) and is applied individually to each of the twelve UKCP Local ensemble members. Future changes plus their uncertainties from each ensemble member are then combined following the method described in Fosser et al (2020). Two estimates of future changes are provided from this "super-ensemble" by estimating percentiles from the distribution obtained using the Fosser et al (2020) method - a central (50%) and high (95%) estimate. Values are rounded to nearest 5%. The future changes are available for each 5km grid point within the borders of the United Kingdom, provided as ERSI shapefiles and a CSV (comma-separated values) file, with separate files for different durations.

ARSF project 03/08 led by M. Cutler. Site: Otterburn, Cheviot Hills.

The EMERALD projects were airborne measurement campaigns designed to study dynamical, microphysical and infra-red radiative properties of cirrus clouds, using both in-situ and remote measurement techniques. The dataset contains static air temperature, static air pressure, relative humidity, water vapour mixing ratio, and ozone mixing ratio. These data are part of the NERC Clouds, Water Vapour and Climate (CWVC) programme.

This dataset contains output data from a number of models from the UK Met Office Hadley Centre which was processed into text files at the Climate Research Unit at the University of East Anglia. The data extraction was intended for use by the Climate Impacts Community (and was funded by the UK Departement of Environment Food and Rural Affairs, Defra). Output from each model is stored in a separate directory in the BADC archive, and the majority of the data comes from experiments performed using the Hadley centre Coupled Model, Version 3 (HadCM3). Note that is dataset is kept for historical purposes only. More consistent and complete HadCM3 data is available from the main British Atmospheric Data Centre (BADC) HadCM3 archive.