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.

ARSF project GB04/03: Influence of habitat structure and composition on energy expenditure and overall reproductive rate of woodland bird species. Led by: Shelly Hinsley. Location: Huntingdon, Cambridgeshire, UK.

This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Aqua (Aqua). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the daytime and night-time Aqua equator crossing times which are 13:30 and 01:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 4th July 2002 and ends on 31st December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.

ARSF project MC04/31: Modelling landslide processes and associated geohazards in seismically active SW Cyprus: a potential NERC community site for applied landslide geohazard research & training. PI: Kevin Northmore. Site: Paphos.

ARSF project MC04/24: Mapping the lower Tiber catchment. PI: Simon Stoddart. Site: Nepi.

ARSF project GB08/18: Assessing the distribution and abundance of a keystone riparian macrophyte - impacts of swan grazing and consequences for salmonid conservation. Led by: Dr. Richard Stilman, Centre for Conservation Ecology and Environmental Change, School of Conservation Sciences Bournemouth University, Talbot Campus, Fern Barrow, Poole, Dorset, BH125BB. Location: River Froome, Somerset, UK.

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.

ARSF Project GB06/05; led by Dr. Tim Malthus (School of Geosciences, University of Edinburgh), Clocaenog Forest (North Wales), Glasfyndd Forest (South Wales).

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 preojections 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.

ARSF project ET07/03: Mapping geothermal and epithermal deposits in the Ethopian Rift Valley. Led by: Dr. Graham Ferrier, Department of Geography, University of Hull, Hull, HU6 7RX. Location: Ethiopia.