This dataset is comprised of raw data from the NERC-funded, full-waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations. Plot (A)EP-02 (Downfall Creek) is part of the CSIRO Rainforest Permanent Plots of North Queensland (Graham et al. 2006) The TLS data were collected on a 10 m x 10 m grid where at each position the scanner captured data in an upright and tilted position. The scanner was set to an angular step of 0.04 degrees for all scans. In between each scan position, a set of retro-reflective targets were positioned to be used as tie-points between scans. For more information on TLS acquisition refer to Wilkes et al. (2017). Scan data were coregistered using RiSCAN Pro, the 4x4 rotation transformation matrices to transform the point cloud data into a common reference coordinate system can be found in the "matrix" directory.

This dataset contains aboveground biomass estimates generated using terrestrial laser scanning (TLS) techniques for different species of tree. It was used to produce the figures and statistics of the publication "Estimating forest aboveground biomass with terrestrial laser scanning: current status and future directions". This dataset contains 391 entries. Each entry is a tree that was terrestrial laser scanned and consecutively harvested to assess its aboveground biomass (AGB). AGB was also obtained from allometric scaling equations. Several ancillary tree properties such as stem diameter, foliage conditions,... and scan metadata (type of scanner, pattern) are included. We refer to the tab 'headers' for an explanation and units of the respective columns. Elaborate method descriptions can be found in the publication or in the following publications, which can be found in the documentation sections

This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations. Plot (AEP-33) Curtain Fig is part of the CSIRO Rainforest Permanent Plots of North Queensland (Graham et al. 2006) The TLS data were collected on a 10 m x 10 m grid where at each position the scanner captured data in an upright and tilted position. The scanner was set to an angular step of 0.04 degrees for all scans. In between each scan position, a set of retro-reflective targets were positioned to be used as tie-points between scans. For more information on TLS acquisition refer to Wilkes et al. (2017). Scan data were coregistered using RiSCAN Pro, the 4x4 rotation transformation matrices to transform the point cloud data into a common reference coordinate system can be found in the "matrix" directory.

This data set consist of a single file which contains a set of optimised global surface fluxes of methane (CH4), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. 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 grid cell is also included. The fluxes and uncertainties are global and cover the period Jan 2010 - Dec 2018. The emissions from fossil fuels are labelled FF_FLUX, whilst the uncertainties are labelled FF_ERROR. The emissions from natural, agricultural and biomass burning sources are labelled NAT_FLUX, whilst the uncertainties are labelled NAT_ERROR. These two sectors (fossil fuel and non-fossil fuel) are solved for separately in the inversion. Flux and uncertainty units are kg(CH4)/m2/s, and time units are days since January 1st 2010. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in Wilson et al. (2020) in the documentation section.

QUEST Fish was led by Dr Manuel Barange (PML) with 18 co-investigators from POL, PML, CEFAS, University of Plymouth, University of Portsmouth, CSIC (Spain), UEA, WorldFish Centre, IPSL, ICES (Denmark), Met Office, IRD (Paris) and University of North Carolina, as part of QUEST (Quantifying and Understanding the Earth System). QUEST-Fish specifically focused on the added impacts that climate change is likely to cause on global fish production, and on the subsequent additional risks and vulnerabilities to human societies. This dataset contains global fish biomass estimates from the Global Coastal-Ocean Modelling System.

This dataset contains isocyanate, amide, nitrate and nitro compounds measurements from an anthropogenic biomass burning event in Manchester, UK. Measured over an 11 day period in November 2014 using a flight chemical ionisation mass spectrometer (ToF-CIMS). Measurements of NOx and O3 are also included. Data were collected from The Whitworth Meteorological Observatory based at the University of Manchester.