This dataset contains a time series of ice velocities for the Hagen Brae glacier in Greenland derived from Sentinel-1 SAR data acquired between 22/1/2015 and 1/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.

The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 3 aerosol daily products from AATSR, using the Swansea University (SU) algorithm, version 4.2. For further details about these data products please see the documentation.

This dataset contains wind speed and direction, pressure, temperature and humidity measurements for the Kirby Misperton site. British Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing. The monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public.

Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1. This dataset contains measurements of atmospheric electricity and electric potential gradient made using a EFM-100 Atmospheric Electric Field Monitor at Tripura University, India.

This dataset contains wind speed and direction, pressure, temperature and humidity measurements for the Little Plumpton site. British Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.” The monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public.

This dataset contains about 5 years of analysed observations regarding the degree of convective aggregation, or clumping, across the tropics - these are averaged onto a large-scale grid. There are also additional variables which represent environmental fields (e.g. sea surface temperature from satellite data, or humidity profiles averaged from reanalysis data) averaged onto the same large-scale grid. The main aggregation index is the Simple Convective Aggregation Index (SCAI) originally defined in Tobin et al. 2012, Journal of Climate. The data were created during the main years of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data so that they could be compared with vertical cloud profiles from this satellite data, and the results of this analysis appear in Stein et al. 2017, Journal of Climate. Each file is one year of data (although the year may not be complete). Each variable is an array: var(nlon, nlat, [nlev], ntime) longitude, latitude, pressure, time are variables in each file units are attributes of each variable (except non-dimensional ones) missing_value is 3.0E20 and is an attribute of each variable Time is in days since 19790101:00Z and is every 3hours at 00z, 03z, ... The actual temporal frequency of the data is described for each variable below. The data is for each 10deg X 10deg lat/lon box, 30S-30N (at outer edges of box domain), with each box defined by its centre coordinates and with boxes overlapping each other by 5deg in each direction. In general, each variable is a spatial average over each box, with the value set to missing if more than 15% of the box is missing data. Exceptions to this are given below. The most important exception is for the brightness temperature data, used in aggregation statistics, which is filled in using neighborhood averaging if no more than 5% of the pixels are missing, but otherwise is considered to be all missing data. The percentage of missing pixels is recorded in 'bt_miss_frac'.

This dataset consists of daily total column water vapour (TCWV) over land, at a 0.05 degree resolution, observed by various satellite instruments. It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1 (TCWV-land (CDR-1). This version of the data is v3.1.

Cloud properties derived from the AVHRR instrument on the NOAA-17 satellite by the ESA Cloud CCI project. The L3C dataset consists of data combined (averaged) from a single instrument into a global space-time grid, with a spatial resolution of 0.5 degrees lat/lon and a temporal resolution of 1 month. This dataset is version 1.0 data from Phase 1 of the CCI project.

This dataset contains Simulated Photolysis rates using the Fast-JX model at the IAP-Beijing site during the winter and summer APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. Fast-JX column photolysis model was used at Lancaster University to simulate column profiles of photolysis rates (JO3 and JNO2) centred on the Institute of Atmospheric Physics (IAP) tower site in Beijing. The photolysis rate profiles are simulated under different aerosol loadings to represent the optical effects of individual species and cloud cover on photochemistry.

This dataset contains ice velocities for the Greenland margin for winter 1995-1996, which have been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The data were derived from intensity-tracking of ERS-2 data acquired between 03-09-1995 and 29-03-1996. It provides components of the ice velocity and the magnitude of the velocity. The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities. Both a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by DTU Space - Microwaves and Remote Sensing. For further information please see the product user guide. Please note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product.