Data from the Instituto Nazionale di Geofisica e Vulcanologia INGV-SXG simulations

SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders. A core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. A standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. The standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. A description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: 1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG); 2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG) 3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); 4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal); 5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5. SPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378).

Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 1 took place in July and August 2003 at Writtle College, near Chelmsford, Essex. This dataset contains ECMWF trajectories

This dataset contains daily monthly average N80 Gaussian gridded, potential vorticity level, analysis timestep parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) 40 program from January 1958 to December 2001. ERA-40 followed on from the ERA-15 re-analysis project. Access limited to UK based academic researchers only. These data are GRIB formatted.

This CD-ROM set contains the Volume 5 Near-surface meteorological analyses and Total and convective precipitation data collection. The data covers a 24 month period, 1987-1988, and all but one are mapped to a common spatial resolution and grid (1 degree x 1 degree). Temporal resolution for most datasets is monthly; however, a few are at a finer resolution (e.g., 6-hourly). This dataset contains data covering Near-surface meteorological analyses, hybrid products and total and convective precipitation

The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1986. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1987. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1988. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1989. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone averages, combining various satellite observations and ozone sonde data. The data are global and covers 1985-1989. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.