Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations

Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 Global Climate Models (GCMs) produce a wide range of simulated SIT in the historical period (1979 – 2014) and exhibit various biases when compared with the Pan-Arctic Ice Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT to narrow projection uncertainty via a statistical bias correction technique. This method is applied to six GCMs from CMIP5, the outputs of which are available in this dataset. Results are reported in: Melia, N., Haines, K., and Hawkins, E.: Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations, The Cryosphere Discuss., 9, 3821-3857, doi:10.5194/tcd-9-3821-2015, 2015

Topology Reconfiguration in Distributed Echo State Networks

Parameter-accuracy results from investigations into Echo State Network (ESN) metanetworks presented in "Topology Reconfiguration in Distributed Echo State Networks"

Partial eclipse meteorological observations, Reading, UK, 20 March 2015

Datasets accompanying the paper entitled Meteorological responses in the atmospheric boundary layer over southern England to the deep partial eclipse of 20 March 2015 by Stephen Burt, Department of Meteorology, University of Reading, Reading RG6 7BE, U

On the detection of pressure perturbations during the March 2015 solar eclipse - supplementary data

A collection of data used in the paper: On the detection of pressure perturbations during the March 2015 solar eclipse. Includes surface measurement data from the University of Reading Atmospheric Observatory and data from the University of Reading research launches from the Met Office Observatory