This dataset comprises the output from a series of eight simulations with the Coupled Magnetosphere-Ionosphere-Thermosphere (CMIT) model as used in the study by Cnossen and Foerster (2016).The first six simulations were run with observed solar radiative forcing, specified by F10.7 values, and observed solar wind conditions. In the last two simulations (dsol-lh and jsol-lh), the solar radiative forcing was artificially reduced by setting the F10.7 values to a constant low value of 80 solar flux units. The dsol-lh and jsol-lh are otherwise identical to the dsol-hh and jsol-mh simulations, respectively. Further details about the simulations and a brief description of the CMIT model are provided by Cnossen and Foerster (2015, in review). Wiltberger et al. (2004) and Wang et al. (2004, 2008) provide further details of the CMIT model. The CMIT simulations were performed on the Yellowstone high-performance computing facility (ark:/85065/d7wd3xhc) provided by the Computational and Information Systems Laboratory of the National Centre for Atmospheric Research, sponsored by the National Science Foundation.

The NERC-funded HiTemp project was conducted by the Birmingham Urban Climate Laboratory (BUCL) research team to examine Birmingham's Urban Heat Island (UHI). The project operated a high density air temperature-sensor network and has lead to a number of research projects examining Birmingham's UHI in more detail than ever-before possible. This dataset collection temperature, dew point, relative humidity, pressure, solar radiation, precipitation, wind and hail measurements from a high density network of meteorological sensors installed within the Birmingham conurbation. This includes 73 Aginova Sentinel Micro air temperature sensors and 25 Vaisala WXT520 weather transmitters between 2012-14. These measurements have been made by the Birmingham Urban Climate Laboratory (BUCL) for the HiTemp (High Density Measurements within the Urban Environment) project in order to study the Birmingham Urban Heat Island (UHI)

The data contain solar radiation, air temperature, temperature depression, wind velocity, wind direction and rainfall from Automatic Weather Stations (AWS) located at Moor House and Helbeck, Cumbria, UK. This data contain a mixture of hourly and daily readings. The data were collected between July 1974 and February 1987 at Moor House and between May 1974 and October 1983 at Helbeck. Full details about this dataset can be found at https://doi.org/10.5285/77df4b96-c5e4-419a-b7cf-fc1d9a05c61c

Data collected during a field experiment investigating the differences between greenhouse gas (GHG) fluxes under a bioenergy crop Miscanthus x giganteus and a conventional arable crop, barley (Hordeum vulgare) on adjacent fields. Measurements taken include soil respiration (Rs) measured using Licor automated chambers and infrared gas analyser (IRGA), from collars excluding aboveground vegetation but not roots. Ancillary measurements included meteorological variables (air temperature and solar radiation) and soil variables (soil moisture and temperature at 5 cm depth). Data were collected between May and September 2013. Full details about this dataset can be found at https://doi.org/10.5285/c397d6f4-96f4-4967-a0df-c64ef35ea572

Meteorology data from the UK Environmental Change Network (ECN) terrestrial sites. Variables measured include albedo (ground and sky), temperature (dry bulb, wet bulb and soil (at 10cm and 30cm)), relative humidity, radiation (net. and solar), rainfall, surface wetness, soil moisture, wind direction and wind speed. These data are collected by Automatic Weather Stations at all of ECN's terrestrial sites using a standard protocol. They represent continuous hourly records from 1991 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/fc9bcd1c-e3fc-4c5a-b569-2fe62d40f2f5

[THIS DATASET HAS BEEN WITHDRAWN]. Meteorology data from the UK Environmental Change Network (ECN) terrestrial sites. Variables measured include albedo (ground and sky), temperature (dry bulb, wet bulb and soil (at 10cm and 30cm)), relative humidity, radiation (net. and solar), rainfall, surface wetness, soil moisture, wind direction and wind speed). These data are collected by Automatic Weather Stations at all of ECN's terrestrial sites using a standard protocol. They represent continuous hourly records from 1992 to 2012. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/e1d33b37-f1d4-4234-a0d5-8bf4e657f653