The Exploitation of new data sources, data assimilation and ensemble techniques for storm and flood forecasting Project is a NERC Flood Risk for Extreme Events (FREE) Research Programme project (Round 1 - NE/E002137/1 - Duration January 2007 - April 2010) led by Prof AJ Illingworth, University of Reading. This project investigates possible methods of producing ensemble weather forecasts at high-resolution. These ensembles will be used with raingauge and river flow to improve methods of flood forecasting. The dataset includes radiosonde and wind profiles in England and Wales derived using Doppler radar returns from insects. The radial velocity measurements from insects were converted into VAD profiles by fitting a sinusoid to radial velocities at constant range. All measured profiles have been interpolated to the instrument location. This dataset contains wind profiler measurements.

"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. This dataset collection contains meteorology and ocean model outputs from the FORTE model. The objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. This dataset collection contains meteorology and ocean model outputs from the Coupled Hadley-Isopycnic Model Experiment (CHIME). The objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

Cloud base and backscatter data from the Met Office's Jenoptik CHM15k Nimbus ceilometer located at South Uist, Outer Hebrides. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

Cloud base and backscatter data from the Met Office's Gibraltar Cl31 ceilometer located at Gibraltar, British Overseas Territory on the south coast of Spain. The Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.

The Cloud_cci AVHRR-PMv3 dataset (covering 1982-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on measurements from AVHRR (onboard the NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19 satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci AVHRR-PMv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. The data in this dataset are a subset of the AVHRR-PM L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003. To cite the full dataset, please use the following citation: Stengel, Martin; Sus, Oliver; Stapelberg, Stefan; Finkensieper, Stephan; Würzler, Benjamin; Philipp, Daniel; Hollmann, Rainer; Poulsen, Caroline (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-PM L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD), DOI:10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003.

"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. This dataset collection contains meteorology and ocean model outputs from FAMOUS model. The objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world. Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.

This dataset contains Fire Radiative Power (FRP) data over Africa from Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data. Fires are detected by applying Roberts and Wooster's (2008) detection algorithm to SEVIRI data. FRP is estimated using the Middle InfraRed (MIR) radiance method (Wooster et al., 2003). The dataset was produced by Gareth Roberts and Martin Wooster (National Centre for Earth Observation (NCEO), Kings College London).

Data from the Max Planck Institute for Meteorology ECHAM5 simulations

These data are the University of Reading (Reading, UK) UR025.4 reanalysis produced by the Earth System Science Centre, and are used to support the work of the NERC (Natural Environmental Research Council) RAPID-WATCH (Rapid Climate Change-Will the Atlantic Thermohaline Circulation halt?) VALOR (VALue of the RAPID-WATCH Climate Change programme array) project. They consist of global ocean and sea ice fields, with coverage at 1/4 deg lat x 1/4 deg lon, on 75 vertical levels, for the period from 1989 to 2010. These variables include monthly means of Temperature, Salinity, Currents, Sea Surface Height and Sea Ice Parameters, forced by ERA-Interim atmospheric variables with Data Assimilation of in-situ T,S profiles and satellite SST, Sea Level Anomalies, Temperature and Salinity profiles and satellite Sea Ice Concentration using the UK Met Office FOAM system. 5-day data also exist for all variables and daily data for some upper ocean variables may be available from the provider. These data were originally produced under the EU MyOcean project and have been validated against observations. They are also currently available through the MyOcean website.