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  • This dataset is one of 2 global ocean reanalyses (named UR025.3 and UR025.4) produced by National Centre for Earth Observation at the University or Reading as part of the EU MyOcean project. Both datasets have been validated against observations. This dataset contains monthly mean output from UR025.3 reanalysis (which uses an older version of the NEMO model v2.3 and assimilates only EN3 T/S profile data).

  • HiGEM (High Resolution Global Environmental Modelling) is a UK programme in between NERC (Natural Environment Research Council) and the Hadley Centre of the Met Office. The aim is to advance in the fidelity of simulations of the global environment by taking the new Met Office climate model (HadGEM1a) to unprecedented resolutions. The resulting simulations aim to improve our understanding of mechanisms of climate variability and change on timescales of days to centuries.

  • 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. These data are retrieved missing files that could not be added to the original dataset due to being published with a DOI (http://dx.doi.org/10.5285/4bcfa3a4-c7ec-4414-863d-caeceb21f16f). 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.

  • This Fundamental Climate Data Record (FDCR) ensemble product contains both recalibrated AVHRR/3 MetOp-A Radiance/Brightness Temperature data with associated metrologically traceable uncertainties in the FIDUCEO FCDR format. It also contains files containing an Ensemble dataset consisting of perturbations to the associated FIDUCEO FCDR radiances and brightness temperatures. By applying the 10 perturbations to the baseline FCDR radiances and brightness temperatures a user is able to generate 10 sets of new measurements whose variance capture the associated underlying uncertainty distributions contained in the Easy FCDR itself. The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project AVHRR FCDR improves on existing AVHRR level-1B: in the infrared the calibration has been improved with a measurement function approach such that the data is of better quality (noise has been reduced, outliers have been filtered) the metrologically traceable uncertainties have been derived together with their associated effects, cross-channel correlations and long-term correlation structures have now been calculated from the processed data and are being understood and used to improve data quality and consistency. For the Ensemble product the sensors have been calibrated against the Advanced Along-Track Scanning Radiometer (AATSR) sensor with additional corrections to calibration parameters which make the data better able to derive sea surface temperature estimates that are consistent with theInternational Comprehensive Ocean-Atmosphere Data Set (ICOADS) drifting buoy network. Because the Ensemble has been tuned for Sea Surface Temperature retrieval it should only be used over ocean scenes.

  • 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.

  • This Fundamental Climate Data Record (FDCR) of recalibrated brightness temperatures for the Advanced Very-High-Resolution Radiometer (AVHRR) AVHRR/1, AVHRR/2 andAVHRR/3 with metrologically-traceable uncertainty estimates. Error covariance information is also provided.In this data set , in addition to relative reflectance for channels 1, 2 and 3A( when available) together with estimated independent, common and structured uncertainties are also provided. The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project AVHRR FCDR improves on existing AVHRR level-1B data (such as that processed by NOAA or EUMETSAT): the calibration has been improved with a measurement function approach such that the data is of better quality (noise has been reduced, outliers have been filtered) the metrologically traceable uncertainties have been derived together with their associated effects cross-channel correlations and long-term correlation structures have now been calculated from the processed data and are being understood and used to improve data quality and consistency all the sensors are calibrated to a common reference (AATSR series).The products have been harmonised across the satellite series using Simultaneous (Nadir) Overpasses (SNOs). Full documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation.

  • The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Fundamental Climate Data Record of recalibrated brightness temperatures for the High-resolution Infrared Radiation Sounder (HIRS) contains recalibrated brightness temperatures for HIRS for all editions of HIRS/2, HIRS/2I, HIRS/3, and HIRS/4, with metrologically traceable uncertainty estimates. This version is harmonised and anchored to infrared atmospheric sounding interferometer IASI via MetopA satellite. It contains 40 years worth of data covering the period period 1985-03-10 to 2016-12-31. Each file contains: Basic telemetry: longitude, latitude, time, satellite and solar angles; Brightness temperatures for channels1--19; Independent and structured uncertainty for channels 1--19; A lookup table to convert between radiances and brightness temperatures for channels 1—19; A channel error correlation matrix; Two bitfields indicating identified problems with the data. For any data field that varies across the channels (such as brightness temperatures and their uncertainties). Full documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation.

  • This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1). COSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the "topHSPF" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model. CSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model

  • "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.

  • Datasets of 5 day back trajectories have been computed on a routine basis using analyses from the European Centre for Medium Range Weather Forecasting (ECMWF). The three components of the wind and surface pressure over three launch grids covering the UK, the mid-Atlantic storm track region and the eastern USA, plus back trajectories from field campaign instrument sites were used to output datasets consisting of latitude, longitude and pressure of the trajectory every 30 minutes. This dataset contains ECMWF trajectories model forecast data for 1997.