This dataset contains the input data (initial conditions, boundary conditions, initial perturbations) for Met Office Unified Model simulations performed during the PRESTO (PREcipitation STructures over Orography) project. It also contains the 2D and 3D output files from these simulations. The PRESTO project was funded by the Natural Environment Research Council (NERC) with the grant references - NE/I024984/1 and NE/I026545/1 - led by Professor Suzanne Gray (University of Reading) and Professor David Schultz (University of Manchester). PRESTO provided a leap forward in the understanding and prediction of quasi-stationary orographic convection in the UK and beyond. This was achieved through an intensive climatological analysis over several regions of the globe where continuous radar data was available, which identified the environmental conditions that support the bands and their characteristic locations and morphologies. Complementary high-resolution numerical simulations pinpointed the underlying mechanisms behind the bands and their predictability in numerical weather prediction models. This work provides positive impacts for the forecasting community, general public, and other academics in the field. Forecasters benefit from the identification of simple diagnostics that can be used operationally to predict these events based on available model forecasts and/or upstream soundings. A series of activities were used to directly engage with forecasters to effectively disseminate our findings. The public benefit from this improved forecasting of potentially hazardous precipitation events. The academic community benefit from the advanced physical understanding (which was disseminated through conferences, workshops, and peer-reviewed publications) and the numerous international collaborations associated with this project.

The Global Ozone Monitoring Experiment (GOME) was an instrument aboard ERS-2. The main scientific objective of the GOME mission is to measure the global distribution of ozone and several trace gases which play an important role in the ozone chemistry of the Earth's stratosphere and troposphere, for example, NO2, BrO, OClO, and SO2. This dataset contains version 1.2 ozone profiles derived by the Remote Sensing Group (RSG) at the STFC Rutherford Appleton Laboratory, Oxfordshire, UK, as part of the National Centre for Earth Observation (NCEO). These were derived from radiances measured by the GOME on-board ERS-2. The collection also includes total column ozone, column BrO, and column NO2 as well as cloud heights derived from the Along Track Scanning Radiometer (ATSR), which are included to aid interpretation of the ozone profiles.

This dataset contains coupled physical-biogeochemical ocean second generation Canadian Earth System Model (CanESM2) simulation outputs using the 1 degree NEMO-HadOCC model. The model output contains 3D Digital Image Correlation (DIC), alkalinity, temperature and salinity datasets at annualy-averaged frequency and monthly averaged surface ocean CO2 fugacities and fluxes. Job IDs included in this dataset: CanESM2 surface fluxes (started on 18th for first, 21st for second, and on the 19th for other 2): RCP85: u-ao419 RCP26: u-ao519 Constant atm CO2: RCP85: u-ao529 RCP26: u-ao531 (reduce walltime for nemo to test) This data was collected in support of CURBCO2: Carbon Uptake Revisited - Biases Corrected using Ocean Observations, a Natural Environment Research Council (NERC) funded project (NERC Grant NE/P015042/1). The overarching aim of this project was to provide UK and international governments with the best possible impartial information from which they can plan how best to work towards the global warming targets (the 'Paris Agreement') set at the Paris Climate Conference in December 2015.

The "ISOMAP UK" project was a combined data-modelling investigation of water isotopes and their interpretation during rapid climate change events project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00460 - Duration 1 May 2003 - 30 Apr 2008) led by Prof J.A. Holmes of the University College London, with co-investigators at the University of Southampton, University of Liverpool, University of Manchester, University of Bristol and the NERC British Antarctic Survey. This dataset contains comparison of high-resolution isotope records from terrestrial archives in NW Europe with model simulations of isotopes in precipitation. This is a control 9K simulation, and a freshwater hosing experiment. The freshwater hosing experiment had 5Sv of freshwater added to the North Atlantic for 1 year. The freshwater forcing was then removed and the model allowed to adjust. 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.

Measurements from a LI-COR LI-7500 open path gas analyser operating at infra-red wavelengths deployed at the Chilbolton Facility for Atmospheric and Radio Research site in Chilbolton, Hampshire. The instrument measures the absorption due to carbon dioxide at specific wavelengths along its 0.125m measurement path. Internally-stored calibration data are used to convert these absorption values to a mole concentration for each gas. Carbon dioxde and water vapour mole concentrations from this instrument are also provided with sonic anemomenter data at a 20Hz data acquisition rate for eddy covariance calculations in another CFARR dataset. Measurements are taken at 10s intervals and are archived at this temporal resolution. Data are in netCDF.

The University of Aberystwyth mobile ozone lidar data contain measurements of ozone mixing ratios and aerosol information. The data were collected at Chilbolton observatory, Hampshire on the 7th and the 8th of June 2005. The data collected on the 7th of June 2005 are of ozone mixing ratios only. The data collected on the 8th of June 2005 are of ozone mixing ratios, aerosol backscatter, and boundary layer height information.

The Cloud_cci ATSR2-AATSRv3 dataset (covering 1995-2012) 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 the ATSR2 and AATSR instruments (onboard the ERS2 and ENVISAT 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 ATSR2-AATSRv3 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 ATSR2-AATSR 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/ATSR2-AATSR/V003. To cite the full dataset, please use the following citation: Poulsen, Caroline; McGarragh, Greg; Thomas, Gareth; Stengel, Martin; Christensen, Matthew; Povey, Adam; Proud, Simon; Carboni, Elisa; Hollmann, Rainer; Grainger, Don (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci ATSR2-AATSR L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD) and Rutherford Appleton Laboratory (Dataset Producer), DOI:10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003

Cloud base and backscatter data from the Met Office's Camborne Cl31 ceilometer located at Camborne, Cornwall. 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.

Data for Figure 3.38 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.38 shows model evaluation of ENSO teleconnection for 2m-temperature and precipitation in boreal winter (December-January-February). --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- Data provided for all panels in one single directory --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains observed global patterns for: - temperature from the Berkeley Earth dataset over land - temperature from ERSSTv5 over ocean - precipitation from GPCC over land (shading, mm day–1) - precipitation from GPCP worldwide (contours, period: 1979-2014) and distributions of regression coefficients in IPCC regions for: - temperature - precipitation --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- maps: - reg_tas_NINO34_BEST_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over land) - reg_sst_NINO34_ERSSTv5_ERSSTv5_1901_2018_DJF.nc (var = 'rc', upper map over ocean) - reg_precip_NINO34_GPCP_ERSST5_1979_2018_DJF.nc (var = 'rc', lower map, contours) - reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc (var = 'rc', lower map, shading) histograms: - tas_enso_regression_pdf_v4_no_cosweight_DJF.nc . upper grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - tas_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dashed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for temperature: 'EAU/RFE/RAR/NWN/NCA/ENA/NSA/MED/NWS/ESAF' (see variable region_info with attributes making the association between the region index and the acronym/name). - pr_enso_regression_pdf_v4_no_cosweight_DJF.nc . lower grey histograms: var = 'region_pdfx_hist' and 'region_pdfy_hist' . MME (black line): var = 'region_ave_hist' . Observations (blue lines): var = 'region_obs' - pr_amip_hist_enso_regression_pdf_v4_no_cosweight_DJF.nc (orange dahsed line): var = 'region_ave_amip_hist' => Fields correspond to regions numbers with labels in the plot, namely for precipitation: 'EAS/SEA/EAU/WNA/NCA/SES/NSA/ESAF/SEAF/MED' (see variable info_region with attributes making the association between the region index and the acronym/name). ENSO is the El Niño Southern Oscillation. GPCC is the Global Precipitation Climatology Centre. GPCP is the Global Precipitation Climatology Project. --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Data provided in reg_pr_NINO34_GPCC_ERSSTv5_1901_2016_DJF.nc are in mm/month. Values should be divided by 30 for plotting in mm/day. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1 - Link to the figure on the IPCC AR6 website

DESIRE (Dynamics of the Earth System and the Ice-Core Record) was part of QUEST (Quantifying and Understanding the Earth System) Theme 2. This dataset contains measurements of chemical traces and meteorological from the TOMCAT (Tropospheric Offline Model of Chemistry and Transport model), as part of the Work Package 1.3. The aim of this work package was to identify any atmospheric chemical signal preserved in the ice-core record that could be used to differentiate between the influences on atmospheric methane of changes in methane emissions and changes in oxidising capacity between the Last Glacial Maximum (LGM) and the pre-industrial era (PI). A series of experiments was carried out using the Cambridge parallelised-Tropospheric Offline Model of Chemistry and Transport (p-TOMCAT; v2.0 beta), the results to which are contained in this dataset.