NERC EDS Centre for Environmental Data Analysis
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This dataset collection contains air quality data from the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme 'Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)'.
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from University of Western Ontario (UWO)'s Lufft CHM15k "Nimbus" deployed at Western, Canada. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-73009. Details for this WIGOS station are presently unavailable in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from Met Office's Lufft CHM15k "Nimbus" deployed at Camborne, Uk. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-03808. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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Data for Figure SPM.5 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure SPM.5 shows changes in annual mean surface temperatures, precipitation, and total column soil moisture. --------------------------------------------------- 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: IPCC, 2021: Summary for Policymakers. 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. 3−32, doi:10.1017/9781009157896.001. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has four panels with 11 maps. All data is provided, except for panel a1. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains: - Annual mean temperature change (°C) (relative to 1850-1900) - Annual mean precipitation change (%) (relative to 1850-1900) - Annual mean soil moisture change (standard deviation of interannual variability) (relative to 1850-1900) The data is given for global warming levels (GWLs), namely +1.0°C (temperature only), +1.5°C, 2.0°C, and +4.0°C. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - Data file: Panel_a2_Simulated_temperature_change_at_1C.nc, simulated annual mean temperature change (°C) at 1°C global warming relative to 1850-1900 (right). Panel b: - Data file: Panel_b1_Simulated_temperature_change_at_1_5C.nc, simulated annual mean temperature change (°C) at 1.5°C global warming relative to 1850-1900 (left). - Data file: Panel_b2_Simulated_temperature_change_at_2C.nc, simulated annual mean temperature change (°C) at 2.0°C global warming relative to 1850-1900 (center). - Data file: Panel_b3_Simulated_temperature_change_at_4C.nc, simulated annual mean temperature change (°C) at 4.0°C global warming relative to 1850-1900 (right). Panel c: - Data file: Panel_c1_Simulated_precipitation_change_at_1_5C.nc, simulated annual mean precipitation change (%) at 1.5°C global warming relative to 1850-1900 (left). - Data file: Panel_c2_Simulated_precipitation_change_at_2C.nc, simulated annual mean precipitation change (%) at 2.0°C global warming relative to 1850-1900 (center). - Data file: Panel_c3_Simulated_precipitation_change_at_4C.nc, simulated annual mean precipitation change (%) at 4.0°C global warming relative to 1850-1900 (right). Panel d: - Data file: Figure_SPM5_d1_cmip6_SM_tot_change_at_1_5C.nc, simulated annual mean total column soil moisture change (standard deviation) at 1.5°C global warming relative to 1850-1900 (left). - Data file: Figure_SPM5_d2_cmip6_SM_tot_change_at_2C.nc, simulated annual mean total column soil moisture change (standard deviation) at 2.0°C global warming relative to 1850-1900 (center). - Data file: Figure_SPM5_d3_cmip6_SM_tot_change_at_4C.nc, simulated annual mean total column soil moisture change (standard deviation) at 4.0°C global warming relative to 1850-1900 (right). --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblink is provided in the Related Documents section of this catalogue record: - Link to the report webpage, which includes the component containing the figure (Summary for Policymakers), the Technical Summary (Figures TS.3 and TS.5) and the Supplementary Material for Chapters 1, 4 and 11, which contains details on the input data used in Tables 1.SM.1 (Figure 1.14), 4.SM.1 (Figures 4.31 and 4.32) and 11.SM.9 (Figure 11.19).
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from Hungarian Meteorological Service (OMSZ)'s Lufft CHM15k "Nimbus" deployed at Budapest, Hungary. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-12843. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from MeteoSwiss's Vaisala CL31 deployed at Mohlin, Switzerland. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06641. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from Météo-France's Vaisala CL31 deployed at Lyon, France. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-07481. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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Daily concatenated files of ceilometer cloud base height and aerosol profile data from Météo-France's Vaisala CL31 deployed at St Auban, France. These data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide. The site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-07588. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. EUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities.
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The Meteosat Second Generation (MSG) satellites, operated by EUMETSAT (The European Organisation for the Exploitation of Meteorological Satellites), provide almost continuous imagery to meteorologists and researchers in Europe and around the world. These include visible, infra-red, water vapour, High Resolution Visible (HRV) images and derived cloud top height, cloud top temperature, fog, snow detection and volcanic ash products. These images are available for a range of geographical areas. This dataset contains cloud and snow mask product images from MSG satellites over the tropics. Imagery available from March 2005 onwards at a frequency of 15 minutes (some are hourly) and are at least 24 hours old. The geographic extent for images within this datasets is available via the linked documentation 'MSG satellite imagery product geographic area details'. Each MSG imagery product area can be referenced from the third and fourth character of the image product name giving in the filename. E.g. for EEAO11 the corresponding geographic details can be found under the entry for area code 'AO' (i.e West Africa).
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This dataset contains estimations of Arctic sea level anomalies produced by the ESA Sea Level Climate Change Initiative project (Sea_level_cci), based on satellite altimetry from the ENVISAT and SARAL/Altika satellites. It has been produced by Collecte Localisation Satellites (CLS) and the Plymouth Marine Laboratory (PML). The retrieval of sea level in the Arctic sea ice covered region requires specific processing steps of the satellite altimetry measurements. For this dataset, a specific radar waveform classification method has been applied based on a neural network approach, and the waveform retracking is based on a new adaptive retracking that is able to process both open ocean and peaky echoes measured in leads without introducing any bias between the two types of surfaces. Editing and mapping processing steps have been optimized for this dataset