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) projcet Advanced Very-High-Resolution Radiometer (AVHRR ) Climate Data Record for Aerosol Optical Depth (AOD) dataset covers Europe and North Africa over land. It was inferred from AVHRR/3 instruments on board the NOAA-16 and NOAA-18 satellites. The dataset is provided on 3 processing levels: superpixels (L2B: 12x12 km2at nadir), gridded (1°x 1°) daily (L3 daily) and monthly (L3 monthly). The original lowest processing level (on selected dark field pixels) is not provided to users, but can be made available on request. The product contains the best AOD estimate but also a more detailed information on different aerosol types (most likely AOD value based on a multi-model ensemble climatology of the aerosol type and a 36 member ensemble of AOD values for a wide range of aerosol types spanning a realistic range in the atmosphere). A user can also process an application with all 36 ensemble members and then calculate the spread of the application results. Note that AOD values on the lowest processing level can be (slightly) negative reflecting radiometric calibration uncertaintiesand keeping un-cut AOD distributions. The products contain on all levels sophisticated and detailed estimates of total AOD uncertainties propagated from the input L1B products and the retrieval algorithm through all levels of the processing chain. These total uncertainties can be directly used for data assimilation or to constrain a confidence interval around the AOD solutions. AOD uncertainties are also kept separated into the (relevant) different parts with different correlation structures, so that a user can conduct averaging and uncertainty propagation as suitable for the intended applications. Uncertainties also include separate values for the dominant effects (reflectance inversion, albedo estimation, aerosol type, cloud masking); also estimates of a sampling uncertainty (due to missing pixels from the cloud masking or from failed inversions) are contained. More information including a report on the datset and scientific background is availible in the documentation section.

The MVIRI Aerosol Optial depth demonstration dataset contains the aerosol optical thickness (AOT) as retrieved from the visible channel of the Meteosat Visible and Infrared Imager (MVIRI) operated on board Meteosat First Generation (MFG) spacecrafts. The channel is centred around 0.7 µm but the spectral coverage of this channel is very broad. The dataset is produced for 2 of the 7 Meteosat satellites, Meteosat -5 and Meteosat-7, that were operated during the period between 1991 and 2007. While Meteosat-7 was, during the considered period, positioned above 0° longitude, Meteosat-5 was moved from 0° to 63° longitude in support of the INDOEX Experiment in 1998, with continued service in the course of the Indian Ocean Data Coverage (IODC) mission. The aerosol optical thickness (AOT) was retrieved from the MVIRI fundamental climate data record (FCDR) using the Combined Inversion of Surface and AeRosol (CISAR) Algorithm. Both datasets were produced as part of the FIDUCEO (Fidelity and uncertainty in climate data records from Earth Observations) EU Horizon 2020 project. The primary objective of this data record is to assess and demonstrate how the recalibrated and uncertainty-quantified MVIRI FCDR can support improved retrieval of geophysical parameters. Of particular interest is the impact of in-flight reconstructed and spectrally degrading spectral response functions. More information is available in the MVIRI Report and Release Note in the documentation

The MVIRI Albedo and Uncertainties demonstration dataset contains the broadband surface albedo as retrieved from the visible channel of the Meteosat Visible and Infrared Imager (MVIRI) operated on board Meteosat First Generation (MFG) spacecrafts. The channel is centered around 0.7 µm but the spectral coverage of this channel is very broad. The dataset is produced for 2 of the 7 Meteosat satellites, Meteosat -5 and Meteosat-7, that were operated during the period between 1991 and 2007. While Meteosat-7 was, during the considered period, positioned above 0° longitude, Meteosat-5 was moved from 0° to 63° longitude in support of the INDOEX Experiment in 1998, with continued service in the course of the Indian Ocean Data Coverage (IODC) mission. The albedo data was retrieved from the MVIRI fundamental climate data record; both were produced as part of the FIDUCEO (Fidelity and uncertainty in climate data records from Earth Observations) EU Horizon 2020 project.

This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. The data represents mean global temperature anomalies with respect to the baseline periods 1981-2000, 1961-1990 or 1981-2010, and cover the period 1861 to 2100.

This dataset provides 100 model realisations of daily river flow in cubic metres per second (m3/s) for 1,366 catchments, for the period 1962 to 2015. The dataset is model output from the DECIPHeR hydrological model driven by observed climate data (CEH-GEAR rainfall and CHESS-PE potential evapotranspiration). The modelled catchments correspond to locations of National River Flow Archive (NRFA) gauging stations and provide good spatial coverage across the UK. The dataset was produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) to provide national scale probabilistic flow simulations and predictions for UK drought risk analysis. MaRIUS was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity. Full details about this dataset can be found at https://doi.org/10.5285/d770b12a-3824-4e40-8da1-930cf9470858

This dataset contain inventories of the impacts of invasive alien species (IAS) in Brazil, Chile, and Argentina. These include seven case studies: pines (Pinus contorta) in the Araucanía and Aysén Regions (Chile); (ii) pines (Pinus contorta) in the Northern Patagonia Region (Argentina); (iii) privet (Ligustrum lucidum) in the Yungas Forest (Argentina); (iv) invasive grasses (Urochloa brizantha and Urochloa decumbens) in the Cerrado (Brazil); (v) the American mink (Neovison vison) in Austral Patagonia (Argentina); (vi) the American mink in the Los Ríos Region (Chile); and, (vi) the yellow jacket wasps (Vespula germanica) in the Los Ríos Region (Chile). The impacts were elicited by experts (varying between two and four experts for each case study) following the procedures described in the supporting files. A total of 1,526 impacts were identified by the experts, and these impacts can be found in the "Compiled-Impact.csv" file. This file contains information about the impact outcome, impact mechanism, EICAT impact category, level of confidence, the species or asset impacted, the direction of the impact, the extent of the study area, the name of the IAS, whether the IAS is a plant or an animal, and the country. After two rounds of scoring, the impacts listed in the “Compiled-Impact.csv” were further discussed during a facilitated workshop in San Carlos de Bariloche (Argentina; December 2019). The final, agreed impact scores can be found in the file "Unique-Impact.csv". This final dataset contains 209 impacts and information about the same variables described above for the “Compiled-Impact.csv” file. Full details about this dataset can be found at https://doi.org/10.5285/d00a647a-16ec-4d2a-a3a3-ad59597e8ca2

This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. The data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 23 river basin regions in the UK is provided. The Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to.

This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. The data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 16 administrative regions in the UK is provided. The Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to.

The The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Upper Tropospheric Humidity (UTH) Climate Data Record version 1.2 dataset is derived from satellite brightness temperatures and uncertainties from the FIDUCEO Microwave Fundamental Climate Data Record (FCDR). The instantaneous observations from the FIDUCEO Microwave FCDR are used to derive a spatio-temporal averaged data record, which contains monthly mean UTH and brightness temperature mapped to a regular latitude/longitude grid covering the tropical region (-30° to 30° N), with a spatial resolution of 1° x 1°. It covers all mission years of the Special Senson Microwave for Temperature (SSMT2) instrument on the F11, F12, F14, F15 satellites, the Advanced Mircowave Sounding Unit (AMSU-B ) instrument on the NOAA 15-17 satellites and the Microwave Humidity Sounder (MHS) instruments on the NOAA18, NOAA19, MetopA, Metop-B satellites. Full documentation including product user guide, tutorials and relevant publications are available in the documentation