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Uncertainty

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  • 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 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 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 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 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.

  • 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 8 'country' regions in the UK is provided: Channel Islands, England, England and Wales, Isle of Man, Northern Ireland, Scotland, United Kingdom, Wales. 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 periods 1961-1990, 1981-2000 and 1981-2010, and cover the period 1 Dec 1960 to 30 Nov 2099. Gridded data on a 25km grid over the United Kingdom, the Isle of Man and the Channel Islands 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 FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Sea and Lake Surface Temperature Climate Data Record core retrieved quantity is the skin (radiometric) temperature of the Earth’s water surfaces (sea and large lakes). This is provided as a best estimate, plus an ensemble of 10 perturbations capturing known uncertainties. The CDR contains grid-cell instantaneous averagesof retrieved surface temperature over ice-free oceans and 300 large lakes. The FIDUCEO Surface Temperature CDR differs from the ESA Sea Surface Temperature Climate Change Initiative CDRs ; which were generated using in the using the same cloud detection and SST retrieval methodology in the following points: - The calibration of the brightness temperatures used is revised for the FIDUCEO ST CDR. The first step in this has been multi-sensor harmonisation to obtain baseline calibration coefficients (Giering et al., 2019). For specific ST application, these coefficients were adjusted such that SSTs had lower bias, using a method of cross-referencing to matched drifting buoys (Merchant et al., 2019) - Perturbations to the obtained ST and quality level determination are provided for an ensemble of 10 members, for the purpose of propagating uncertainty in ST in complex (large scale, non-linear) applications. - The FIDUCEO ST CDR includes retrievals over the world’s 300 largest lakes, unlike the SST-only product. (Lakes, including much smaller lakes,are addressed in other CDRs requiring significantly different methodsto cope with the difficulties of small target water bodies.) Full documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation.

  • The FIDUCEO Microwave Fundamental Climate data record, v4.1, contains microwave brightness temperatures and uncertainties for series of satellite instruments (all mission years of SSMT2 on F11, F12, F14, F15; AMSU-B on NOAA15, NOAA16 and NOAA17; and MHS missions (NOAA18, NOAA19, MetopA,-B)). The presented FCDR is a long data record of increased consistency among the instruments compared to the operational data record and is a long enough data record to generate climate data records (CDRs) for climate research. The improvements are based on the strict application of the measurement equation as well as dedicated corrections and improvements within the calibration process. The data record contains quantified uncertainty components, respecting the correlation behaviour of underlying effects. Full documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation