#---------------------------------------------------------------------------- # HINDCAST DATA FROM THE UREAD-ECM1.0 MODEL: DECADAL PREDICTION EXPERIMENTS # # CREATORS: Emma Suckling, Ed Hawkins, University of Reading # # NOTE: Decadal prediction is still experimental and the forecasts should # not be relied on for making decisions. #---------------------------------------------------------------------------- 0. SECTIONS ------------- 1. Project 2. Dataset 3. Terms of Use 4. Content 5. Method and Processing 6. Associated Datasets 1. PROJECT ------------ Title: SPECS - Seasonal-to-decadal Prediction for the Improvement of European Climate Services Funding organisation: European Commission (EU FP7) Grant no.: 308378 2. DATASET ------------ Title: University of Reading Empirical Climate Model Version 1.0 (UREAD-ECM1.0): Decadal Prediction Experiment Description: Each zip file contains ensemble hindcast data for annual mean (Jan-Dec) surface air temperature anomalies covering the period 1960-2014, with start dates every year, generated from the UREAD empirical model. The data is intended as a benchmark model for the decadal prediction experiments. Each hindcast set is generated using a different prediction mode. The 'standard' model configuration data also contains a forecast ensemble covering the period 2016-2025 (with a 2015 launch date). All anomalies are given relative to the mean of 1961-1990. For more information about the model and experimental design see: E. Suckling, et al., An empirical model for probabilistic decadal prediction: A global attribution and regional hindcasts, Climate Dynamics (2016) Publication Year: 2016 Creator(s): Emma Suckling, Ed Hawkins Organisation(s): University of Reading 3. TERMS OF USE ----------------- This dataset is made available under the terms of the Creative Commons Attribution 4.0 International licence (CC BY 4.0): https://creativecommons.org/licenses/by/4.0/. 4. CONTENT ------------ File listing 1) UREAD-ECM1.0_DecadalHindcasts_standard.zip: A directory containing hindcast data (for annual mean surface air temperature anomalies) from the decadal prediction experiments using the standard configuration of the empirical model (in 'exploiting the trend' prediction mode). This directory also contains a 51 member forecast ensemble covering the period 2016-2025 (tas_yr_UREAD-ECM1.0_decadal2015_rXi1p1.nc, where X is the ensemble member number - r0i1p1 indicates the ensemble mean and r1i1p1_best indicates the deterministic model from the best fit parameters). 2) UREAD-ECM1.0_DecadalHindcasts_prescribed.zip: A directory containing hindcast data (for annual mean surface air temperature anomalies) from the decadal prediction experiments under a 'prescribed forcing' prediction mode. 3) UREAD-ECM1.0_DecadalHindcasts_realtime.zip: A directory containing hindcast data (for annual mean surface air temperature anomalies) from the decadal prediction experiments under a 'real-time' prediction mode. Additional information Organisation of files: The files in each directory are named according to the CMIP5/CMIP6 file naming convention. See further information below and at: K. E. Taylor, and C. Doutriaux: CMIP5 Model Output Requirements: File Contents and Format, Data Structure and Metadata, http://cmip-pcmdi.llnl.gov/cmip5/docs/CMIP5_output_metadata_requirements.pdf, 2011. K. E. Taylor, V. Balaji, S. Hankin, M. Juckes, B. Lawrence, and S. Pascoe: CMIP5 Data Reference Syntax (DRS) and Controlled Vocabularies, http://cmip-pcmdi.llnl.gov/cmip5/docs/cmip5_data_reference_syntax.pdf, 2012. File formats and structure: NetCDF format; one file per ensemble member and hindcast start date Versions: 1.0 5. METHOD and PROCESSING -------------------------- The empirical model uses historical observations of surface air temperature anomalies, natural and anthropogenic forcing and an ENSO (Nino3.4) index to generate ensemble decadal hindcasts with lead times of 1-10 years. Hindcasts are started each year from 1960-2014 and each contain 51 ensemble members. Annual mean (Jan-Dec) surface air temperature anomaly hindcasts are contained in this deposit and are separated into one netCDF file per ensemble member and hindcast start date. Attributes of the netCDF files: Experiment: Decadal Naming convention: rXiYpZ rX: Realization (or ensemble member number) => 1->51 iY: Initialisation strategy => 0=forcing only 1=forcing + ENSO ('standard model') pZ: Physics version => 1=exploiting the trend ('standard model') 2=prescribed forcing 3=real-time The standard model version files are therefore have the form: rXi1p1 netCDF Example Global Attributes: :INSTITUTION = "University of Reading" ; :INSTITUTE_ID = "UREAD" ; :EXPERIMENT_ID = "decadal1960" ; :MODEL_ID = "ECM1.0" ; :CONTACT = "Emma Suckling , Ed Hawkins " ; :COMMENT = "University of Reading Empirical Climate Model: A benchmark for the decadal prediction experiments" ; :ASSOCIATED_EXPERIMENT = "decadal_r1i1p1" ; :ASSOCIATED_MODEL = "UREAD-ECM1.0" ; :CONVENTIONS = "CF-1.6" ; :FORECAST_REFERENCE_TIME = "1960-07-01(T00:00:00Z)" ; :FREQUENCY = "year" ; :INITIALIZATION_METHOD = "1" ; :INITIALIZATION_DESCRIPTION = "Initial conditions come from the anthropogenic and solar forcing and the ENSO index" ; :MODELLING_REALM = "atmos" ; :PHYSICS_VERSION = "1" ; :PHYSICS_DESCRIPTION = "Forced with anthropogenic forcings, solar and volcanic forcing from CMIP5 and the ENSO (Nino3.4) index. Model trained using an \"exploiting the trend\" prediction mode. See: E. Suckling, et al., An empirical model for probabilistic decadal prediction: A global attribution and regional hindcasts, Climate Dynamics (2016)" ; :PROJECT_ID = "SPECS" ; :REALISATION = "1" ; :STARTDATE = "S1960701" ; Input data sources: 1) Surface air temperature observations: Cowtan, K. and Way, R. G. (2014), Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends, Q.J.R. Meteorol. Soc., 140: 1935-1944. doi: 10.1002/qj.2297 http://www-users.york.ac.uk/~kdc3/papers/coverage2013/methods.html 2) Historical forcing data: Meinshausen, M., S. J. Smith, K. V. Calvin, J. S. Daniel, M. L. T. Kainuma, J.-F. Lamarque, K. Matsumoto, S. A. Montzka, S. C. B. Raper, K. Riahi, A. M. Thomson, G. J. M. Velders and D. van Vuuren (2011), The RCP Greenhouse Gas Concentrations and their Extension from 1765 to 2300, Climatic Change (Special Issue), DOI: 10.1007/s10584-011-0156-z http://www.pik-potsdam.de/~mmalte/rcps/ 3) SST indices: Climate Explorer - https://climexp.knmi.nl/selectindex.cgi?id=someone@somewhere 6. ASSOCIATED DATASETS ------------------------ The set of hindcasts in this deposit correspond to the 2016-2025 forecast ensemble. Equivalent hindcast sets for future forecasts will be made available in due course.