HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). Version 3.0.2 was added due to a correction to the land-sea mask used. More details can be found in the HadEX3 blog under 'Details/Docs' tab.

This dataset consists of 5x5 historical simulations (1850-2014) with HadGEM3-GC3.1 (Met Office Hadley Centre Global Coupled model General Circulation 3.1). This is an ensemble dataset, part of the Securing Multidisciplinary UndeRstanding and Prediction of Hiatus and Surge events (SMURPHS) project. The model version used here is a development version of the UK's submission to Coupled Model Intercomparison Project Phase 6 (CMIP6) and differs from the CMIP6 version in its treatment of prescribed ozone. This ensemble was designed to sample a range in plausible historical aerosol forcing, with the present-day aerosol effective radiative forcing ranging from -0.38 W/m2 to -1.5 W/m2, which spans a large range of the total aerosol effective radiative forcing presented in Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The targeted aerosol forcings were achieved by applying a constant scaling factor in space and time to the standard historical CMIP6 historical AA and precursor emissions, namely organic and black carbon (fossil and biofuel) and sulfur dioxide (SO2) emissions. All other forcing agents follow historical CMIP6 emissions. The scalings were chosen such that the targeted aerosol forcings are approximately equally spaced: - 0.2x scaling to give -0.38 W/m2 - 0.4x scaling to give -0.60 W/m2 - 0.7x scaling to give -0.93 W/m2 - 1.0x scaling to give -1.17 W/m2 - 1.5x scaling to give -1.50 W/m2. The scalings required to reach the intended forcing values were determined from 5 10-year atmosphere-only time-slice runs for the year 2014 with pre-industrial sea-surface temperatures. Note that the 1x scaling is not strictly a ‘scaling’ but corresponds to the standard emissions. The configuration for the scaled aerosol simulations was derived from the 1x scaling simulations, therefore these are directly comparable with the only difference being the scaled aerosol emissions. Five simulations were performed for each scaling and the simulations cover the period 1850-2014. The same five initial conditions were used for each scaling sub-ensemble, and the first four correspond to the initial conditions selected for the four CMIP6 historical simulations. These were well spaced in a pre-industrial control simulation and sample different phases of internal variability in both the Pacific and Atlantic. We recommend only analysing data from 1900, as introducing the scaled aerosols in 1850 produces a small initial drift in the climate system. We estimate that most of this drift has been removed by 1900. The reference paper for this dataset is Dittus et al., 2020. Please cite this paper when using the dataset. Dittus, A. J., Hawkins, E., Wilcox, L. J., Sutton, R. T., Smith, C. J., Andrews, M. B. and P. M. Forster, 2020: Sensitivity of historical climate simulations to uncertain aerosol forcing. In press, Geophysical Research Letters

This dataset contains results in support of a publication that investigates processes affecting water vapour entry to the stratosphere. The back trajectories were calculated using the OFFLINE trajectory model. Past publications have shown the key processes are temperatures in the tropical tropopause layer and large-scale transport into the stratosphere using trajectory methods. Lagrangian Dry Points (LDPs) are normally calculated as the minimum water vapour saturation mixing ratio experienced along a back-trajectory that has traversed from troposphere to tropical lower stratosphere in its recorded history. This study separated the two key processes by sampling alternative temperatures. These alternative temperatures are either time-shifted or averaged in time or longitude. This method is applied for two meteorological datasets: ERA-Interim (ERA-I) reanalysis for the period 1999-2009, and the UM-UKCA chemistry-climate model for eleven years of a repeat-year-2000 forcing scenario. The ERA-I trajectories were calculated by S Fueglistaler and S Liu for separate publications. The UM-UKCA climate model scenario was conducted by A Maycock. This dataset contains only the LDPs resulting from alternative-temperature sampling. The directory UM-UKCA/LDP-original-T/ provides a simple view of the original unmodified method to calculate LDPs. LDP-alt-T/ directories contain LDPs determined with time-shifted alternative temperature samplings. The time-shift is identified by the alternative initialisation date, denoted in the filename and file metadata. LDP-ave-T/ directories contain LDPs determine with averaged alternative temperature samplings. The averaging is identified by the variable name and metadata. In the variable names, shorthand and full-name identifiers include 6h (6 hourly instantaneous), ZM (zonal mean), 30DZM (30-day rolling window mean and zonal mean), 120DM, 90DM, 60DM, 30DM, 15DM, 14DM, 8DM, 7DM, 4DM, 2DM, 1DM (rolling window 120 day mean, 90 day mean, etc.). Note that various alternative temperatures are recorded at each LDP calculated from each alternative temperature. For more information on the directory structure, file naming conventions, variable naming conventions and attribute conventions please see the README.txt.

The future Climate Predictions for Africa (CP4A-future) data were produced using the Met Office's Unified Model (4.5km horizontal grid spacing), the IMPALA (Improving Model Processes for African cLimAte) project ran a ten-year timeslice simulation that is representative of end the 21st century (2095-2105) using a 30-year averaged sea surface temperature (SST) anomaly (2085-2115 relative to 1975-2005). Parameters include (but not limited to); near-surface air temperature, outgoing longwave radiation, surface latent heat flux and surface sensible heat flux. The NERC funded IMPALA project is within the Future Climate for Africa (FCFA) programme. Here a subset of variables of the data produced is provided in NetCDF format for community reuse, variables are available at a range of temporal frequencies.

Ten years of present-day 25km regional pan-Africa (P25: Present) data were produced by the NERC funded IMPALA (Improving Model Processes for African cLimAte) project team using the Met Office Unified Model and are valid from 1997-2007. Parameters include (but not limited to); near-surface air temperature, outgoing longwave radiation, surface latent heat flux and surface sensible heat flux. The IMPALA project is within the Future Climate for Africa (FCFA) programme. Here a subset of variables of the data produced is provided in NetCDF format for community reuse, variables are available at a range of temporal frequencies.

Ten years of present-day Climate Predictions for Africa (CP4A-present) data were produced by the NERC funded IMPALA (Improving Model Processes for African cLimAte) project team using the Met Office Unified Model (4.5km horizontal grid spacing) and are valid from 1997-2007. Parameters include (but not limited to); near-surface air temperature, outgoing longwave radiation and surface sensible heat flux. The IMPALA project is within the Future Climate for Africa (FCFA) programme. Here a subset of variables of the data produced is provided in NetCDF format for community reuse, variables are available at a range of temporal frequencies.

The future 25km regional pan-Africa (P25: Present) data were produced using the Met Office's Unified Model, the IMPALA (Improving Model Processes for African cLimAte) project ran a ten year timeslice simulation that is representative of end the 21st century (2095-2105) using a 30-year averaged sea surface temperature (SST) anomaly (2085-2115 relative to 1975-2005). Parameters include (but not limited to); near-surface air temperature, outgoing longwave radiation, surface latent heat flux and surface sensible heat flux. The NERC funded IMPALA project is within the Future Climate for Africa (FCFA) programme. Here a subset of variables of the data produced is provided in NetCDF format for community reuse, variables are available at a range of temporal frequencies.

HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). Version 3.0.3 was added due to an error in how the Rx1day and Rx5day data were being handled for one of the West African data sources. More details can be found in the HadEX3 blog under 'Details/Docs' tab.

HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). In September 2020, a user identified some issues in the DTR and TN90p (61-90) indices. These were found to have arisen from erroneous values in a few stations which were not picked up by any quality control checks. These stations were noted on the bad list and these two indices re-run, hence v3.0.1.

HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110').