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Dataset

 

A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years

Update Frequency: Unknown
Latest Data Update: 2019-09-19
Status: Underdevelopment
Online Status: ONLINE
Publication State: Citable
Publication Date: 2019-09-20
DOI Publication Date: 2019-10-25
Download Stats: last 12 months
Dataset Size: 222 Files | 675GB

This dataset has been superseded. See Latest Version here
Abstract

We present a continuous land climate reconstruction dataset extending from 60 kyr before present to the pre-industrial period at 0.5deg resolution on a monthly timestep for 0degN to 90degN. It has been generated from 42 discrete snapshot simulations using the HadCM3B-M2.1 coupled general circulation model. We incorporate Dansgaard-Oeschger (DO) and Heinrich events to represent millennial scale variability, based on a temperature reconstruction from Greenland ice-cores, with a spatial fingerprint based
on a freshwater hosing simulation with HadCM3B-M2.1. Interannual variability is also added and derived from the initial snapshot simulations. Model output has been downscaled to 0.5deg resolution (using simple bilinear interpolation) and bias corrected using either the University of East Anglia, Climate Research Unit observational data (for temperature, precipitation, windchill, and minimum monthly temperature), or the EWEMBI dataset (for incoming shortwave energy). Here we provide datasets for; surface air temperature, precipitation, incoming shortwave energy, wind-chill, snow depth (as snow water equivalent), number of rainy days per month, minimum monthly temperature, and the land-sea mask and ice fractions used in the simulations. The datasets are in the form of NetCDF files. The variables are represented by a set of 24 files that have been compressed into nine folders: temp, precip, down_sw, wind_chill, snow, rainy_days, tempmonmin, landmask and icefrac. Each file represents 2500 years. The landmask and ice fraction are provided annually, whereas the climate variables are given as monthly files equivalent to 30000 months, between the latitudes 0deg to 90degN at 0.5deg resolution. Each of the climate files therefore have the dimensions 180 (lat) x 720 (lon) x 30000 (month). We also provide an example subset of the temperature dataset, which gives decadal averages for each month for 0-2500 years.

Citable as:  Armstrong, E.; Hopcroft, P.; Valdes, P. (2019): A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years. Centre for Environmental Data Analysis, 25 October 2019. doi:10.5285/de6591c3d5d44b08b4d954410f353c6e. https://dx.doi.org/10.5285/de6591c3d5d44b08b4d954410f353c6e

Abbreviation: Not defined
Keywords: Climate, Model, HadCM3B, air temperature, precipitation

Details

Previous Info:

2025-12-09 This dataset is temporarily unavailable for download from the CEDA archive. We are working on restoring access. Please see our … Show More 2025-12-09 This dataset is temporarily unavailable for download from the CEDA archive. We are working on restoring access. Please see our latest news items for updates. - if you require access to this data in the meantime then please contact the CEDA helpdesk. Show Less

Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s):
http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

The dataset has been produced using the HadCM3B coupled climate model, a version of the more commonly known HadCM3 that has been developed at the University of Bristol, and is outlined in detail in the study of Valdes et al., (2017). The original HadCM3 originated from the UK Met Office Hadley Centre. Data provided to Centre for Environmental Data Analysis (CEDA) for archiving. Files with extra metadata to make them compliant with the CF conventions and using compressed to make them more manageable overwrote the originals in June 2019. Additional variable added Sep 2019.

Data Quality:
Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)
File Format:
NetCDF

Citations: 22

The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.

Armstrong, E., Hopcroft, P.O. & Valdes, P.J. (2020) Author Correction: A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years. Scientific Data 7. https://doi.org/10.1038/s41597-020-0432-8 https://doi.org/10.1038/s41597-020-0432-8
Armstrong, E., Hopcroft, P. & Valdes, P. (2020) A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years (version 2). https://doi.org/10.5285/4CA242208E904EFE830AF45F1697F730 https://doi.org/10.5285/4ca242208e904efe830af45f1697f730
Armstrong, E., Izumi, K. & Valdes, P. (2021) Identifying the Mechanisms of DO-scale Oscillations in a Gcm: a Salt Oscillator Triggered by the Laurentide Ice Sheet. https://doi.org/10.21203/rs.3.rs-715149/v1 https://doi.org/10.21203/rs.3.rs-715149/v1
Armstrong, E., Tallavaara, M., Hopcroft, P.O. & Valdes, P.J. (2023) North African humid periods over the past 800,000 years. Nature Communications 14. https://doi.org/10.1038/s41467-023-41219-4 https://doi.org/10.1038/s41467-023-41219-4
Beyer, R., Krapp, M. & Manica, A. (2019) A systematic comparison of bias correction methods for paleoclimate simulations. https://doi.org/10.5194/cp-2019-11 https://doi.org/10.5194/cp-2019-11
Beyer, R.M., Krapp, M., Eriksson, A. & Manica, A. (2021) Climatic windows for human migration out of Africa in the past 300,000 years. Nature Communications 12. https://doi.org/10.1038/s41467-021-24779-1 https://doi.org/10.1038/s41467-021-24779-1
error occurred https://doi.org/10.1038/s43247-024-01380-0
error occurred https://doi.org/10.1038/s41559-022-01861-5
error occurred https://doi.org/10.3989/tp.2022.12298
error occurred https://doi.org/10.1007/s10816-023-09628-3
error occurred https://doi.org/10.1029/2021gl094194
error occurred https://doi.org/10.32942/osf.io/wknjq
error occurred https://doi.org/10.5194/egusphere-egu23-5479
error occurred https://doi.org/10.1038/s41598-023-30059-3
error occurred https://doi.org/10.5194/cp-16-1493-2020
Kondor, D., Bennett, J.S., Gronenborn, D., Antunes, N., Hoyer, D. & Turchin, P. (2023) Explaining population booms and busts in Mid-Holocene Europe. Scientific Reports 13. https://doi.org/10.1038/s41598-023-35920-z https://doi.org/10.1038/s41598-023-35920-z
Krapp, M., Beyer, R., Edmundson, S., Valdes, P. & Manica, A. (2019) A statistics-based reconstruction of high-resolution global terrestrial climate for the last 800,000 years. https://doi.org/10.31223/osf.io/d5hfx https://doi.org/10.31223/osf.io/d5hfx
Leonardi, M., Hallett, E.Y., Beyer, R., Krapp, M. & Manica, A. (2022) pastclim: an R package to easily access and use paleoclimatic reconstructions. https://doi.org/10.1101/2022.05.18.492456 https://doi.org/10.1101/2022.05.18.492456
Li, X., Hu, Y., Guo, J., et al. (2022) A high-resolution climate simulation dataset for the past 540 million years. Scientific Data 9. https://doi.org/10.1038/s41597-022-01490-4 https://doi.org/10.1038/s41597-022-01490-4
Muschitiello, F. & Aquino-Lopez, M.A. (2023) Continuous synchronization of the Greenland ice-core and U-Th timescales using probabilistic inversion. https://doi.org/10.5194/cp-2023-65 https://doi.org/10.5194/cp-2023-65
Peng, F., Zhou, H., Chen, G., Li, Q., Wu, Y. & Liang, H. (2020) New Insights in Regional Climate Change: Coupled Land Albedo Change Estimation in Greenland from 1981 to 2017. Remote Sensing 12, 756. https://doi.org/10.3390/rs12050756 https://doi.org/10.3390/rs12050756
Zani, D., Lehsten, V. & Lischke, H. (2022) Tree migration in the dynamic, global vegetation model LPJ-GM 1.0: Efficient uncertainty assessment and improved dispersal kernels. https://doi.org/10.5194/gmd-2021-422 https://doi.org/10.5194/gmd-2021-422

Process overview

This dataset was generated by the computation detailed below.
Title

HadCM3B coupled climate model

Abstract

The Hadley Centre Climate Model 3 Bristol (HadCM3B) is a coupled climate model consisting of a 3D dynamical atmosphere26 and ocean27 component. HadCM3B is a version of the more commonly known HadCM3 that has been developed at the University of Bristol

Input Description

None

Output Description

None

Software Reference

None

  • units: %
  • long_name: Fraction of Grid Cell Covered with Glacier
  • standard_name: land_ice_area_fraction
  • var_id: sftgif
  • units: Wm-2
  • standard_name: surface_downwelling_shortwave_flux
  • var_id: surface_downwelling_shortwave_flux
  • long_name: Incoming_SW
  • units: %
  • long_name: Land Area Fraction
  • standard_name: land_area_fraction
  • var_id: sftlf
  • units: degC
  • var_id: tempmonmin_abs
  • long_name: Min month temp (degC)
  • standard_name: air_temperature
  • var_id: tas
  • units: degC
  • long_name: Near-Surface Air Temperature
  • var_id: pr
  • standard_name: precipitation_flux
  • long_name: Precipitation
  • units: mm day-1
  • units: m
  • standard_name: lwe_thickness_of_surface_snow_amount
  • var_id: lwe_thickness_of_surface_snow_amount
  • long_name: Snow water equivalent
  • var_id: tas
  • units: Degrees C
  • long_name: Temperature at 1.5M
  • units: degC
  • var_id: wchill
  • long_name: Wind_chill
  • units: degrees_north
  • var_id: lat
  • units: degrees_east
  • var_id: lon
  • var_id: month
  • var_id: number_rainy_days
  • long_name: number_rainy_days
  • units: 0-30
  • var_id: time

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: latitude
  • long_name: latitude
  • units: degrees_east
  • standard_name: longitude
  • var_id: longitude
  • long_name: longitude
Coverage
Temporal Range
Start time:
-
End time:
-
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
0.0000°