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Dataset

 

Idealised climate model simulations for the Iceland Greenland Sea's Project (IGP)

Update Frequency: Not Planned
Latest Data Update: 2022-05-26
Status: Ongoing
Online Status: ONLINE
Publication State: Published
Publication Date: 2023-08-10
Download Stats: last 12 months
Dataset Size: 456 Files | 127GB
Abstract

This dataset contains idealised climate model simulations for the Atmospheric Forcing of the Iceland Sea (AFIS) project which was the UK component, funded by NERC, of the Iceland Greenland Sea's Project (IGP). The UK Met Office Unified Model (MetUM) version 10.6 with a regional nested domain was used to carry out a suite of simulations of the atmosphere over the NE North Atlantic region. The set up of the MetUM uses the Global Atmosphere 6 and Global Land 6 (GA6/GL6) configurations including the ENDGame dynamical core.
Model simulations were run on the Met Office supercomputer accessed through Monsoon.

This dataset contains the output for one of 7 model outputs.
These are:
Temperature - 1.5m Surface Temperature output from themodel simulations.
Latent HF - Latent Heat Flux output from the model simulations.
Sensible HF - Sensible Heat Flux output from the model simulations.
Relative Humidity - Relative Humidity output from the model simulations.
Specific Humidity - Specific Humidity output from the model simulations.
Surface Winds - 10 m U and V wind component output from the model simulations.
MSLP - Mean Sea Level Pressure output from the model simulations.

A list of papers related to this dataset can be found in the linked online resources on this record.

Citable as:  Pope, J. (2023): Idealised climate model simulations for the Iceland Greenland Sea's Project (IGP). NERC EDS Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/9fb47f1d6d294b0dba553adc2253e6cf
Abbreviation: Not defined
Keywords: IGP, AFIS, MetUM

Details

Previous Info:
No news update for this record
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: 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 model simulations were run by James Pope when he was employed on the IGP project at the British Antarctic Survey. Model simulations were run on the Met Office supercomputer accessed through Monsoon. As of July 2019, James Pope is employed by the Met Office and can be contacted at james.pope@metoffice.gov.uk. These data were then supplied to CEDA for archiving.
Data Quality:
No quality information available. Data are as provided by the project team
File Format:
Data are NetCDF formatted. Files ending _daymean.nc or ydaymean.nc were processed using CDO. the CDO command that the filename ends with. IE for MSLP, the file u_au087_MSLP_9110_daymean.nc was created using cdo daymean u_au087_MSLP_9110.nc u_au087_MSLP_9110_daymean.nc The folder splitmon used the CDO command splitmon to break each file down into January, February, March and April, identified by the suffix 01, 02, 03 and 04 respectively. Daymean and ydaymean versions were created.

Related Documents

 Walters, D et al. (2017) The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci Model Dev 10:1487-1520.
 Roberts-Jones J, Fiedler EK, Martin MJ (2012) Daily, Global, High-Resolution SST and Sea Ice Reanalysis for 1985-2007 Using the OSTIA System. J Clim 25:6215-6232.
 Renfrew IA, Elvidge AD, Edwards J (2019a) Atmospheric sensitivity to marginal-ice-zone drag: local and global responses. Q J R Meteorol Soc in press.
 Lupkes C, Gryanik VM, Hartmann J, Andreas EL (2012) A parametrization, based on sea ice morphology, of the neutral atmospheric drag coefficients for weather predict ion and climate models. J Geophys Res 117:D13112.
 Elvidge AD, Renfrew IA, Weiss AI, Brooks IM, Lachlan-Cope TA, King JC (2016) Observations of surface momentum exchange over the marginal-ice-zone and recommendations for its parameterization. Atmos Chem Phys 16:1545-1563.
 Donlon CJ, Martin M, Stark J, Roberts-Jones J, Fiedler E, Wimmer W (2012) The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system. Rem Sens Env 116:140-158.
 Dee D et al. (2011) The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597.
 IGP Project overview paper

Process overview

This dataset was generated by the computation detailed below.
Title

MetUM vn.10.6 using the nested suite for IGP.
Abstract

The UK Met Office Unified Model (MetUM) version 10.6 with a regional nested domain was used to carry out a suite of simulations of the atmosphere over the NE North Atlantic region. This set up of the MetUM used the Global Atmosphere 6 and Global Land 6 (GA6/GL6) configurations including the ENDGame dynamical core (Walters et al. 2017). One modification to the standard GA6/GL6 configuration was to include form drag in surface momentum exchange over sea ice, based on Lüpkes et al. (2012) and Elvidge et al. (2016), and now part of the GL8 configuration. This new scheme has recently been implemented in the operational forecasting suite following evidence of significant improvements in simulated fluxes of momentum and heat and consequently improvements to the representation of wind speeds and temperatures over-and-downwind of the marginal-ice-zone during Arctic CAOs (Renfrew et al. 2019a). In our set up the MetUM was run globally with an N320 longitude-latitude grid (0.56° x 0.375°, equivalent to 60 km by 42 km at the equator) and 70 vertical levels up to a height of 40 km. The Iceland and Greenland Seas nested domain was 200 x 210 grid points with a spacing of 0.072° x 0.072° (equivalent to 8 km by 8 km) centred on 70.8°N, 14.0°W.

The MetUM was run in atmosphere-only mode with SST and sea-ice fields prescribed at the lower boundary for both the global and regional nested domains. The SST and sea-ice data were taken from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system (Donlon et al. 2012; Roberts-Jones et al. 2012) and re-gridded to match the respective resolutions of the global model and the nested domain. The lower boundary conditions were updated daily. Within this set up, the global model was re-initialised daily at 00 UTC by ERA-Interim reanalysis (Dee et al. 2011). After initialisation on the first day of the simulation, the nested domain was only forced at the lateral boundaries by the global model. This means the nested domain is able to spin up and maintain mesoscale structures, within a regional atmospheric circulation environment that is nudged towards reality on a daily basis. The nested domain is relatively small, so is strongly influenced by the lateral boundary conditions. All simulations were run across an extended winter period, 1st November to 30th April, for 20 seasons from winter 1990/91 to 2009/10.
Input Description

None
Output Description

None
Software Reference

None
  • var_id: air_pressure_at_sea_level
  • standard_name: air_pressure_at_sea_level
  • units: Pa
  • units: K
  • long_name: air_temperature
  • var_id: air_temperature
  • standard_name: air_temperature
  • standard_name: forecast_period
  • var_id: forecast_period
  • units: hours
  • units: hours
  • var_id: forecast_reference_time
  • standard_name: forecast_reference_time
  • units: degrees
  • var_id: grid_latitude
  • standard_name: grid_latitude
  • units: degrees
  • standard_name: grid_longitude
  • var_id: grid_longitude
  • var_id: height
  • standard_name: height
  • units: m
  • var_id: rotated_latitude_longitude
  • var_id: rotated_pole
  • long_name: specific_humidity
  • standard_name: specific_humidity
  • var_id: specific_humidity
  • units: 1
  • var_id: surface_upward_latent_heat_flux
  • long_name: surface_upward_latent_heat_flux
  • standard_name: surface_upward_latent_heat_flux
  • units: W m-2
  • var_id: unknown
  • units: m.s-1
  • long_name: unknown
  • long_name: x_wind
  • var_id: x_wind
  • standard_name: x_wind
  • units: m s-1
  • var_id: y_wind
  • standard_name: y_wind
  • units: m s-1

Co-ordinate Variables

  • units: hours
  • var_id: time
  • standard_name: time
Coverage
Temporal Range
Start time:
2018-02-28T00:00:00
End time:
2018-03-19T23:59:59
Geographic Extent

 
78.0000°
  
-21.2000°
  
-6.8000°
 
63.0000°
  
Related parties
Authors (1)
Publishers (1)
Funders (1)
Principal Investigators (1)