This README.txt file was generated on 20171220 by Lauren J Gregoire





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GENERAL INFORMATION

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1. Title of Dataset 



Climate model data presented in “Holocene lowering of the Laurentide ice sheet affects North Atlantic gyre circulation and climate”





2. Author Information





  Principal Investigator Contact Information

        Name: Lauren J Gregoire

           Institution: University of Leeds

           Email: l.j.gregoire@leeds.ac.uk





   Co-investigator Contact Information

        Name: Ruza F. Ivanovic	

           Institution: University of Leeds

           Email: r.ivanovic@leeds.ac.uk





3. How to cite this dataset ? / Associated publication



Please cite the publication in which this data was presented:



Gregoire LJ; Ivanovic RF; Maycock AC; Valdes PJ; Stevenson S (2018) Holocene lowering of the Laurentide ice sheet affects North Atlantic gyre circulation and climate, Climate Dynamics. doi: 10.1007/s00382-018-4111-9.







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DATA & FILE OVERVIEW

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1. List of simulations



This dataset contains 4 climate simulations with input boundary conditions (e.g. greenhouse gases, orbit, geography) set to 9.0 thousands of years BP (ka), but where the Laurentide (North American) ice sheet extent and topography has been set to a snapshot of ice sheet model output. There is a control simulation for comparison corresponding to the climate at 0.0 ka. See the associated publication for full details of experimental design. 



The simulations are labeled as follows: 

- 0.0 ka : tdqqa

- 9.5 ka : tdqqc

- 9.0 ka : tdqqd

- 8.5 ka : tdqqe

- 8.0 ka : tdqqf 











2. File structure

There is one zip file per experiment, which contains the following structure of subdirectories: 



 {expt}.zip

  |-input

  |-ocean

  |-atmosphere



 where: {expt} is tdqq[acdef]











3. Input (boundary condition) files



In directories {expt}/input/



{expt}.qrfrac.type.PMIP.nc



  contains the ice sheet mask: Variable 'field1391' at 'pseudo' level 1 (1st level).  

	

{expt}.qrparm.mask



  contains the land-sea mask: Variable 'lsm'.



{expt}.qrparm.orog



  contains the surface orography: Variable 'ht'.











4. Output atmospheric files 



 In directories {expt}/atmosphere 

 The files have the following naming convention:  

  {expt}a.pdcl{mth}.nc 



 with: 

  {expt} is tdqq[acdef]

  {mth} is a 3 letter id for the month, seasonal or annual (e.g. jan-dec, djf, mam, jja, son, ann)



 There are 4 types of atmospheric files : 

  {expt}a.pdcl{mth}.nc : Climatological means of the atmospheric surface 2D fields

  {expt}a.pdsd{mth}.nc : Climatological standard deviations of the atmospheric surface 2D fields 

  {expt}a.pccl{mth}.nc : Climatological means of the atmospheric 3D fields

  {expt}a.pcsd{mth}.nc : Climatological standard deviations of the atmospheric 3D fields 





4.1 Main variables in the atmospheric 2D (a.pd) files

 The main variables of interest are as follows:



 For experiment tdqqa, tdqqc

  - Surface air temperature at 1.5 m : temp 

  - surface winds at 10 m: u, v

  - surface Wind stress curl : taux, tauy

  - surface pressure: p

  - evaporation :  evap

  - precipitation : precip

  - fractional sea-ice cover: iceconc



 For experiment tdqq[def]

  - Surface air temperature at 1.5 m : temp_mm_1_5m 

  - surface winds at 10 m : u_mm_10m, v_mm_10m

  - surface Wind stress curl : taux, tauy

  - surface pressure: p_mm_srf

  - evaporation :  evap_mm_srf

  - precipitation : precip_mm_srf

  - fractional sea-ice cover: iceconc_mm_srf



 The files also contain other variables relating to humidity, water fluxes and energy balance.





4.2 Main variables in the atmospheric 3D (a.pc) files

 The variables are on pressure levels p (17 levels). 

 The main variables of interest are as follows:



 For experiment tdqqa, tdqqc

  - temperature : temp

  - winds : u, v

  - geopotential height : ht

  - relative humidity : rh





 For experiment tdqq[def]

  - temperature : temp_mm_p

  - winds : u_mm_p, v_mm_p

  - geopotential height : ht_mm_srf

  - relative humidity : rh_mm_p

  - specific humidity : q_mm_p











5. Output ocean files



In directories {expt}/ocean



There are 4 types of ocean files : 

  {expt}o.pfcl{mth}.nc : Climatological means of the ocean surface fields

  {expt}o.pfsd{mth}.nc : Climatological standard deviations of the ocean surface fields

  {expt}o.pgclann.nc : Climatological annual means of the ocean 3D fields

  {expt}o.pgsdann.nc : Climatological annual standard deviations of the ocean 3D fields 



5.1 Main variables in the surface ocean (o.pf) files

 The main variables of interest are as follows:



 For experiment tdqqa, tdqqc

  - temperature : temp

  - potential temperature : temp_1

  - salinity : salinity

  - velocity : field703, field704 

  - mixed layer depth : field653

  - ocean barotropic streamfunction : field611



 For experiment tdqq[def]

  - temperature : temp_mm_uo 

  - potential temperature : temp_mm_dpth  

  - salinity : salinity_mm_dpth

  - velocity : ucurrTot_mm_dpth, vcurrTot_mm_dpth, WcurrTot_mm_dpth

  - mixed layer depth : mixLyrDpth_mm_uo

  - ocean barotropic streamfunction : streamFn_mm_uo





5.2 Main variables in the 3D ocean (o.pg) annual files

 The main variables of interest are as follows:



 For experiment tdqqa, tdqqc

  - potential temperature : temp

  - in situ temperature : insitu_T

  - salinity : salinity

  - velocity : field703, field704 



 For experiment tdqq[def]

  - potential temperature : temp_ym_dpth  

  - in situ temperature : insitu_T_ym_dpth

  - salinity : salinity_ym_dpth

  - velocity : ucurrTot_ym_dpth, vcurrTot_ym_dpth, WcurrTot_ym_dpth











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METHODOLOGICAL INFORMATION

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1. Description of the model used to generate the data: 



The data was generated using the Met Office Hadley Centre Coupled Model version 3 (HadCM3) ocean-atmosphere-vegetation general circulation model. The atmosphere has a regular latitude-longitude grid of 2.5° × 3.75° resolution and 19 hybrid sigma-pressure coordinate layers, from the surface up to ~10 hPa. The ocean has a horizontal resolution of 1.25° × 1.25° with 20 vertical layers. See the reference publication (described above) for more details. 







2. Methods for processing the data: 



Raw monthly mean model output from the the last 100 years of the model simulations was used to calculate monthly, seasonal and annual climatological mean and standard deviations using nco netcdf operators. 







3. software-specific information needed to interpret the data:



The data is provided in Netcdf-3 classic format. This format can be read and plotted to produce maps and other types of plots using software such as Panoply, Ferret, NCL, python, Matlab, IDL...