DOI: 10.26180/26525212
title: Data for Modulation in Teleconnections of the El Nino Southern Oscillation by Atlantic Multidecadal Sea Surface Temperature Variability

description: Here we store the idealised AGCM experiment output used to explore impacts of observed decadal Atlantic sea surface temperature (SST) changes on El Nino Southern Oscillation teleconnections. This manuscript titled "Modulation in Teleconnections of the El Nino Southern Oscillation by Atlantic Multidecadal Sea Surface Temperature Variability", which describes these simulations and their output, is submitted for publication in Geophysical Research Letters, where the lead author is Dylan Wreford and is co-authored by Shayne McGregor and Rajeshree Naha.Manuscript Key Points:· Atlantic Multidecadal Variability SSTA can produce statistically significant changes of ENSO teleconnections without any changes in ENSO.· ENSO teleconnection modulation by the AMV was regionally specific with variation in statistical strength and sign relative to the control.· Teleconnection modulation is likely a result of tropical Pacific precipitation changes during ENSO induced atmospheric stability changes.========================================================================Data details:ncdump -h<b> Expmt_Data.nc</b>netcdf Expmt_Data {dimensions:lon = 192 ; lat = 145 ; ens = 10 ; T = 288 ; P = 288 ;Here P refers to precipitation, while T is surface temperature. There are 10 ensemble members and the data os each simulation covers 288 months. The AOa in the variable name refers the Atlantic Anomalies that were utilise, while whether they are added or subtracted is indicated by a p (plus) or m (minus), and if there is an additional p5, this identifies that the experiment data includes the pattern at half magnitude. So P_pp5AOa.nc is the precipitation output from the experiment with idealised Atlantic SSTA pattern added at half strength to the Atlantic.variables:double lon(lon) ; double lat(lat) ;double controlT(lat, lon, T, ens) ; controlT:units = "K" ;double T_mAOa(lat, lon, T, ens) ; T_mAOa:units = "K" ;double T_mp5AOa(lat, lon, T, ens) ; T_mp5AOa:units = "K" ;double T_pAOa(lat, lon, T, ens) ; T_pAOa:units = "K" ;double T_pp5AOa(lat, lon, T, ens) ; T_pp5AOa:units = "K" ;double controlP(lat, lon, P, ens) ; controlP:units = "mm/day" ;double P_mAOa(lat, lon, P, ens) ; P_mAOa:units = "mm/day" ;double P_mp5AOa(lat, lon, P, ens) ; P_mp5AOa:units = "mm/day" ;double P_pAOa(lat, lon, P, ens) ; P_pAOa:units = "mm/day" ;--------------------------------------------------------------------------------------------------Data detailsncdump -h <b>GEOPOT_HT_200hPa_AMV_exps_NEW.nc</b>netcdf GEOPOT_HT_200hPa_AMV_exps_NEW {dimensions:lat = 49 ; lon = 192 ; levels = 17 ; time = 288 ; ensembles = 10 ;Here zg_plevs refers to geopotential height on pressure levels, while the 200hPa to the 200hPa pressure level. There are 10 ensemble members and the data os each simulation covers 288 months. The AOa in the variable name refers the Atlantic Anomalies that were utilise, while whether they are added or subtracted is indicated by a p (plus) or m (minus), and if there is an additional p5, this identifies that the experiment data includes the pattern at half magnitude. So zg_plevs_pp5AOa_200hPa is the experiment 200hPa geopotential height output from the experiment with idealised Atlantic SSTA pattern added at half strength to the Atlantic.variables:float lat(lat) ; lat:_FillValue = NaNf ; lat:MATLAB_class = "single" ;float lon(lon) ; lon:_FillValue = NaNf ; lon:MATLAB_class = "single" ;double pressure(levels) ; pressure:_FillValue = NaN ; pressure:MATLAB_class = "double" ;double time(time) ; time:_FillValue = NaN ; time:MATLAB_class = "double" ;double zg_plevs_ctl_200hPa(lat, lon, time, ensembles) ; zg_plevs_ctl_200hPa:_FillValue = NaN ; zg_plevs_ctl_200hPa:MATLAB_class = "double" ;double zg_plevs_mAOa_200hPa(lat, lon, time, ensembles) ; zg_plevs_mAOa_200hPa:_FillValue = NaN ; zg_plevs_mAOa_200hPa:MATLAB_class = "double" ;double zg_plevs_mp5AOa_200hPa(lat, lon, time, ensembles) ; zg_plevs_mp5AOa_200hPa:_FillValue = NaN ; zg_plevs_mp5AOa_200hPa:MATLAB_class = "double" ;double zg_plevs_pAOa_200hPa(lat, lon, time, ensembles) ; zg_plevs_pAOa_200hPa:_FillValue = NaN ;zg_plevs_pAOa_200hPa:MATLAB_class = "double" ;double zg_plevs_pp5AOa_200hPa(lat, lon, time, ensembles) ; zg_plevs_pp5AOa_200hPa:_FillValue = NaN ; zg_plevs_pp5AOa_200hPa:MATLAB_class = "double" ;=======================================