Data from: The Relationship between the Southern Ocean and the Eastern tropical Pacific in unforced and forced climate model simulations

Zheng, Yiyu1 ; Rugenstein, Maria1 ; Alessi, Marc1

Published Jul 15, 2024; Updated Oct 28, 2024 on Dryad. https://doi.org/10.5061/dryad.r4xgxd2nw

Data files

Jul 15, 2024 version files 3.09 GB

README.md

2.97 KB
Zheng_202406.zip

3.09 GB

Oct 28, 2024 version files 8.73 GB

Abstract

The sea surface temperature (SST) over the eastern tropical Pacific significantly influences global-mean climate feedback and may be driven in part by the SST over the Southern Ocean. Previous studies demonstrated a teleconnection from the Southern Ocean to the eastern tropical Pacific by perturbing the Southern Ocean climate. We investigate if this teleconnection holds in a fully coupled, freely running climate system using CMIP6 models. We assess the relationship between the Southern Ocean (SO) and the eastern tropical Pacific (SEP) by calculating correlations between SO and SEP SST timeseries within each model and regressions between mean SO and SEP SSTs across models. We show robust, positive SO-SEP relationships in an unforced climate using pre-industrial SSTs, in a forced climate using SST anomalies between pre-industrial and quadrupled CO₂ simulations, and in the SST pattern of the forced response relative to the global-mean SST anomaly. The strength of SO-SEP correlations is positively related to the stratocumulus cloud feedback off the west coast of South America, and negatively related to ocean heat uptake in the same region. As both shortwave cloud feedback and ocean heat uptake are underestimated in climate models, understanding their effects on SO-SEP teleconnections and their interactions is crucial for determining the strength of SO-SEP teleconnection in the real world and its trustworthiness in climate model projection.

README: Data from: The Relationship between the Southern Ocean and the eastern tropical Pacific in unforced and forced climate model simulations

https://doi.org/10.5061/dryad.r4xgxd2nw

This dataset contains multi-model simulations (in total, 53 models are used) from CMIP6 archive that serve our analyses of finding the connections between the Southern Ocean and the eastern tropical Pacific. The original CMIP6 model outputs are downloaded from https://aims2.llnl.gov/search, which then went through processes that convert the monthly data to annual data and re-grid different spatial resolutions of different models to a 2.5° x 2.5° resolution. This dataset generally contains five variables (sea surface temperature, wind, wind-evaporation-SST feedback, shortwave cloud feedback, and ocean heat uptake) under three conditions (unforced pre-industrial condition, forced condition, and the pattern of the forced condition). File information in the following content is ordered in accordance with the figures in the associated article. The specific model names are hidden for concision.

Format of data file:

.nc and .txt

File Information:

grid.nc:

Grid cell area with the same spatial resolution as all other NetCDF files. This file is used for calculating the area-weighted average.

tos_piControl/tos_regrid_ann_*_piControl.nc:

Three-dimensional (time x latitude x longitude) sea surface temperature (SST) in unforced pre-industrial simulations, behind Fig.1.

tos_anomaly/tos_regrid_ann_*_anomaly.nc:

Three-dimensional SST anomaly, behind Fig.2.

tos_pattern/division/tos_regrid_ann_*_pattern.nc:

Three-dimensional SST pattern, behind Fig.3 and Fig.4.

tos_pattern/subtraction/tos_regrid_ann_*_pattern_s.nc

tos_pattern/regression/tos_regrid_ann_*_pattern_r.nc

tos_pattern/PCA/tos_regrid_ann_*_pattern_PCA.nc

Three-dimensional SST pattern calculated by three other methods in the same models, behind Fig.5.

"pattern_s" represents SST pattern calculated by subtraction; "pattern_r" represents SST pattern calculated by regression; "pattern_PCA" represents SST pattern calculated by PCA.

Wind/uas_regrid_ann_*_piControl.nc

Wind/vas_regrid_ann_*_piControl.nc

Wind/wind_regrid_ann_*_piControl.nc

Wind/uas_regrid_ann_*_anomaly.nc

Wind/vas_regrid_ann_*_anomaly.nc

Wind/wind_regrid_ann_*_anomaly.nc

WES/WES_*_piControl.nc

WES/WES_*_pattern.nc

cloudFeedback/RS_regrid_ann_*_piControl.nc

cloudFeedback/CF_regrid_ann_*_anomaly.nc

OHU/OHU_regrid_ann_*_piControl.nc

OHU/dOHU_regrid_ann_*_anomaly.nc

Three-dimensional surface zonal wind (uas), surface meridional wind (vas), and surface total wind (wind) in pre-industrial simulations and their anomalies, two-dimensional WES feedback-related variables in pre-industrial control simulations and using anomalies, two-dimensional radiative restoration strength in pre-industrial simulations (RS), two-dimensional shortwave cloud feedback using anomalies (CF), three-dimensional ocean heat uptake in pre-industrial simulations (OHU), and three-dimensional changes in ocean heat uptake between unforced and forced simulations (dOHU) behind Fig.6.
The two-dimensional WES feedback-related netCDF files contain five physical variables, of which the calculations are shown in Method section and are repeated here:

In piControl files:

WES_LH: regressing the surface upward latent heat flux (LH) from pre-industrial simulations onto normalized SST averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W) from pre-industrial simulations.
WES_SST: regressing the SSTs from pre-industrial simulations onto normalized SST averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W) from pre-industrial simulations.
WES_SLP: regressing the sea-level air pressure (SLP) from pre-industrial simulations onto normalized SST averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W) from pre-industrial simulations.
WES_U (V): regressing the zonal (meridional) winds from pre-industrial simulations onto normalized SST averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W) from pre-industrial simulations.

In pattern files:

WES_LH: regressing the anomalous LH onto normalized SST pattern averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W).
WES_SST: regressing the anomalous SSTs onto normalized SST pattern averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W).
WES_SLP: regressing the anomalous SLP onto normalized SST pattern averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W).
WES_U (V): regressing the anomalous zonal (meridional) winds onto normalized SST pattern averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W).

Wind_wSA.txt

dWind_wSA.txt

WESp.txt

dWESp.txt

RS_wSA.txt

CF_wSA.txt

OHU_wSA.txt

dOHU_wSA.txt

Wind advection in pre-industrial simulations and anomalies averaged over a box off the west coast of South America (42S-10S, 85W-70W). WES parameter in pre-industrial simulations and its change between pre-industrial and abrupt4xCO2 simulations averaged over a triangular region near the central South Pacific ((10S,180), (10S,100W), (30S,100W)). Radiative restoration strength and shortwave cloud feedback averaged over a box off the west coast of South America (35S-10S, 100W-71W), and ocean heat uptake and its changes averaged over a box off the west coast of South America (40S-15S, 82W-70W), behind Fig.7.

Version changes

10/24/2024: added variables related to wind and WES feedback, including a folder named "Wind" that contains three-dimensional surface zonal, meridional, and total wind advection for each climate model, and a folder named "WES" that contains two-dimensional WES-related variables. In addition, area-weighted average of wind and WES feedback in pre-industrial control simulations and using anomalies are included in files "Wind_wSA.txt", "dWind_wSA.txt", "WESp.txt", and "dWESp.txt".

Methods

The original data for SST and for calculating the radiative restoration strength, shortwave cloud feedback, and ocean heat uptake are downloaded from https://aims2.llnl.gov/search.

The original monthly data has been converted to annual data and re-grided to 2.5^o x 2.5^o spatial resolution.

SST anomalies are calculated for each grid by subtracting the linear regression fit of timeseries of piControl simulations from abrupt-4xCO2 simulations.

The main SST pattern used in the study is calculated by dividing SST anomalies at each grid point by the global-mean SST anomalies at each timestep. Other SST patterns are calculated by subtracting local SST anomalies at each grid point from the global-mean SST anomalies at each timestep, by regressing local SST anomalies at each grid point onto the global-mean SST anomalies across the entire timeseries (150 years), and by applying principal component analysis (PCA) to the three-dimensional SST anomalies.

The climatological total wind advection is calculated using climatological zonal and meridional winds by √(U² + V²) in pre-industrial control simulations across the entire timeseries (150 years).

The anomalous total wind advection is calculated by subtracting the climatological total winds from the forced total winds that calculated in abrupt4xCO2 simulations across the entire timeseries.

The wind-evaporation-SST (WES) feedback is calculated using the surface upward latent heat flux (LH), the wind advection, SSTs, and sea-level air pressure. Regressing surface upward latent heat flux, SSTs, sea-level air pressure, zonal (u) and meridional winds onto normalized SST averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W) in pre-industrial simulations provides a spatial pattern of WES feedback mechanism in an unforced climate.

The WES feedback on SST pattern is calculated by regressing anomalous surface upward latent heat flux, SSTs, sea-level air pressure, zonal and meridional winds onto normalized SST patterns averaged over a small region in the southeast Pacific (19°S–15°S, 103°W–107°W).

The WES parameter (WESp) in pre-industrial control simulation is calculated based on WESp = LH · u / wind_bar². wind_bar accounts for submonthly wind variance and is calculated by √(U² + V² + w_hat²), where w_hat is set to 4m/s.

The changes in WESp is calculated by subtracting WESp in pre-industrial control simulation from WESp in abrupt4xCO2 simulations.

Radiative restoration strength is calculated by regressing the local shortwave cloud radiative effect onto local SST in pre-industrial control simulations across the entire timeseries (150 years). The shortwave cloud radiative effect is the difference between the outgoing shortwave flux at the top-of-atmosphere and the outgoing shortwave flux at top-of-atmosphere when there are no clouds (clear sky).

Shortwave cloud feedback is calculated by regressing anomalies of the local shortwave cloud radiative effect onto local SST anomalies across the entire timeseries (150 years). The anomalies of the shortwave cloud radiative effect are calculated by subtracting the linear regression fit of timeseries of piControl simulations from abrupt-4xCO2 simulations.

Ocean heat uptake is represented by the net surface downward heat flux, which is the difference between surface downward longwave flux, surface upward longwave flux, surface downward shortwave flux, surface upward shortwave flux, surface upward sensible heat flux, and surface upward latent heat flux.

Changes in ocean heat uptake are calculated by subtracting the linear regression fit of timeseries of piControl simulations from abrupt-4xCO2 simulations.