EnsoFbSstThf
SST-NHF_feedback: coupling between SST anomalies and NHF anomalies in the eastern equatorial Pacific
Computes net surface heat flux anomalies (NHFA; sum of latent and sensible heat fluxes and longwave and shortwave radiations) regressed onto surface temperature anomalies (SSTA) both in the eastern equatorial Pacific (horizontal Niño3 average).
TropFlux 1979-2018 (main)
NHF: OAFlux-ISCCP 1984-2009, DEEP-C 1985-2016, ERA5 1940-2022, 20CRv3 1836-2015, NCEP2 1979-2023
SST: ERSSTv5 1854-2023, HadISST 1870-2023, COBE2 1850-2023, ERA5 1940-2022, 20CRv3 1836-2015, NCEP2 1979-2023
Niño3, Niño4
None
- seasonal cycle removed
- detrending (if applicable)
- spatial average
- seasonal cycle removed
- detrending (if applicable)
- spatial average
- NHFA regressed onto SSTA (slope)
- abs((model-ref)/ref)*100
monthly
% of error
- sea surface temperature (SST)
- net surface heat flux (NHF; sum of latent and sensible heat fluxes and longwave and shortwave radiations)
The first level shows the diagnostic used to compute the metric and highlight the difference between the model and the reference.
Figure 1: scatterplot of sea surface temperature anomalies (SSTA) and net surface heat flux anomalies (NHFA) in the eastern equatorial Pacific (Niño3 averaged), showing the strength of the SST-to-NHF coupling (usually too weak by half; here slightly too strong). The black and blue markers show respectively the reference and the model. The metric is based on the slope of the regression and is the absolute value of the relative difference: abs((model-ref)/ref)*100.
The second level tests the hypothesis of a nonlinear relationship between SSTA<0 and SSTA>0.
Figure 2: scatterplot of sea surface temperature anomalies (SSTA) and net surface heat flux anomalies (NHFA) in the eastern equatorial Pacific (Niño3 averaged), showing the possible nonlinearity in the strength of the SST-to-NHF coupling (usually shows a gentler slope for SSTA<0 and steeper slope for SSTA>0 in both reference and model). The black, red and blue lines and numbers show respectively linear regression computed for all SSTA, SSTA>0 and SSTA<0, the left and right scatterplots show respectively the reference and the model.
The third level shows the local coupling in the equatorial Pacific.
Figure 3: spatial structure of net surface heat flux anomalies (NHFA) regressed onto sea surface temperature anomalies (SSTA) both in the equatorial Pacific (meridional 5°S-5°N average; zonal 30° running average), showing the possible nonlinearity in the strength of the SST-to-NHF coupling (the reference shows the maximum coupling around the dateline, west of the dateline for SSTA<0, east of the dateline for SSTA>0, but the amplitude of the maximum coupling is about the same; usually the models simulate a weaker coupling, the maximum coupling is shifted westward and the models reproduce the displacement of the maximum coupling for all SSTA, SSTA<0, SSTA>0; here the model also simulates a too strong coupling in the far east). The black, red and blue lines and numbers show respectively linear regression computed for all SSTA, SSTA>0 and SSTA<0, the dashed and solid curves show respectively the reference and the model.
The fourth level shows the spatio-mean annual structure of the coupling.
Figure 4: spatio-mean annual structure of net surface heat flux anomalies (NHFA) regressed onto sea surface temperature anomalies (SSTA) both in the equatorial Pacific (meridional 5°S-5°N average; zonal 30° running average), showing the possible nonlinearity in the strength of the SST-to-NHF coupling. The reference shows a strong seasonality with a strong coupling during the first half of the year and a weak one during the second half, in addition, the coupling is strong during the first half of the year when SSTA>0 and quite weak when SSTA<0 (but in the far west), indicating that this SSTA damping by heat fluxes is mainly active to terminate El Niño events. Usually models reproduces these aspects but the coupling is weaker and the coupling's seasonality is also weaker. The first, second and third rows show respectively linear regression computed for all SSTA, SSTA>0 and SSTA<0, the left and right Hovmöllers show respectively the reference and the model.