Wind Stress Curl and ENSO Discharge/Recharge in the Equatorial Pacific

Abstract

Discharge and recharge of the warm water volume (WWV) above the 20°C isotherm in an equatorial Pacific Ocean box extending across the Pacific from 156°E to the eastern ocean boundary between latitudes 5°S and 5°N are key variables in ENSO dynamics. A formula linking WWV anomalies, zonally integrated wind stress curl anomalies along the northern and southern edges of the box, and flow into the western end of the box is derived and tested using monthly data since 1993. Consistent with previous work, a WWV balance can only be achieved if the 20°C isotherm surface is not a material surface; that is, warm water can pass through it. For example, during El Niño, part of the WWV anomaly entering the box is cooled so that it is less than 20°C and therefore passes out of the bottom of the box, the 20°C isotherm surface. The observations suggest that the anomalous volume passing through the 20°C isotherm is approximately the same as TЈ W , the anomalous WWV entering the western end of the box. Therefore the observed WWV anomaly can be regarded as being driven by the anomalous wind stress curl along the northern and southern edges of the box. The curl anomaly changes the WWV both by divergent meridional flow at the edges of the box and vortex stretching; that is, the Sverdrup balance does not hold in the upper ocean. A typical amplitude for the rate of change of WWV for the 5°S-5°N box is 9.6 Sv (Sv ϵ 10 6 m 3 s Ϫ1 ). The wind stress curl anomaly and the transport anomaly into the western end of the box are highly correlated with the El Niño index Niño-3.4 [the average sea surface temperature anomaly (SSTA) over the region 5°S-5°N, 170°-120°W] and Niño-3.4 leads minus the WWV anomaly by one-quarter of a cycle. Based on the preceding results, a simple discharge/recharge coupled ENSO model is derived. Only water warmer than about 27.5°-28°C can give rise to deep atmospheric convection, so, unlike past discharge/recharge oscillator models, the west-central rather than eastern equatorial SSTAs are emphasized. The model consists of two variables: TЈ, the SSTA averaged over the region of strong ENSO air-sea interaction in the west-central Pacific equatorial strip 5°S-5°N, 156°E-140°W and DЈ, the 20°C isotherm depth anomaly averaged over the same region. As in the observations, TЈ lags DЈ by one-quarter of a cycle; that is, ‫ץ‬TЈ/‫ץ‬t ϭ DЈ for some positive constant . Physically, when DЈ Ͼ 0, the thermocline is deeper and warmer water is entrained through the base of the mixed layer, the anomalous heat flux causing ‫ץ‬TЈ/‫ץ‬t Ͼ 0. Also, when DЈ Ͼ 0, the eastward current anomaly is greater than zero and warm water is advected into the region, again causing ‫ץ‬TЈ/‫ץ‬t Ͼ 0. Opposite effects occur for DЈ Ͻ 0. A second relationship between TЈ and DЈ results because the water is warm enough that TЈ causes deep atmospheric convection anomalies that drive the wind stress curl anomalies that change the heat storage ‫ץ‬DЈ/‫ץ‬t. The atmosphere responds essentially instantly to the TЈ forcing and the curl causes a discharge of WWV during El Ni...

ENSO-driven energy budget perturbations in observations and CMIP models

“…3f) may be related to the generally too narrow band of ENSO-related wind stress anomalies along the equator in the coupled climate models (Capotondi et al 2006). Along the equator, DIVFO variability is mainly associated with Sverdrup transports resulting from equatorial wind stress curl anomalies (Jin 1997;Clarke et al 2007) and compensating DIVFO anomalies of opposite sign occur in the subtropics. Indeed, all considered datasets (reanalyses and models) have a positive response of equatorial (5N-5S) DIVFO to ENSO with all models exhibiting a weaker response than reanalyses (not shown).…”

Forecasts of Tropical Pacific Sea Surface Temperatures by Neural Networks and Support Vector Regression

“…Inclusion of the WWV index in the forecast of PC1 generally increased the correlation scores for all three models, while at the same time reducing or eliminating the differences between them. This increase in the correlation scores is expected given that the WWV along with SST is the main variables in most theoretical discharge/recharge oscillator models [14,18,19].…”

“…Incidentally, correlation skills for the Niño 4 region show the largest observed discrepancies among the different models, with BNN winning at longer lead times (12-15 months) and SVR at shorter lead times (3 and 6 months). Incorporating the WWV tended to reduce the differences in correlation among the 3 methods due to the mainly linear coupling between WWV and SST [18]. The advantage of the nonlinear methods is the most apparent in the region of largest variability, Niño 1 + 2, over short lead times of 3-9 months.…”

Assessing the Twenty-First-Century Shift in ENSO Variability in Terms of the Bjerknes Stability Index*

“…2c). On the equator, wind stress forcing balances the zonal pressure gradient vertically integrated from the depth of the thermocline to the surface [see Clark et al 2007, their Eq. (1.4)] and the thermocline slope response is proportional to the zonal integral of the wind to the west of an observation point (Kessler and McPhaden 1995).…”