3.1 Mean Ocean state during different types of El Niño
A warming event in the Pacific Ocean is termed as El Niño only when 3-month running means of the area-averaged SST anomaly over the Niño 3.4 region (170° W–120° W, 5° S–5° N) crosses a threshold of 0.5°C for at least five consecutive seasons. Climate Prediction Center (CPC-NOAA) uses the same definition for its operational forecasts. An El Niño can further be categorized into canonical ENSO and protracted ENSO based on the persistence of area-averaged SST anomaly over the Niño 3.4 region. If a positive SST anomaly during an El Niño event lasts for more (less) than 3 consecutive years, the event is termed as protracted (canonical) El Niño (Allan and D’Arrigo 1999b, a). Figure 1 shows the time series of the seasonal mean (3-month running mean) of SST anomaly averaged over Niño 3.4 region for the period 1948–2009. Identification of El Niño events is done following the standard definition of Climate Prediction Center (CPC-NOAA). Different ocean states are chosen based on temporal temperature evolution in the eastern PO. Observed SST anomaly averaged over Niño 3.4 region shows the transition of strong ENSO in the year 1982-83 into a La Nina in the following year 1983-84, 1984-85. This state is termed as canonical ENSO (1980-84; CE) state in this study. SST anomaly averaged over Niño 3.4 region during 1991-92 does not show the transition of El Niño to La Nina state instead weak El Niño continues in the following year too (Allan and D’Arrigo 1999b; Arora and Kumar 2019). This state of the equatorial ocean is termed protracted ENSO state (1990-94; PE). During the period 1958-62, there does not exist either El Niño or La Nina in the eastern Pacific. This state is termed as Normal Ocean state (1958-62; NS). Ocean state before the start of NS (December 1957), CE (December 1979), and PE (December 1989) is termed as pre-NS, pre-CE, and pre-PE respectively.
Figure 2(a-c) shows mean SST during pre-NS, pre-CE, and pre-PE state in the model control simulation of the model respectively. The difference in the spatial structure of SST in the tropical Indo-Pacific region shows the different values of heat content before the onset of distinct types of ENSO. Each state exhibits a peculiar signature of zonal extent and position of Indo-Pacific warm pool (SST greater than 28°C; (Gadgil et al. 1984; Graham and Barnett 1987). Oceanic anomalies before the onset of El Niño over the western Pacific are related to the strengthening of the trades, and the accumulated warm water flows eastward in the form of Kelvin waves to initiate an El Niño event (Wyrtki 1975). Also, the cold tongue in the equatorial eastern Pacific is more extended towards the international dateline in the pre-PE state compared to the pre-NS and pre-CE state. Figure 2(d&e) shows the difference of mean SST of pre-CE and pre-PE state from the pre-NS state as shown in Fig. 2(a-c). Higher values of SST are seen in the Indo-Pacific warm pool during the pre-CE state before the onset of strong canonical ENSO compared to the pre-NS state. Higher values of SST during pre-CE and pre-PE state compared to pre-NS are seen over the western PO. Bay of Bengal region shows cooler SST during pre-PE state compared to pre-NS and pre-CE state. A comparison of pre-CE and pre-PE state shows the higher SST (by 2°C) in the cold tongue region during pre-CE conditions with cooler SST over the western PO (Fig. 2(f)). It implies that before the onset of the protracted ENSO event, heating is confined to the western Pacific with additional cooling along the eastern Pacific due to the presence of trade winds in the eastern Pacific.
Figure 3 shows the mean SST during NS, CE, and PE events for model control run (Fig. 3(a-c)) and observations (Fig. 3(d-f)) and their respective differences (Fig. 3(g-i)). Higher values of SST are seen over the Indo-Pacific warm pool region with the extent of the warm pool from the eastern Indian Ocean to the western Pacific Ocean. A comparison of mean SST in model control run and observations during NS shows warmer (cooler) SST in western (eastern) PO near the dateline in the model control run. Also, mean SST is cooler over the Arabian Sea and Bay of Bengal region in the model control run compared to observed SST. This structure of model bias is systematic and appears during CE as well as PE with a small difference in magnitude. This systematic bias in SST in the Pacific Ocean in OGCM leads to an increased east-west gradient of SST along the equator in the Pacific Ocean compared to observations. Since zonal SST gradients are coupled to atmospheric zonal circulation, known as the Walker circulation (Allan and D’Arrigo 1999b; Levine and McPhaden 2016; Arora and Kumar 2019); any change in zonal SST gradient can further alter the zonal tilt of the oceanic thermocline and the strength of equatorial upwelling. Figure 4 shows the difference of SST for the mean states of CE, PE, and NS states for the model control run and observations as shown in Fig. 3. Difference of mean SST during CE state from NS and PE state in the model control run simulate warmer SST with wider horizontal extent over Indo-Pacific warm pool along with basin-wide warmer SST in the Indian Ocean compared to observations. The difference of mean SST during PE state from NS state shows cooler SST over the equatorial eastern-central PO. This is due to the presence of anomalous easterly trade winds during protracted ENSO events(Levine and McPhaden 2016).
Figure 5 shows the mean D20 during NS, CE, and PE events for model control run (Fig. 5(a-c)) and observations (Fig. 5(d-f)) and their respective differences (Fig. 5(g-i)). OGCM can simulate the subsurface structure of the thermocline very well consistent with the surface. Systematic warm SST bias present over Indo-Pacific warm pool and western PO is also seen at subsurface levels in model control simulation. Model control run can capture spatial structure of shallow thermocline regions in the Western Indian Ocean (IO) (the Seychelles Dome) and eastern Pacific (Yokoi et al. 2008) (Fig. 5). However, the value of D20 in deeper thermocline regions has a positive bias in western and southern tropical IO and the northern Pacific during all types of ENSO events (NS, CE, and PE). This positive bias is strongest in the case of PE events. Also, D20 is underestimated (overestimated) in NS and CE (PE) events in the southwestern and central Pacific. Figure 6 shows the difference of mean D20 for CE, PE, and NS states for the model control run and observations as shown in Fig. 5. Indian ocean shows a relatively deeper thermocline mainly throughout the basin during CE and PE events compared to NS with shallower D20 during CE event in observations as well as model control run. A deeper (shallower) thermocline depth in western PO during PE and CE compared to NS is a qualitative measure of the higher value of WWV acting as a precursor for the initiation of ENSO (Arora and Kumar 2019). Also, higher values of D20 are seen over the western Pacific during PE compared to CE events consistent with previous studies (Levine and McPhaden 2016; Arora and Kumar 2019).
3.2 Preconditioning of equatorial Pacific for triggering of ENSO
Figure 7 shows the mean zonal wind forcing anomaly at 10m averaged over equatorial Western Pacific (100–200°E, 2.5°S-2.5°N) for NS, CE, and PE states. Wind forcing for NS indicates the dominant presence of westerlies (positive values) over the Western Pacific region embedded with easterlies (negative values). Zonal wind forcing anomaly at 10m shows predominant westerlies with maximum values (up to 6m/s) at the end of the year 1982 yielding a peak of strong El Niño. Along with the change in phase of SST anomalies averaged over the Niño 3.4 region, zonal wind anomalies over Western Pacific also change to easterlies following (Bjerknes 1969)’s positive feedback in equatorial PO. Wind forcing anomaly during PE events hovers around mean value with values ranging from − 4 to 4 m/s. Figure 8 shows the histogram of wind forcing anomaly shown in Fig. 7 for NS, CE, and PE states. The distribution of zonal wind anomaly averaged over the western Pacific Ocean follows a normal distribution for PE state. However, this distribution is slightly skewed towards positive values indicating the presence of more anomalous westerlies during NS, and skewness towards positive values increases more during CE compared to NS. This implies that the difference in zonal wind forcing at the surface in the western Pacific before the onset of El Niño can trigger different states of ENSO in the eastern Pacific.
Warm water volume (WWV) is defined as the volume of water up to 20°C isotherm depth and is an important predictor of ENSO (Meinen and McPhaden 2000; Bunge and Clarke 2014). WWV is calculated for the equatorial eastern PO (EP; 5°S-5°N, 80°W-155°W), western PO (WP; 5°S-5°N,120°E-155°W), and total PO (TP; 5°S-5°N, 120°E-80°W). Figure 9 compares WWV anomalies calculated for the model control run with WWV calculated using EN4-v4.2.1 for TP, EP, and WP. Model control simulation well captures the WWV over the WP region with a very high correlation with observations for NS, CE, and PE (0.79, 0.8, and 0.75 respectively). The value of the correlation of WWV over TP (EP) among observations and model control run is 0.32, 0.67, and 0.41 (0.3, 0.19, and 0.54) for NS, CE, and PE respectively. All values except 0.19 are statistically significant at 90%. WWV anomaly averaged over TP and WP remains below normal the climatology for NS for model control run as well as observations indicating no build-up of heat content in TP and WP. WWV averaged over EP hovers around the mean value during NS indicating the presence of no ENSO-like conditions in EP. During the CE event, WWV averaged over TP and WP increased before the peak of the El Niño event and then decreased as El Niño made the transition to La Nina. WWV averaged over CE starts increasing from the beginning of 1982. It reaches maximum value around the end of 1982 and then reverses its sign with the transition of El Niño to La Nina. (Arora and Kumar 2019) highlighted a high value of correlation (0.8) between SST anomaly averaged over Niño 3.4 region and WWV anomaly averaged over EP. Discharge of warm water from WP towards EP leads to initiation of El Niño with a lead period of 6–10 months and WWV averaged over EP leads Niño 3.4 SST anomaly by 1–2 months. WWV averaged over TP and WP shows above normal values along with an increasing trend during PE. This increasing trend in anomalous WWV is due to the build-up of heat content in WP due to the presence of weak westerly or easterly winds during boreal summer and fall months (Allan and D’Arrigo 1999b; Levine and McPhaden 2016; Arora and Kumar 2019). Also, anomalous WWV averaged over EP remains positive indicating persistent El Niño type conditions throughout the PE duration (1990-94) consistent with the previous study (Arora and Kumar 2019) for both model control run as well as observations.
3.2 Changes in surface and subsurface parameters during model experiments
Figure 10 shows ocean temperature anomaly averaged over Niño 3.4 region for different layers of the upper ocean for model control as well as six experimental runs overlaid by observed temperature anomaly. The value of the correlation of ocean temperature anomaly averaged over Niño 3.4 region averaged over layers of upper ocean (5-100m, 100-200m, and 200-300m) between model control run and observations is 0.81, 0.61, and 0.19 respectively. These correlation values are statistically significant at 99%. A significant value of correlation between temperature anomaly simulated by OGCM averaged over these layers with observed temperature anomaly implies that the model can capture temperature in the upper ocean over Niño 3.4 region well. Temperature anomalies in the near-surface layer (5-100m) in the upper ocean are better captured compared to the deeper layer of the upper ocean (200-300m). Forcing of normal ocean state (NS:1958-62) with horizontal wind forcing at 10m during protracted ENSO (PE:1990-94; exp5) years and canonical (CE:1980-84; exp6) ENSO years perturb mean anomalous state to have variability of PE and CE state. A similar change in variability of CE (PE) state compared to model control run is observed when forced with horizontal winds of PE (CE) and NS respectively. Table 1 provides a list of experiments performed using OGCM. This interplay of horizontal wind forcing among the NS, PE, and CE states of the ocean shows the importance of strength and variability of winds as a governing factor in the onset and type of ENSO. Subsurface layers (100-200m, 200-300m) in the upper ocean over Niño 3.4 region also vary following surface layers due to shallow thermocline depth over the equatorial eastern Pacific Ocean (Zelle et al. 2004).
Figure 11 shows the ocean temperature anomaly averaged over 5°S–5°N up to 300 m depth for PE, CE, and NS for model simulations and observations. Observed PE event shows the strengthening of positive anomalies near the surface in the eastern PO extending up to date line along with negative subsurface anomalies in the western PO. Compared to PE, the extent of positive anomalies is confined to the eastern Pacific only for CE event. However negative subsurface anomalies indicating the presence of upwelling Kelvin waves are more zonally extended in CE event compared to PE event. NS does not show any significant surface or subsurface anomalies. Model control run overestimates the ocean temperature anomalies during NS and PE compared to observations. Though the zonal extent of anomalies from the eastern Pacific in the model control run matches well with observations, subsurface anomalies from the western Pacific are far more zonally extended and strengthened in model control run compared to observations especially in the case of PE and NS. Change of zonal wind forcing over the pre-PE state to the wind forcing used during the CE period (exp1) shows a reduction in the magnitude of subsurface temperature anomalies. Also, the zonal extent of positive anomalies from the eastern Pacific decreases in the case of exp1 compared to model control run and observations. Forcing the pre-PE state with wind forcing during NS (exp2) completely diminishes the ENSO-like conditions in the equatorial Pacific. Similarly forcing the pre-CE state with wind forcing during PE (NS) show the strengthened (diminished) subsurface signature of PE (NS). Forcing of pre-NS state with wind forcing of PE (exp5) and CE (exp6) shows weakened PE and CE-like structure due to the presence of La Nina-like conditions due to systematic bias during NS in the model control run.