Sea Surface Salinity Changes in Response to El Niño–like SST Warming and Relevant Ocean Dynamics in the Tropical Pacific under the CMIP6 Abrupt-4XCO2 Scenario

Qiwei Sun aSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China
bState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
cCollege of Marine Science, University of Chinese Academy of Sciences, Beijing, China

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Yan Du bState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
aSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China
cCollege of Marine Science, University of Chinese Academy of Sciences, Beijing, China

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Abstract

Based on the abrupt-4XCO2 scenario in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study investigates the response of the rainfall changes to El Niño–like SST warming and the role of ocean dynamical processes in the salinity changes in the tropical Pacific. The results show that the Walker circulation weakening and eastward shift, related to El Niño–like SST warming, dominates the zonal precipitation change. Precipitation decreases (increases) in the Maritime Continent (the equatorial Pacific), partly offsetting the effect of specific humidity. At the same time, the El Niño–like warming triggers convergence of meridional winds, which leads to a precipitation increase in the equatorial Pacific and a decrease in the intertropical convergence zone and the South Pacific convergence zone, following the “warmer-get-wetter” mechanism. Unlike the spatial pattern of precipitation changes, the sea surface salinity changes become fresher in the tropical western Pacific, related to the precipitation and the mean horizontal advection. The precipitation increase leads to negative salinity anomalies in the equatorial central Pacific. The westward climatological zonal currents transport the negative salinity anomalies westward. The meridional currents advect the salinity anomalies to both sides of the equator, partly offsetting the contribution of the freshwater flux on the salinity change. In addition, shallower mixed layer depth and weakening upwelling bring less high-salinity water to the surface and impact salinity redistribution through the vertical process in the equatorial regions.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Yan Du, duyan@scsio.ac.cn

Abstract

Based on the abrupt-4XCO2 scenario in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study investigates the response of the rainfall changes to El Niño–like SST warming and the role of ocean dynamical processes in the salinity changes in the tropical Pacific. The results show that the Walker circulation weakening and eastward shift, related to El Niño–like SST warming, dominates the zonal precipitation change. Precipitation decreases (increases) in the Maritime Continent (the equatorial Pacific), partly offsetting the effect of specific humidity. At the same time, the El Niño–like warming triggers convergence of meridional winds, which leads to a precipitation increase in the equatorial Pacific and a decrease in the intertropical convergence zone and the South Pacific convergence zone, following the “warmer-get-wetter” mechanism. Unlike the spatial pattern of precipitation changes, the sea surface salinity changes become fresher in the tropical western Pacific, related to the precipitation and the mean horizontal advection. The precipitation increase leads to negative salinity anomalies in the equatorial central Pacific. The westward climatological zonal currents transport the negative salinity anomalies westward. The meridional currents advect the salinity anomalies to both sides of the equator, partly offsetting the contribution of the freshwater flux on the salinity change. In addition, shallower mixed layer depth and weakening upwelling bring less high-salinity water to the surface and impact salinity redistribution through the vertical process in the equatorial regions.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Yan Du, duyan@scsio.ac.cn

1. Introduction

As an important part of the climate system, precipitation (P) and evaporation (E) are the two most important processes for the water cycle in the ocean (Du et al. 2019; Schmitt 2008; Yu 2011). In the tropics, abundant precipitation appears in the ascending branch of the atmospheric circulation, such as the intertropical convergence zone (ITCZ) and the South Pacific convergence zone (SPCZ) (Thompson et al. 1979; Trenberth 1976; Vincent 1994). In the subtropics, strong evaporation is stronger than precipitation due to atmosphere sinking movement. As an “ocean rain gauge,” sea surface salinity (SSS) could indicate the ocean water cycle (Du et al. 2019; George et al. 1997; Nielsen et al. 2003; Reul et al. 2014; Schmitt 2008; Yu 2011). High SSS in the subtropics and low SSS in the tropics (the freshwater pool) are consistent with freshwater flux on a global scale (Durack 2015). The investigation of the SSS changes provides a new perspective on global water cycle changes.

With human activities releasing carbon dioxide into the atmosphere, the global surface temperature has kept increasing since the industrial revolution (Collins et al. 2006; Joos et al. 2013; Long and Collins 2013; Shindell et al. 2013). Global warming directly leads to a sea level increase, the sea ice melting, and the occurrence of extreme weather or climate, such as marine heatwaves (Church and White 2006; Church et al. 2004; Diffenbaugh et al. 2005; Wu et al. 2011). The global water cycle has changed in response to global warming (Chadwick et al. 2013; Huang et al. 2013; Ma et al. 2018; Seager et al. 2010). According to the Clausius–Clapeyron (CC) relation, total water vapor increases by 7% °C−1 (Allen and Ingram 2002; Held and Soden 2006). Increasing specific humidity could strengthen the global water cycle under global uniform warming (Adler et al. 2017; Han et al. 2019; Marvel and Bonfils 2013; Meehl and Teng 2014; Sarojini et al. 2016). Specifically, tropical regions become wetter with more precipitation, and subtropics become direr with enhanced evaporation, following the “wet-get-wetter, dry-get-drier” mechanism on global scales (Chou and Neelin 2004; Chou et al. 2009; Held and Soden 2006).

However, there are still many important scientific problems to be solved. The mechanism only considers the thermodynamic processes (humidity increase) under global uniform warming. It does not consider the dynamic processes (e.g., the atmospheric circulation change) associated with non-uniform spatial warming. Previous studies show that the long-term warming trend of sea surface temperature (SST) is not uniform, with significant spatial patterns (Liu et al. 2005; Tokinaga et al. 2012; Vecchi et al. 2008). The SST warming pattern is controversial from different reconstructed datasets based on the observations, especially in the tropical Pacific. The SST presents a La Niña–like warming pattern in the tropical Pacific in Kaplan SST and HadISST but an El Niño–like warming pattern in ICOADS and ERSST. These results show that the spatial heterogeneity sampling of historical observations affects the accuracy of long-term trend assessment in SST. For most of the coupled models in the Coupled Model Intercomparison Project phase 5 (CMIP5) and phase 6 (CMIP6) abrupt-4XCO2 scenario in this paper (Figs. 1a and 4a), the SST shows an El Niño–like warming pattern, similar to the ICOADS and ERSST observations (Vecchi and Soden 2007; Yeh et al. 2012). The non-uniform SST warming patterns play an essential role in precipitation change. On the one hand, the El Niño–like warming could change the zonal SST gradient in the tropical Pacific, which leads to atmospheric circulation and precipitation changes. On the other hand, Xie et al. (2010) pointed out the “warmer-get-wetter” mechanism to explain that the precipitation will increase in the regions with stronger SST warming. These changes reflect the importance of dynamic processes. The “wet-get-wetter” mechanism cannot explain the precipitation change in the tropical Pacific. This raises a scientific question: How do dynamic and thermodynamic processes affect precipitation changes under El Niño–like SST warming patterns?

There is a close relationship between SSS and surface freshwater flux, reflecting the dynamic balance between global freshwater flux and ocean dynamic processes (Durack et al. 2012; Schmitt 1995; Yu et al. 2020; Yu 2014). Researchers used the long-term trend of SSS to evaluate the water cycle changes (Boyer et al. 2005; Durack and Wijffels 2010; Hosoda et al. 2009; Skliris et al. 2014). On a global scale, high-salinity regions (e.g., subtropics) have become more saline, while low-salinity regions (e.g., tropics and high latitudes) have become fresher since the 1950s (Cheng et al. 2020; Durack et al. 2012; Lago et al. 2016; Zika et al. 2018), providing evidence for the enhancement of global water cycle.

Fig. 1.
Fig. 1.

The 7-yr running-mean leading EOF mode of (a) SST, (b) precipitation, and (c) SSS under the abrupt-4XCO2 scenario. (d) The corresponding principal component time series of SST (red line), precipitation (black line), and SSS (green line).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Although the spatial distribution of SSS is directly affected by freshwater flux, the central position between freshwater flux and SSS is not completely consistent, even in the Pacific warm pool and ITCZ regions with the most abundant precipitation (Du et al. 2019; Yu 2014). Previous studies reveal that the ocean dynamic processes, such as ocean horizontal advection, vertical entrainment, mesoscale eddies, and mixing, play an important role in salinity distributions (Kouketsu et al. 2017; Liu et al. 2019; Mignot and Frankignoul 2003, 2004; Ponte and Vinogradova 2016; Trott et al. 2019; Zhang et al. 2018). For example, Vinogradova and Ponte (2017) find that the interdecadal trend of global SSS has not shown the enhancement of the water cycle in the past two decades. In some regions, even if the precipitation increases, the SSS will not become fresher. It is necessary to consider the ocean dynamic processes in estimating the relationship between the water cycle and SSS. Therefore, this raises another question: What is the role of ocean dynamics, especially horizontal and vertical advection, in long-term salinity changes under global warming?

This study uses CMIP6 4 × CO2 forcing to investigate the tropical Pacific rainfall and SSS changes in response to global warming. The results show that the dynamic processes (wind changes) dominate the rainfall changes due to El Niño–like SST warming. For salinity changes, ocean dynamics, especially the mean horizontal currents, play an important role in balancing the mismatch between the precipitation and salinity changes.

The rest of the paper is organized as follows. Section 2 briefly describes the data and methods. Section 3 presents the general features of SST and precipitation changes in response to global warming. Section 4 compares the role of dynamics and thermodynamics in tropical rainfall changes. Then, we focus on the salinity changes and related ocean dynamics in section 5. Section 6 presents conclusions with discussion.

2. Data and methods

a. Data

The CMIP6 experiments (Eyring et al. 2016; O’Neill et al. 2016) used here is a 150-yr abrupt-4XCO2 scenario: a coupled ocean–atmosphere experiment with CO2 concentrations abruptly quadrupled from preindustrial levels at the start and then held constant. There are two purposes for using the abrupt-4XCO2 scenario in this paper. One is to study the effect of CO2 increase on SST, precipitation, and salinity changes and further estimate their long-term change. The other is because internal variability leads to large uncertainties in estimating the salinity trends due to radiative forcing in our previous study (Sun et al. 2021). The abrupt-4XCO2 scenario could reduce the impacts of the internal variability in assessing the salinity changes and relevant physical processes. The monthly variables of 15 models (listed in Table 1) are used in this study, including SST, precipitation, evaporation, SSS, specific humidity, winds, vertical motion, and ocean currents. For models with more than one ensemble member for the abrupt-4XCO2, only the first member-run (e.g., r1i1p1f1) is used. CMIP6 model outputs are available from the Earth System Grid Federation (ESGF) (https://esgf-node.llnl.gov/projects/cmip6/). Using the least-squares method, all data are gridded to a common grid (1° × 1°). Unless noted otherwise, we used the ensemble mean of the 15 models to estimate the salinity changes, reducing the uncertainty from model biases.

Table 1

List of 15 CMIP6 models used in this study.

Table 1

In addition, this paper uses the CMIP6 historical scenario and observations datasets to estimate the biases and compare with the results from the abrupt-4XCO2 scenario, including 1) the EN4 version 4.2.1 salinity and temperature datasets provided by the Met Office Hadley Centre (Good et al. 2013), 2) the National Centers for Environmental Prediction (NCEP) wind (Kalnay et al. 1996), and 3) the Global Precipitation Climatology Project (GPCP) precipitation (Adler et al. 2003).

b. Methods

1) Moisture budget

Based on the water vapor transport (Richter and Xie 2010; Xu et al. 2005), this paper calculates the moisture budget:
PE=1gρw(ptpsqVdp),
where P is precipitation, E is evaporation, is the divergence operator, and ps and pt are atmospheric pressure at the surface and the top of the troposphere, respectively; also, q is specific humidity, V is the horizontal wind vector, and p is atmospheric pressure. Based on the mean state and long-term changes (such as q=q¯+q), this paper further decomposes the water vapor flux (qV) to four terms:
qV=q¯V¯+qV¯+q¯V+qV,
where q¯ and V¯ represent the mean state of the specific humidity and horizontal wind in the first 20 years, respectively; q′ and V′ represent the differences between the last 20 years and the first 20 years for the specific humidity and horizontal wind, respectively. The moisture budget equation, Eq. (1), is rewritten as
(PE)=1gρw[ptps(qV¯+q¯V+qV)dp].
The three terms on the right side of Eq. (3) represent the moisture divergence caused by the specific humidity changes, wind changes, and both changes, respectively.

2) Dynamic and thermodynamic decomposition in rainfall changes

Following Chadwick et al. (2013), the rainfall changes are separated into thermodynamic and dynamical components:
ΔP=Δ(Mq)=MΔq+qΔM+ΔqΔM=MΔqCC+MΔqRH+qΔMweak+qΔMshift+ΔqΔM=ΔPt+ΔPRH+ΔPweak+ΔPshift+ΔPNL,
where Δ is defined as the differences between the last 20 years and the first 20 years, P is precipitation, q is 2-m specific humidity, and M is a proxy for convective mass flux from the boundary layer to the free troposphere (Mc), defined as M = P/q. Thus M could represent the changes in atmospheric circulation. The term ΔPt is the thermodynamic change of the rainfall due to Clausius–Clapeyron (CC) related specific humidity (ΔqCC) increases at constant M; ΔPRH is the rainfall change due to relative humidity changes, ΔqRH = Δq − ΔqCC, and ΔPweak is the rainfall change due to the weakening tropical circulation at constant q, representing the dynamic processes. The term ΔMweak = aM is the weakening of atmospheric circulation, where a = −0.11 is the coefficient of least-squares fitting between ΔM and M (Fig. S1 in the online supplemental material); ΔPshift is the rainfall change due to spatial shifts of convective mass flux; ΔMshift (=ΔM − ΔMweak) explains the nonlinear change of M [see, e.g., Fig. S1 (cyan scatters) in the online supplemental material]; and ΔPNL is the “nonlinear term” component of rainfall change.

3) Mixed layer salinity budget

By neglecting the higher-order nonlinear terms, the mixed layer salinity (MLS) budget equation can be written as (Qu et al. 2013; Sun et al. 2019)
[S]t=(PE)h[S](uS,υS)we[S]Shh+ε,
where [S] means the MLS, [S]/t is the MLS tendency, P and E are the precipitation and evaporation rates, h is the mixed layer depth, u and υ are the zonal and meridional velocities, and =(/x,/y) is the horizontal gradient operator; also, Sh is chosen as the salinity 15 m below the mixed layer base (Ren et al. 2011). Vertical entrainment velocity (we) is calculated as we=(h/t)+(hu/x)+(hυ/y). In the following text, horizontal advection with vertical entrainment terms is called S-adv. For simplicity, the horizontal and vertical mixing and the accumulation of errors from the other terms are added to the residual term ε.
Similar to the moisture budget, every variable is divided into two parts: the climatological mean and the anomaly (e.g., u=u¯+u). The salinity horizontal advection and vertical entrainment terms can be rewritten as (Sun et al. 2019; Zhang et al. 2013) follows:
(u¯[S]x+u[S]¯x+υ¯[S]y+υ[S]¯y)we[S]Sh¯h.

3. General features of SST and precipitation changes under global warming

First, this paper evaluates the CMIP6 model simulations and biases in SST, precipitation, SSS, and surface wind (Figs. 2 and 3). Due to the limitations of abrupt-4XCO2 forcing, this paper also uses the same 15 models under the CMIP6 historical scenario to compare with observations during the same period. The results show that the CMIP6 multimodel mean can capture the general characteristics of SST, precipitation, SSS, and surface wind in tropical regions. For instance, easterly trade wind leads to the warming pool in the western tropical Pacific, which is consistent with the observation results. There is strong precipitation in the ITCZ and SPCZ regions, causing low salinity in the tropics.

Fig. 2.
Fig. 2.

The spatial distributions of SST (shading; °C) and wind (vectors; m s−1) for (a) CMIP6 abrupt-4XCO2 years 1–20 annual mean of the multimodel mean, (b) CMIP6 Historical 1981–2010 annual mean of the multimodel mean, (c) EN4 SST and NCEP wind 1981–2010 annual mean, and (d) the biases between CMIP6 Historical and observations.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Fig. 3.
Fig. 3.

As in Fig. 2, but for the SSS (shading; psu) and precipitation (contours; mm day−1).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

However, there are intermodel uncertainties and model biases in the CMIP6 abrupt-4XCO2 and historical scenarios. For instance, the standard deviation of 15 models for SSS years 1–20 annual mean shows the intermodel uncertainties in the tropics, especially in the tropical western Pacific (Fig. S2). In the tropics, the precipitation location and intensity are different in models, especially in the tropical western Pacific and ITCZ region (figure not shown). This leads to a relatively higher SSS for ITCZ in the western Pacific in the CNRM-CM6-1, IPSL-CM6A-LR, and MRI-ESM2-0 models (Fig. S2). To reduce the model uncertainties, we used the average of the 15 models to study the salinity changes and related physical processes, unless noted otherwise.

In addition, well-known biases in SST, wind, and precipitation exist in CMIP6 models, similar to CMIP5 results (Figs. 2d and 3d). Specifically, there is an excessive westward extension of the equatorial cold tongue and surface easterly wind anomalies in equatorial Pacific, and weaker equatorial western Pacific precipitation biases. The tropical Pacific SST biases are associated with the insufficient precipitation/clouds over the western Pacific warm pool, with weaker negative SST–convective feedback (Li et al. 2016). In addition, the anomalous easterly winds regulate the oceanic upwelling and thermocline depth to enhance the excessive equatorial cold tongue (Li and Xie 2014; Bellenger et al. 2014). These biases challenge the reliability of our results when using these models. Appling an “observational constraint” to calibrate the tropical SST changes, a previous study revealed that SST changes robustly show an El Niño–like warming pattern under global warming in the CMIP5 models (Li et al. 2016). Fortunately, the results in this paper indicate that SST shows high model consistency with an El Niño–like warming pattern (Fig. 4a; see also Fig. S3) in response to high-concentration 4 × CO2 forcing in CMIP6. These changes lead to more reliable results in the tropical Pacific.

Fig. 4.
Fig. 4.

(a) The spatial distributions of SST (contours; °C) and precipitation (shading; mm day−1) changes between years 131–150 and 1–20 for the multimodel mean CMIP6 abrupt-4×CO2. (b) As in (a), but for SSS (shading; psu). (c) EN4 SSS 1951–2010 trend (shading; psu) and (d) the CMIP6 abrupt-4XCO2 SSS (shading; psu) changes minus the biases between CMIP6 Historical and observations. Gray stippling in (a) and (b) indicates high model consistency, where ≥90% of models agree on the sign of change.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

For precipitation and SSS biases (Fig. 3d), there are two significant features: weaker precipitation and saltier SSS in equatorial western Pacific precipitation and double ITCZ biases with fresher SSS in the regions (Lin 2007; Li and Xie 2014). The former is related to the westward expanded cold tongue mentioned above. The latter is complex, which is related to the zonal SST gradient–trade wind feedback (or Bjerknes feedback), the SST–surface latent heat flux (LHF) feedback (Lin 2007), and wind–evaporation–SST (WES) feedback (Li and Xie 2014). Compared with the precipitation biases, the precipitation changes are large in response to 4 × CO2 forcing. In addition, similar to the SST, the precipitation changes also have high model consistency with an increase in the equatorial Pacific and a decrease in the ITCZ and SPCZ regions (Fig. 4a; see also Fig. S3), which is partly opposite to the model biases, indicating the precipitation biases have weak impacts on the precipitation changes. These results both enhance the reliability of our conclusions.

Then, this paper compares the leading EOF mode of SST, precipitation, and SSS under 4 × CO2 forcing (Fig. 1). The leading principal component (PC1) in SST, precipitation, and SSS includes the rapid increasing phase and the slowly increasing phase, which capture the long-term change in response to the 4 × CO2 forcing (Fig. 1d). The main difference is that the response rate of SSS and precipitation is slightly slower than that of SST. The lag response may reflect the influence of SST on precipitation and salinity changes.

Under the 4 × CO2 forcing, the spatial pattern of SST is global warming with an El Niño–like pattern in the tropical Pacific (Figs. 1a and 4a), which is consistent with the CMIP5 results (Vecchi and Soden 2007; Yeh et al. 2012). The SST warming increases the specific humidity, especially in the tropical central and eastern Pacific (Fig. 5). Previous studies found that the water vapor increase rate is 7% °C−1, following the Clausius–Clapeyron equation (Chou and Neelin 2004; Held and Soden 2006). The increase in water vapor capacity could promote rainfall in tropical regions. In addition, the El Niño–like warming pattern changes the zonal SST gradient in the tropical Pacific Ocean. Previous studies have shown that the Pacific zonal SST gradient leads to the change of zonal wind and the adjustment of Walker circulation (Bayr et al. 2014; Choi et al. 2016; L’Heureux et al. 2013; Ma and Zhou 2016), further impacting the distribution of precipitation in the regions (Huang 2014; Zheng et al. 2019).

Fig. 5.
Fig. 5.

(a) Years 1–20 annual mean and (b) changes between years 131–150 and 1–20 in specific humidity (shading; %) and wind (vectors; m s−1) at the sea surface. (c),(d) As in (a) and (b), but for 850 hPa.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

The spatial pattern of precipitation changes shows a zonal distribution in the Pacific. Precipitation increases in the equatorial and subpolar regions and decreases in the extra-equatorial and subtropical regions (Figs. 1b and 4a). This zonal distribution is approximately consistent with previous studies, following the wet-get-wetter pattern in response to global warming on basin scales (Chou and Neelin 2004; Chou et al. 2009; Held and Soden 2006). However, in the tropical Pacific, the correlation between precipitation changes and the climatological mean is only 0.18, which does not follow the wet-get-wetter mechanism (Fig. 4a). Specifically, the precipitation shows a weakening trend in the Maritime Continent, ITCZ, and SPCZ regions, which feature abundant precipitation in the mean state. In the equator and the south of the equator, the precipitation is increasing, contrary to the wet-get-wetter mechanism. This result shows that precipitation changes are affected by thermodynamic processes (e.g., specific humidity increasing) and other factors (e.g., the change and nonlinear effect of atmospheric circulation in response to SST warming) (Emori and Brown 2005; Norris et al. 2019; Seager et al. 2010).

In addition, previous studies found that the precipitation increase rate is only 1%–2% °C−1, significantly lower than the increase rate of water vapor. Under the 4 × CO2 forcing, the wind changes are the westerly anomalies, opposite to the climatological easterly wind in the tropical Pacific (Figs. 4a and 4b). The atmospheric circulation shows a weakening change, consistent with previous results (Tokinaga et al. 2012; Vecchi and Soden 2007). The weakening wind anomalies may reduce the precipitation increasing to matching the ratio between the precipitation and water vapor, indicating that the dynamic processes play an important role in the rainfall changes.

4. The role of dynamics and thermodynamics in tropical rainfall changes

To study the role of thermodynamics and dynamics in precipitation changes, this study separates the effects of specific humidity and wind anomalies on the water cycle based on the moisture budget equation (Fig. 6). The results show that the changes in total moisture convergence and divergence are positive in the equatorial Pacific and negative in the Maritime Continent, ITCZ, and SPCZ regions, which are consistent with the spatial distribution of freshwater flux changes (Figs. 6d and 7a).

Fig. 6.
Fig. 6.

Spatial distribution of moisture divergence changes: (a) total moisture divergence changes, (b) moisture divergence changes due to specific humidity change, (c) moisture divergence changes due to wind change, and (d) moisture divergence changes due to specific humidity and wind change and residual term. (e),(f) As in (c), but for zonal and meridional components, respectively. Unit: mm day−1. The contours in (a) are the sum of (b) and (f).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Fig. 7.
Fig. 7.

Spatial distribution of decomposed components of precipitation change between years 131–150 and 1–20: (a) total precipitation change (shading; mm day−1) and years 1–20 mean state of precipitation (contours; mm day−1), and (b)–(h) ΔPshift, ΔPt, ΔPweak, the sum of ΔPt and ΔPweak, the sum of ΔPRH, ΔPNL and the Residual term, respectively. The contours in (b) are SST changes. Gray stippling indicates high model consistency, where ≥90% of models agree on the sign of change.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

The change of moisture convergence and divergence caused by the increase of specific humidity is related to the spatial pattern of climatological rainfall (Fig. 6b). In the Maritime Continent, ITCZ, and SPCZ regions, the moisture convergence enhances (negative anomalies in Fig. 6), indicating precipitation increases. In the divergence areas, such as the tropical southeastern Pacific and subtropics, the moisture divergence increases (positive anomalies in Fig. 6), indicating precipitation decreases. When the atmospheric circulation is constant, the increase of specific humidity leads to the enhancement of the water cycle, which follows the wet-get-wetter mechanism. However, this pattern is opposite to the total moisture divergence changes in the Maritime Continent, ITCZ, and SPCZ regions (Figs. 6a and 6b), indicating that increase in specific humidity is not the main factor for local precipitation change.

The pattern of moisture divergence caused by the change of atmospheric circulation is similar to that of the total moisture divergence, dominating the change of freshwater flux in the tropical Pacific (Figs. 6a and 6c). In the Maritime Continent, ITCZ, and SPCZ regions, the moisture convergence decreases (negative anomalies), which is opposite to the spatial pattern of moisture convergence caused by the increase of specific humidity (Chadwick et al. 2013; Ma et al. 2018). In the equatorial Pacific, the moisture convergence caused by wind anomalies is enhanced (positive anomalies), increasing local precipitation. Furthermore, the zonal component contributes to moisture convergence decreases in the Maritime Continent regions due to wind weakening (Fig. 6e). However, the meridional component is more important to the moisture convergence increase in the equatorial Pacific and decrease in the ITCZ and SPCZ regions (Fig. 6f). These processes show that the role of dynamic processes is different in regions.

Following Chadwick et al. (2013), this paper further distinguishes the effects of the atmospheric circulation weakening (ΔPweak) and atmospheric circulation shift (ΔPshift) on precipitation changes (Fig. 7). ΔPweak shows precipitation decreases in the tropical Pacific, especially in the Maritime Continent, ITCZ, and SPCZ regions, caused by the weakening of atmospheric circulation, which is opposite to ΔPt, which is caused by the increase of specific humidity (Figs. 7c and 7d). Under 4 × CO2 forcing, the sea surface and the 850-hPa wind show westerly anomalies in the tropical Pacific, opposite to the climatological easterly trade winds (Fig. 5). In the ascending branch of the Walker circulation, especially in the Maritime Continent (100°–130°E), the vertical component of the atmospheric circulation is downward anomalies (Fig. 8c; see also Fig. S5), revealing that the tropical atmospheric circulation is weakening, in agreement with previous studies (Bayr et al. 2014; DiNezio et al. 2013; Gastineau et al. 2009; Power and Kociuba 2011; Tokinaga et al. 2012; Vecchi et al. 2006). Ma et al. (2012) proposed the mean advantage of stratification change (MASC) to explain the weakening of Walker circulation. The mechanism reveals that the temperature increases faster in the upper troposphere, which reduces the vertical temperature gradient, weakening the atmospheric circulation. The changes in convective mass flux (Mweak) also support the weakening of atmospheric circulation in the tropical Pacific (Fig. S4b). The weakening of atmospheric circulation further leads to the precipitation decrease in the tropical convective zones. The effect of specific humidity increasing and atmospheric circulation weakening on rainfall changes offset each other, the wet-get-wetter mechanism cannot explain the precipitation changes. It shows that the thermodynamic processes are not important in the precipitation changes. The spatial pattern of precipitation changes is mainly determined by ΔPshift (Figs. 7a and 7b).

Fig. 8.
Fig. 8.

Pressure–longitude sections of (a) the years 1–20 annual mean, (b) the years 131–150 annual mean, (c) the differences between years 131–150 and 1–20 along the equator (meridionally averaged in 2°S–2°N), and (d) pressure–latitude sections of the differences between years 131–150 and 1–20 along the international date line (zonally averaged over 179°E–179°W) in the vertical wind (vectors; m s−1) and specific humidity (shading; %).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

In the equatorial Pacific, the change of convective mass flux is positive, revealing an increasing trend of atmospheric convergence (Fig. S4c). Specifically, the atmospheric deep convection increases in the 150°E–160°W equatorial regions (upward anomalies; Fig. 8c), opposite to that in the Maritime Continent, indicating that the Walker circulation eastward shifts, which is closely related to the SST warming pattern. On the one hand, the El Niño–like SST warming in the eastern Pacific weakens the zonal SST gradient, inducing the Walker circulation weakening and eastward shift. These changes result in precipitation increasing in the equatorial Pacific due to Walker circulation eastward shift, while precipitation decreases in the Maritime Continent and the southeastern Indian Ocean due to Walker circulation weakening, similar to the changes when an El Niño event occurs. On the other hand, the warmer-get-wetter mechanism explains the precipitation increases in the equatorial Pacific (Xie et al. 2010). The increase of SST in the equatorial Pacific is warmer than that of the surrounding regions (e.g., the ITCZ and SPCZ regions). This warming pattern changes the meridional SST gradient, causing the convergence of meridional wind in the equatorial Pacific, northerly anomalies in the north, and southerly anomalies in the south of the equator (Fig. 8d; see also Fig. S6). These lead to precipitation increases in the equatorial regions and decreases in the surrounding regions. It is worth noting that different intensity changes in meridional wind and specific humidity in different models lead to corresponding precipitation intensity changes. For instance, there are weaker changes in meridional wind and specific humidity in GISS-E2-1-G and MIROC6 (Fig. S6). The corresponding precipitation changes in these models also show weaker changes in the equatorial Pacific (Fig. S3).

5. Salinity changes and related ocean dynamics

The SSS changes in 15 models are shown in Fig. 9. The 15 models have high model consistency in the tropical Pacific (Fig. 4b), with a strong decrease in the tropical western Pacific and a weak increase in the eastern Pacific under 4 × CO2 forcing. Similar to the mean state, the significant model uncertainty in the tropics is located in the tropical western Pacific (Fig. 9p; see also Fig. S2). Some models’ most significant salinity changes are located in the warm pool, west of the international date line, including CanESM5 and MPI-ESM1-2-HR. In other models, they are located nearby or east of the international date line, such as CESM, MRI-ESM2-0, and SAM0-UNICON. The intensity of salinity changes is another factor for the model uncertainty, with the weakest in BCC-CSM2-MR and the strongest in CanESM5. In addition, considering the salinity biases in models, this paper compared the SSS changes between CMIP6 and observations and simply corrected the SSS changes in models by subtracting the systematic biases in the climatological salinity (Fig. 4). The results show that SSS changes in models are consistent with observations, and biases have weak impacts on the pattern of salinity changes. Using the multimodel mean could reduce the model uncertainty and biases and increase the reliability of the results.

Fig. 9.
Fig. 9.

The spatial distributions of SSS changes (shading; psu) between years 131–150 and 1–20 for (a)–(o) 15 models and (p) the standard deviation of 15 models.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Previous studies reveal that the SSS changes are similar to the climatological pattern in SSS on global scale, indicating the strengthening of the water cycle (Durack et al. 2012; Helm et al. 2010; Hosoda et al. 2009; Skliris et al. 2014). However, the correlation between SSS changes with climatological SSS is only 0.28 in the tropical Pacific. This weak correlation indicates that the SSS changes do not follow the wet-get-wetter mechanism. The main contribution to salinity decrease comes from the increase in precipitation in the equatorial region, following the warmer-get-wetter mechanism. However, there are significant differences between the SSS changes and rainfall changes (r = 0.41), especially in the tropical western Pacific (Figs. 4a and 4b). Specifically, the SSS changes do not show sandwich structure like rainfall. In addition, there are position shifts between the center of precipitation and SSS changes. In addition to the effect of freshwater flux, these results reveal that other factors, such as ocean dynamic processes, are important for the redistribution of SSS.

Based on the mixed layer salinity budget, this paper investigates the impact of ocean dynamic processes such as ocean horizontal advection and vertical entrainment on the SSS changes (Fig. 10). The results show that the effect of ocean dynamic processes on the salinity change is opposite to that of freshwater flux in the tropical Pacific with high model consistency (Figs. 10b and 10c). Specifically, ocean dynamic processes have negative contributions to the salinity changes in the ITCZ and SPCZ regions and positive contributions in the equatorial central Pacific, which partly offset the contribution from the freshwater flux, leading to the salinity changes being different from the precipitation.

Fig. 10.
Fig. 10.

Spatial distribution of (a) the sum on the right side of MLS budget equation, (b) surface freshwater forcing, (c) salinity horizontal advection, and (d) vertical entrainment. Unit: psu yr−1. Gray stippling indicates high model consistency, where ≥90% of models agree on the sign of change.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

This study further separates the zonal, meridional, and vertical processes to study the role of different ocean dynamic processes in the salinity changes (Fig. 11). The results show that the contributions from the climatological zonal and meridional currents are similar to that from total ocean dynamic processes (Figs. 10c and 11a). In the equatorial central Pacific, the precipitation increasing leads to the salinity decreasing, and the westward climatological zonal current transports the negative salinity anomalies westward, showing a positive contribution to salinity changes, resulting in obvious salinity anomalies in the west of the international day line (Figs. 11c and 12b). A similar effect occurs in the ITCZ and SPCZ regions for the meridional current (Fig. 11d). Due to the divergent meridional current, the negative salinity anomalies are transported to both sides of the equator, which leads to a positive contribution in the equatorial Pacific and a negative contribution in the ITCZ and SPCZ regions on salinity changes, partly offsetting the contribution from freshwater flux, smoothing the salinity changes in the western Pacific.

Fig. 11.
Fig. 11.

The contribution of horizontal advection to salinity changes, (a) the salinity horizontal advection from the mean horizontal currents (uS′ + υS′), (b) the salinity horizontal advection from the anomalies of the horizontal current (u′S + υ′S), (c) the salinity horizontal advection from the mean zonal currents (uS′), and (d) the salinity horizontal advection from the mean meridional currents (υS′). Unit: psu yr−1. Gray stippling indicates high model consistency, where ≥90% of models agree on the sign of change.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Fig. 12.
Fig. 12.

Spatial distribution of (a) SSS mean state (shading; psu) and current anomalies (vectors; m s−1) and (b) SSS anomalies (shading; psu) and current mean state (vectors; m s−1).

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

In addition, vertical entrainment changes impact the salinity changes under global warming. In the tropical Pacific, mixed layer depth (MLD) shoals, especially near the international date line. MLD decreases from 25 to 20 m, shoaling by about 5 m (Fig. 13). Under global warming, SST and precipitation increase, and salinity decrease in the equatorial regions (Fig. 4), which results in seawater density decreasing. As a result, the MLD becomes shallower. This causes less high salinity from the bottom to enter the MLD, decreasing the SSS in the equatorial regions. At the same time, the surface circulation shows a weakening trend, leading to the Ekman upwelling wakening (Fig. 12a). The weakened upwelling brings less high salinity and cold water into the MLD, having a negative contribution to salinity changes in the equatorial regions. Although the contribution of the vertical entrainment is smaller than that of the horizontal advection, the two vertical processes mentioned above play an important role in salinity redistribution.

Fig. 13.
Fig. 13.

(a) Mixed layer depth changes (shading; m) and (b) longitude–depth salinity changes (shading; psu) with mixed layer depth (red line for years 1–20 and black line for years 131–150). Gray stippling indicates high model consistency, where ≥90% of models agree on the sign of change.

Citation: Journal of Climate 35, 18; 10.1175/JCLI-D-21-0973.1

Previous studies suggested that the change of salinity could reveal the water cycle change in response to global warming, following the wet-get-wetter mechanism (Chou and Neelin 2004; Chou et al. 2009; Held and Soden 2006). However, this study shows that the ocean dynamic processes play an important role in the salinity redistribution, leading to a significant difference between SSS and precipitation changes in the tropical Pacific. In addition, it is worth noting that there are still some differences between the spatial pattern of salinity changes and the sum on the right side of the budget equation, such as the ITCZ region and equatorial central and eastern Pacific (Figs. 10a and 4b). These biases may be caused by the model uncertainty and nonlinear processes, including small-scale ocean dynamics that cannot be described in long-term changes, such as the ocean eddies, mixing, and diffusion processes. To better understand global water cycle change, more factors need to be considered to accurately estimate the salinity and water cycle changes in the future.

6. Conclusions with discussion

Using the CMIP6 abrupt-4XCO2 scenario, this study mainly investigates the physical mechanism of rainfall and salinity changes in response to the El Niño–like SST warming pattern and the role of ocean dynamic processes in the salinity changes in the tropical Pacific.

In the tropical Pacific, SST change shows an El Niño–like warming pattern under 4 × CO2 forcing, which impacts the precipitation changes. Precipitation increases in the equatorial Pacific while decreasing in the Maritime Continent, ITCZ, and SPCZ regions. The El Niño–like SST warming triggers the atmospheric circulation weakening and eastward shift. The weakening of the Walker circulation leads to a precipitation decrease in the Maritime Continent, which partly offsets the precipitation changes caused by the thermodynamic processes (e.g., an increase in specific humidity). The eastward shift of the Walker circulation causes precipitation to increase in the equatorial Pacific. On the other hand, the El Niño–like warming pattern changes the meridional SST gradient, promoting the convergence of meridional winds, which leads to precipitation increase in the equatorial Pacific while precipitation decrease in the ITCZ and SPCZ regions, following the “warmer-get-wetter” mechanism.

The SSS becomes fresher in the tropical Pacific, similar to the climatological pattern in SSS, indicating the strengthening of the water cycle. However, there is a position shift between the salinity and precipitation changes. The contributions of ocean dynamic processes, especially the climatological horizontal advection, partly offset the contribution of the freshwater flux on the salinity change, leading to the salinity changes similar to the climatological SSS. In addition, a shallower MLD, induced by increased SST, decreased salinity, and weakening Ekman upwelling, brings less high-salinity water into the MLD in the equatorial regions, which also plays an important role in salinity redistribution.

There are still some problems needed to answer in the future. We only give the qualitative description and do not quantify the contributions of the ocean dynamic process to the SSS changes. At the same time, smaller-scale processes (e.g., the effects of mixing and mesoscale eddies) could change the salinity pattern, which needs to be assessed. In addition, three-dimensional salinity changes are worthy of studies to understand better the relationship between the salinity and the water cycle in the future.

It is worth noting that significant model uncertainty and model biases still exist in CMIP6 models. IPCC AR6 reports that the model uncertainty is the most influential factor in limiting the estimation of water cycle changes, which is associated with the representation of key processes, such as atmospheric convection and aerosol microphysics, that are not entirely resolved in models. Model biases, including an excessive westward extension of equatorial cold tongue, surface easterly wind anomalies in equatorial Pacific, weaker equatorial western Pacific precipitation, and double ITCZ, are another important factor in the accurate assessment of water cycle and salinity changes. With the in-depth understanding of physical processes and the increased horizontal resolution in modes, these biases are expected to be solved in the future.

Acknowledgments.

We acknowledge the Earth System Grid Federation (ESGF) for providing the CMIP6 products (https://esgf-node.llnl.gov/projects/cmip6/). This work is supported by the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0303, GML2019ZD0302), the National Natural Science Foundation of China (42090042), and the Chinese Academy of Sciences (183311KYSB20200015, 133244KYSB20190031, ISEE2021PY02, and ISEE2021ZD01).

Data availability statement.

CMIP6 outputs used in this study are downloaded from the ESGF nodes (https://esgf-node.llnl.gov/search/cmip6/). EN4 datasets are downloaded from the Met Office Hadley Centre observations datasets (https://www.metoffice.gov.uk/hadobs/en4/). NCEP datasets are provided by the NOAA Physical Sciences Laboratory (PSL) (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html). The GPCP datasets are also downloaded from PSL (https://psl.noaa.gov/data/gridded/data.gpcp.html).

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