Tropical Atlantic Oceanic Variability in the CCSM4

Ernesto Muñoz

New Mexico Consortium

Los Alamos, NM

Wilbert Weijer

Los Alamos National Laboratory and New Mexico Consortium

Los Alamos, NM

Ilana Wainer

University of Sao Paulo

Sao Paulo, Brazil

Semyon Grodsky

University of Maryland

College Park, MD

Marlos Goes

Cooperative Institute for Marine and Atmospheric Studies

University of Miami and NOAA-AOML

Miami, FL

Susan C. Bates

National Center for Atmospheric Research

Boulder, CO

Submission to: Journal of Climate, Special Collection on CCSM4

Date of submission: 19 May 2011

Corresponding author address:

Ernesto Muñoz

New Mexico Consortium

4200 West Jemez Road, Suite 301

Los Alamos, NM 87501

E-mail:

Abstract:

In this study we analyze important aspects of the tropical Atlantic Ocean from the new simulations of the 4th version of the NSF-DOE coupled climate model, the Community Climate System Model (CCSM4). The data used in this study is from several different simulations, among them a set of five 20th-century simulations with different initial conditions, but similar radiative forcing. Among the features analyzed in this study are: the structure of the Atlantic warm pools; the main modes of sea surface temperature (SST) variability in the tropical South and North Atlantic; the variability of heat storage in the Benguela region; the density-dependent circulation from the subtropics to the tropics; and differences between the model simulations and the observations in the tropical Atlantic. The results indicate that some of the biases of the tropical Atlantic have been reduced in CCSM4 compared to the previous version of the CCSM. The ensemble mean and variability of the Tropical North Atlantic Warm Pool in the CCSM4 is realistic when compared to observations for the period between 1980 and 2005. The variability of SSTs in the tropical Atlantic is well represented in CCSM4 although the leading EOF in CCSM4 shows more homogeneous warming than the leading EOF in observations. A heat budget analysis of the Benguela region indicates that the variability of SSTs is dominated by vertical advection. The subtropical waters in the coupled configuration reach the Equator mainly from the South Atlantic, whereas in an ocean-only simulation there are also contributions from the North Atlantic.

1. Introduction

The tropical Atlantic is an important region in the Earth’s coupled climate system. Understanding the variability of the tropical Atlantic is not only important for the communities of tropical America and tropical Africa, but is also important for other remote regions and for the climate system in general. A few recent reports summarize the advances in the understanding of the tropical Atlantic climate and its variability (e.g., Hurrell et al. 2006; Xie and Carton, 2004; Garzoli and Servain, 2003; Visbeck et al. 2001). To date, the tropical Atlantic has been challenging to model adequately by coupled climate models. In this study the following main aspects of the tropical Atlantic Ocean are analyzed from the 4th version of the NSF-DOE Community Climate System Model (CCSM4).

a. The Atlantic Warm Pools

The Atlantic warm pool (AWP) has been defined as that region of the tropical Atlantic Ocean with temperatures greater than 28.5°C (Wang and Enfield, 2003). The AWP has a component in the northwestern tropical Atlantic spanning the Gulf of Mexico and the Caribbean Sea (i.e., the Intra-Americas Sea) that peaks during boreal summer and early fall. During boreal winter and spring the waters of the tropical South Atlantic reach temperatures greater than 28.5°C also forming a warm pool.

Beyond its surface manifestation and extent, the Atlantic Warm Pools (AWPs) in the Tropical North Atlantic (TNA) and the Tropical South Atlantic (TSA) have a vertical profile that is important with respect to the heat content of the upper layer of the ocean. The heat content in the AWP-TNA is also available for tropical storms and hurricanes that travel through that region (Wang et al. 2006). Furthermore, the earlier CCM3 modeling study of Saravanan and Chang (2000) regarding the Caribbean sea surface temperatures (SSTs) already pointed to the Caribbean as critical in the teleconnections with the tropical Pacific. That is to say, Saravanan and Chang (2000) found that the Caribbean heat sources can affect the Pacific through an upper-level Gill-type circulation. This and other impacts of the AWP-TNA were documented by Wang et al. (2008) from a model.

b. Leading modes of Tropical Atlantic Variability

Anomalous SSTs in the tropical Atlantic vary on a wide range of time scales. On multidecadal timescales, the Atlantic Multidecadal Oscillation (Enfield et al., 2001) is mostly confined to the North Atlantic, and possibly reflects changes in the strength of the Atlantic Meridional Overturning Circulation (Muñoz et al., 2011). At decadal timescales, the out-of-phase variations of SST in the northern and southern tropical Atlantic are self-sustained and driven by the wind-evaporation-SST feedback in the trade winds (Carton et al., 1996; Chang et al., 1997), sometimes referred to as the inter-hemispheric mode. At shorter timescales remote impacts of the El Niño-Southern Oscillation (ENSO; Enfield and Mayer, 1997) and the North Atlantic Oscillation (Czaja et al., 2002) produce different SST responses in the northern and southern tropical sectors and thus contribute to the observed lack of coherence between SST variations in the two regions.

The tropical Atlantic variability (TAV) has been observed to have two main modes of variability that are predominant at different times of the year (Servain et al. 1990; Servain et al. 2003). One of the modes of variability is the so-called meridional mode or interhemispheric mode and is usually observed in the boreal spring (Servain et al. 1998). The meridional mode is characterized by a meridional gradient of SST anomalies from one subtropical region to its counterpart in the other hemisphere, and a pattern of surface wind anomalies from the colder subtropics to the warmer subtropics (Nobre and Shukla, 1996). Another mode of variability is the so-called zonal mode or Atlantic Niño and is predominant in the boreal summer (Carton and Huang, 1994; Zebiak, 1993; Shannon et al. 1986). Previous studies have analyzed these modes and the dynamics and thermodynamics that explain their variability (Bates, 2010; Huang and Shukla, 2005; Florenchie et al. 2004; Chang et al. 1997; Carton et al. 1996; Shannon et al. 1987).

c. The Benguela region

Periodic changes of sea surface temperature (SST) in the northern and southern tropical Atlantic meridionally displace the Intertropical Convergence Zone (ITCZ) and the rainfall associated with it, impacting precipitation over northeastern Brazil (see e.g. Xie and Carton, 2004 and references therein). Observation-based analyses of SST variability in the tropical Atlantic indicate that the standard deviation of anomalous[1] SST is strongest in areas adjacent to the western coast of Africa and reaches a maximum in the Angola-Benguela frontal zone (referred to as the Benguela region in this paper; see e.g. Florenchie et al., 2003). The enhanced variability of SST in the Benguela region suggests that this region may contribute significantly to the meridional gradient of tropical Atlantic SST and thus plays a role in tropical Atlantic variability.

In the Benguela region significant interannual variations of SST (area average of up to 3°C, e.g. Florenchie et al., 2003) are superimposed on lower-frequency variations. Observations and model simulations of Florenchie et al. (2003) suggest a link between the Benguela warm events and weakening of the Equatorial winds 1 to 2 months in advance. This remotely impacts the Benguela region via Kelvin waves propagating eastward along the Equator and further south along the coast (Zebiak, 1993). Impacts of local versus distant winds on the Benguela SST have been addressed in a number of recent reports (Richter et al. 2010; Rouault, 2010). In particular, Richter et al. (2010) has demonstrated based on observations and model simulations that impact of local upwelling on Benguela SST is comparable to the remote impact of the Equatorial winds.

d. Density-dependent subtropical source waters

The regions of the Benguela Niño, the Americas Warm Pool, and the equator are sourced by subtropical water. Aside from local air-sea interactions and wave dynamics, the water in the regions indicated above is affected by water from remote locations in the subtropics. The Caribbean Sea, for example, is sourced by waters from both the tropical North Atlantic and the tropical South Atlantic (Kilbourne et al. 2007). The fate of the subtropical waters of the Atlantic Ocean is therefore important to understand. In fact, there is still much to be learned about the causes of variability of the Atlantic south-north pathways between different models.

Some of the Atlantic subtropical water ventilates the equator via Subtropical-Tropical Cells (STCs). The STCs are shallow overturning cells, mostly confined to the upper 500 meters, associated with the equatorial upwelling and a return flow. The ventilation process associated with STCs in the tropical Atlantic has been discussed by Wainer et al. (2006), Kroger et al. (2005), Zhang et al. (2003), Molinari et al. (2003), Snowden and Molinari (2003), and others. Once the subtropical water reaches the equator it travels eastward reaching the eastern boundary and the region of the Benguela Niño. Yet, there is other subtropical water from the South Atlantic that crosses the equator northward, ultimately reaching the Caribbean Sea and other regions of the tropical North Atlantic. The Intra-Americas Sea is also sourced by subtropical water from the North Atlantic.

d. Organization of the manuscript

The recent availability of the CCSM4 provides an opportunity to assess the status of the simulation of the tropical Atlantic by one of the leading coupled climate models. Also, the Community Earth System Model (CESM) (of which the CCSM4 is a subset) will be used as part of the next phase of the Coupled Model Intercomparison Project (CMIP5); is therefore important to understand the CCSM4 simulation of the tropical Atlantic Ocean.

Section 2 of this study introduces the general improvements and biases in the tropical Atlantic of the CCSM4 surface fields compared to observations and those of CCSM3 (the previous CCSM version). Next, an analysis of the structure of the Atlantic Warm Pools (in the north and south tropical Atlantic) is presented based on a suite of ensemble simulations. Additionally, the main modes of sea surface temperature (SST) variability in the tropical Atlantic are compared against those from observations. The variability of the tropical South Atlantic, in specific the Benguela region, is further analyzed based on the heat storage. Finally, the density-dependent flow from the subtropics to the tropics is analyzed through the use of virtual floats. Summaries and discussion are presented as the final section of the manuscript.

2. Mean Biases in the Tropical Atlantic Ocean

Among the known biases of coupled models in the tropical Atlantic region are: a warm bias in the tropical southeastern Atlantic, a barrier layer thicker than observed, and relaxed zonal winds along the equator related to weaker precipitation over the Amazon region (Richter et al. 2011; Wahl et al. 2011; Richter and Xie, 2008; Breugem et al. 2008; Chang et al. 2007). However, as discussed below, the CCSM4 version shows some improvement with respect to CCSM3 regarding some of these features. In this section we compare the ensemble mean of five 20th century (20C) CCSM4 simulations (see Gent et al. (2011)), from 1986 to 2005 to observations and to a CCSM3 20C ensemble mean.

In the tropical Atlantic (Figs. 1a,c) a shift to warmer surface ocean temperatures is noted in the CCSM4 versus CCSM3 (Danabasoglu et al, 2011). The mean values from 40°S to 40°N of the tropical Atlantic biases (shown in Fig. 1) are -0.53°C for CCSM3 and 0.61°C for CCSM4, excluding the Mediterranean Sea and Pacific. These indicate that the overall mean of the SST bias has not changed in magnitude but has flipped from an overall negative bias in CCSM3 to an overall positive bias in CCSM4. This is a trend that is also seen globally (Danabasoglu et al., 2011). The root mean square (RMS) error of these biases over the same region does show improvement with a value of 1.52°C for CCSM3 and 1.29°C for CCSM4.

Particular regions show great improvement in SST bias. Of importance to the investigations of this paper are the large improvements in the cold bias centered at 20°N as well as in the Caribbean Sea and Gulf of Mexico. The warm bias of the upwelling regions is worse in CCSM4 compared to CCSM3. This too is a global feature, as the SST warm bias in CCSM3 in all the eastern basin upwelling regions has worsened in CCSM4. More details on this particular feature of the CCSM are discussed in Large and Danabasoglu (2006).

Sea surface salinity (SSS) in the tropical Atlantic has improved in the CCSM4 (Figs. 1b,d). The mean of the SSS biases, as calculated above, is -0.517 g/kg for CCSM3 and -0.148 g/kg for CCSM4 indicating an overall reduction of fresh biases. The RMS error of these biases also displays improvement with a value of 1.080 g/kg for CCSM3 and 0.775 g/kg for CCSM4. Large improvements in the fresh bias are apparent in the northern and southern tropics from approximately 20°S to the equator and in the eastern North Atlantic from approximately 15°N-30°N. This improvement is most likely due to a reduction of the positive precipitation bias in this region causing a reduction in the input of freshwater to the ocean (Bates et al. 2011, this issue). Salinity bias improvements are also noted in the south Caribbean Sea; however, the northern portion of the Gulf of Mexico now has a larger saline bias in CCSM4 over CCSM3.

The biases in the mean state of zonal (TAUX) and meridional (TAUY) wind stress for CCSM3 and CCSM4 compared to observations are provided in Fig. 2. As will be shown later, wind stress is important to processes controlling heat content changes in the eastern equatorial Atlantic as well as to changes in the volume of the Atlantic warm pools. It is therefore encouraging to see (in Figs. 2c and 2e) the large improvements made in the transition to CCSM4 from CCSM3 in TAUX in the northern Caribbean Sea. The TAUX in the Caribbean Sea is related to the Caribbean low-level jet (Mo et al. 2005; Muñoz et al. 2008). Both CCSM3 and CCSM4 display weakened easterlies along the equator compared to observations; however, this bias has been greatly reduced in CCSM4. Also apparent from Fig. 2 (panels c and e) is a reduction in the overly strong easterlies in the north tropical Atlantic near the coast of Africa.

Notable improvements in TAUY (Fig. 2, panels d and f) include a reduction of overly strong wind stress in the north tropical Atlantic, in particular near the coast of Africa, as well as improvement in the weaker than observed northerly wind stress near the coast of Angola and in the Gulf of Guinea. This weak northerly flow contributes to weaker upwelling in this region and therefore to the warm SST bias mentioned above, though Large and Danabasoglu (2006) cite a number of oceanic and atmospheric processes in addition to weak upwelling that cause these eastern basin SST biases.

3. The Atlantic Warm Pools

a. Data and Methods

In this section the differences in the simulation of the AWPs by CCSM4 are evaluated against those estimated from observations. The data used in this section is from an ensemble of five 20th century (20C) CCSM4 simulations, from which the last few decades of data (i.e., from 1980 to 2005) are used. Complete descriptions of these simulations are provided by Gent et al. (2011, this issue).

Two observational data sets were used for comparison. One observational data set is the World Ocean Atlas 2009 (WOA09) climatological fields (Locarnini et al. 2010; Levitus et al. 1998) with mean temperature data for the twelve calendar months. These WOA09 monthly climatological fields are based on the period from the year 1773 to the year 2008. Also used is the observational data set developed by Ishii et al (2006) with monthly temperature data interpolated to a 1x1 degree grid. Both of these observational data sets have the same horizontal 1x1 degree grid, and the same vertical levels, with data at the surface, 10m, 20m, 30m, 50m, 75m, 100m, 125m, 150m, 200m, 250m, and at 100m intervals between 300m and 700m. (The depth of the 28.5°C isotherm does not exceed 185 meters at any time in the period analyzed from these observational products.)

An advantage of the observational product from Ishii et al (2006) (from now on Ishii) is that it provides monthly data for the recent period thereby allowing for the calculation of means based on different periods (e.g., from 1980 to 2005), whereas the Levitus climatology provides 12 monthly climatologies based on the period 1773-2008 covering more than a couple of centuries. In this section the averages from the Ishii product were computed based on the period from the year 1980 to the year 2005. That is to say, the means computed from the Ishii et al (2006) product correspond in time to the means computed from the ensemble of CCSM4 simulations, thereby allowing a fair comparison.

The CCSM4 temperature data is provided in a non-equidistant grid with horizontal resolution of nominally 1 degree (and finer resolution in the Tropics). The vertical resolution of the model is finer than that of the observational data sets. To do a consistent comparison of the depth of the 28.5°C isotherm (Z28.5), the model data was interpolated to the vertical levels of the observations before calculating the Z28.5 depth. Once the Z28.5 depth was calculated, the result was interpolated to the horizontal grid of the observational products at each month. These monthly values were used to calculate the long-term averages.

b. Results

Figure 3 shows the month of the calendar year when the 28.5°C isotherm is deepest in the long-term mean. Although both the Ishii and Levitus (Figs. 3a-b) are products derived from observations, there is a clear distinction in much of the central tropical Atlantic. The Ishii Z28.5 depth extends across much of the tropical Atlantic throughout the year. The Levitus monthly means do not have a 28.5°C isotherm present in many areas of the tropical Atlantic. The main difference in these results most likely stems from the period covered by each of the Z28.5 estimates. As indicated before, the Ishii Z28.5 values were computed based on the period from 1980 to 2005, whereas the Levitus climatological fields are based on available data in the period from the year 1773 to 2008.

When the CCSM4 ensemble mean is compared to the Levitus and the Ishii data sets, a better agreement is obtained between CCSM4 and Ishii. The CCSM4 Z28.5 extends throughout the tropical South Atlantic similar to the Ishii Z28.5 (Fig. 4). Also, in the tropical North Atlantic the CCSM4 produces a Z28.5 depth in the Intra-Americas Sea (i.e., Caribbean Sea and Gulf of Mexico) and across the basin at about 10°N similar to the Ishii Z28.5 (Fig. 5).