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    Multivariate ENSO Index

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    ISCCP/Hartmann cloud classification

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    DJF C from ERBE for the study average. The dashed vertical lines indicate the boundaries of the Pacific basin (120°E–70°W). White regions correspond to no available data

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    DJF interannual variations of the spatially averaged C from ERBE

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    DJF C from ERBE for (a) the El Niño and (b) the La Niña. White regions correspond to no available data

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    DJF cloud amount anomaly from ISCCP for middle-thick cloud: (a) the El Niño, (b) the La Niña; and for high-thin cloud: (c) the El Niño, (d) the La Niña. White regions correspond to no available data

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    DJF TOA net radiation from ERBE for (a) the study period. TOA net radiation anomaly for: (b) the El Niño and (c) the La Niña

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    DJF interannual variations of the spatially averaged divergence of atmospheric energy from ERA

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    DJF interannual variations of the zonally integrated divergence of atmospheric energy from ERA

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    DJF interannual variations of the meridional transport by the mean meridional circulation from ERA for (a) s and (b) LH

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    DJF interannual variations of the meridional transport by stationary eddies from ERA for (a) s and (b) LH

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    DJF interannual variations of the meridional transport by transient eddies from ERA for (a) s and (b) LH

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Interannual Variability of Cloud Forcing and Meridional Energy Transport for the Northern Hemisphere Winter from 1984 to 1990

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  • 1 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
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Abstract

Broadband radiative flux data from the Earth Radiation Budget Experiment (ERBE) are used to document the interannual variability of net cloud forcing over the lifetime of the ERBE scanner instruments. The study focuses on the high variability observed in the Pacific basin during the Northern Hemisphere winter from 1984 to 1990. This period captures the El Niño season of 1986/87 and the La Niña season of 1988/89, with an average state biased toward La Niña–type conditions. Clouds are found to cool the Pacific basin by approximately 23 W m−2 over the study period. Interannual variations of net cloud forcing vary by less than 5%, with a decrease of cloud cooling during the El Niño and an increase during the La Niña.

A key aspect of this study is the concurrent analysis of cloud type and amount information from the International Satellite Cloud Climatology Project (ISCCP). It demonstrates that the variability of middle-thick and high-thin clouds is integral to the observed changes in net cloud forcing. A subsequent analysis of ERBE net radiation measurements reveals that the geographic redistribution of cloudiness observed in the ISCCP data results in an increase of the meridional energy gradient during the El Niño and a decrease during the La Niña.

ECMWF reanalyses data are used to document and discuss the interannual variability of the meridional transport of atmospheric energy and the atmospheric circulation. During the 1986/87 El Niño, it is found that the transport of atmospheric energy from the Tropics and subtropics to higher latitudes increases by approximately 6% from the study average. Conversely, the transport decreases by about 2% during the 1988/89 La Niña. An investigation of the variability of the structure and the strength of the meridional energy transport by the mean meridional circulation, stationary eddies, and transient eddies is then used to diagnose changes to the atmospheric circulation.

Corresponding author address: Richard W. Moore, Department of Atmospheric Science, Colorado State University, Foothills Campus, West Laporte Avenue, Fort Collins, CO 80523-1375. Email: moore@cira.colostate.edu

Abstract

Broadband radiative flux data from the Earth Radiation Budget Experiment (ERBE) are used to document the interannual variability of net cloud forcing over the lifetime of the ERBE scanner instruments. The study focuses on the high variability observed in the Pacific basin during the Northern Hemisphere winter from 1984 to 1990. This period captures the El Niño season of 1986/87 and the La Niña season of 1988/89, with an average state biased toward La Niña–type conditions. Clouds are found to cool the Pacific basin by approximately 23 W m−2 over the study period. Interannual variations of net cloud forcing vary by less than 5%, with a decrease of cloud cooling during the El Niño and an increase during the La Niña.

A key aspect of this study is the concurrent analysis of cloud type and amount information from the International Satellite Cloud Climatology Project (ISCCP). It demonstrates that the variability of middle-thick and high-thin clouds is integral to the observed changes in net cloud forcing. A subsequent analysis of ERBE net radiation measurements reveals that the geographic redistribution of cloudiness observed in the ISCCP data results in an increase of the meridional energy gradient during the El Niño and a decrease during the La Niña.

ECMWF reanalyses data are used to document and discuss the interannual variability of the meridional transport of atmospheric energy and the atmospheric circulation. During the 1986/87 El Niño, it is found that the transport of atmospheric energy from the Tropics and subtropics to higher latitudes increases by approximately 6% from the study average. Conversely, the transport decreases by about 2% during the 1988/89 La Niña. An investigation of the variability of the structure and the strength of the meridional energy transport by the mean meridional circulation, stationary eddies, and transient eddies is then used to diagnose changes to the atmospheric circulation.

Corresponding author address: Richard W. Moore, Department of Atmospheric Science, Colorado State University, Foothills Campus, West Laporte Avenue, Fort Collins, CO 80523-1375. Email: moore@cira.colostate.edu

1. Introduction

Satellite-based observations of cloud–radiative flux interactions have been intensely studied over the past 25 years. Many different methods incorporating data from various satellite instruments have been used to quantify cloud forcing (Arking 1991). There is agreement that clouds cool the earth, but estimates of the magnitude of cloud cooling vary depending on the method and dataset examined. Cloud forcing exhibits significant seasonal and geographic variability (Harrison et al. 1990), in part due to the fact that cloud effects are different for different cloud regimes (Hartmann and Short 1980). Interannual variability of the top of the atmosphere (TOA) radiative fluxes has also been observed (Heddinghaus and Krueger 1981; Liebmann and Hartmann 1982; Ardanuy and Kyle 1986; Smith and Smith 1987; and Sohn and Smith 1992a,b).

Year-to-year changes of cloud amount can contribute to fluctuations of the global climate system. Sohn and Smith (1992a) asserted that the cloud variability induced by an El Niño can modify the TOA energy balance. In a later study, Sun and Trenberth (1998) used a combination of the Earth Radiation Budget Experiment (ERBE), National Centers for Environmental Prediction reanalysis, and ocean data to examine the heat removal from the equatorial Pacific during the El Niño season of 1986/87. They found significant modifications of the tropical atmospheric circulation, resulting in marked increases in the poleward transport of atmospheric energy from the Tropics, with respect to non–El Niño years.

The goals of this study are to document and analyze the interannual variability of cloud–radiative flux interactions and concurrent meridional energy transports in the Pacific basin (120°E–70°W) for the Northern Hemisphere winter [December–February (DJF)] from 1984 to 1990. The specific study period and area were chosen for the availability of ERBE scanner data and the significant interannual variability.

The largest year-to-year changes in the global climate system are associated with the El Niño–Southern Oscillation (ENSO) phenomena (Climate Diagnostics Center 2000). To show the activity of ENSO during the study period, a time series of the Multivariate ENSO Index (MEI) is presented in Fig. 1. The MEI can be thought of as a weighted average of the main ENSO features (Climate Diagnostics Center 2000). Figure 1 clearly identifies the 1986/87 El Niño and the 1988/89 La Niña (hereinafter referred to as the El Niño and the La Niña, respectively). Another noteworthy feature is the slight bias toward La Niña–type conditions over the 6-yr study period.

In section 2, ERBE broadband radiative flux data are used to investigate the interannual variability of the TOA energy balance, specifically examining the parameters of net cloud forcing and the meridional gradient of energy. ISCCP cloud amount and type information is analyzed to help to explain the measured variability. ECMWF reanalyses (ERA) data are used to document and interpret the response of the atmospheric circulation to the variable forcing (section 3). In section 4, a discussion of the study findings is presented.

2. Interannual variability of cloud–radiative effects at the TOA

a. Data and analysis techniques

1) ERBE

The satellite system utilized in the ERBE program is well designed for the accurate measurement of cloud–radiative flux interactions. The three-satellite mission was a significant improvement over previous attempts to measure the Earth Radiation Budget due to advances in instrument design and calibration, in the algorithms used to convert radiances to flux density (Smith et al. 1986), in sampling (Harrison et al. 1988), and in the time–space-averaging algorithm (Brooks et al. 1986). A discussion of ERBE instruments, data processing, and validation can be found in Barkstrom et al. (1989).

The current study incorporates both clear- (cloud free) and all-sky TOA longwave (0.5–50 μm) and TOA shortwave (0.2–5 μm) radiation data obtained by the scanner instruments. Total solar energy information is used to calculate the TOA net radiation. All data are binned into an equal-angle, 2.5° × 2.5° projection.

(i) Cloud forcing
Net cloud forcing C is defined as follows (Ramanathan et al. 1989),
CRclearRall
where Rclear is the clear-sky, and Rall is the all-sky, daily ERBE measurement of the TOA net radiative flux. Because of the temporal and spatial sampling of ERBE and the fact that cloudiness is quite persistent over certain regions of the globe, it is impossible to calculate cloud forcing on a daily basis for many regions. To solve this problem, a value of C is calculated for each grid box and day with an all-sky observation. If there is no corresponding daily, clear-sky observation, a monthly averaged clear-sky value is used for Rclear in (1). All valid daily measurements of C are then averaged over the Northern Hemisphere winter months (DJF) for the years 1984–90. For a discussion of the uncertainties in ERBE-derived cloud forcing calculations, see Harrison et al. (1990).

Over a limited number of regions, a monthly averaged clear-sky measurement is not available. In this case, the region is characterized by “no available data” and the information is not included in the averaging calculation. This fact introduces an uncertainty in the averaged measurements; however, the problem is a systematic one for most regions. As a result, the effect on the interannual variability signal is minimized.

(ii) Meridional energy gradient

In an attempt to quantify the TOA meridional energy gradient over the Pacific basin and the globe, a surface area-weighted sum of the deficit and surplus of energy is calculated from ERBE TOA net radiation measurements. For each grid box, the TOA net radiation value is weighted by its surface area. If the value is positive, it is added to the surplus summation. If negative, it is added to the deficit summation. The meridional energy gradient can be thought of as the difference between the positive radiative surplus and the negative radiative deficit, if the majority of the variability is not due to zonal variability.

2) International Satellite Cloud Climatology Project (ISCCP)

ISCCP, Stage D1 cloud type and amount data are used to explain the calculated interannual variability of the TOA energy balance. Cloud types are distinguished by their cloud-top pressure and optical thickness values. In order to measure these parameters, the ISCCP algorithms use both infrared and visible satellite radiance data. It is known that cloud identification can be troublesome over the highly reflective surfaces of ice and snow (Rossow and Garder 1993). Due to the dependence on visible data, the cloud measurements used in the present study are not available northward of approximately 67°N, thereby minimizing the cloud identification problem.

For both consistency and clarity, the cloud classification devised by Hartmann et al. (1992; hereafter H92) is used in this study (Fig. 2). This rather simplistic cloud classification system is nevertheless appropriate because it allows one to easily describe a relationship between cloud type and radiation balance that is both intuitive and quantitative (H92).

H92 defined the sensitivity of the TOA net radiative flux to a cloud type as the net forcing from a particular cloud type divided by the fraction of that cloud type present. To calculate the net forcing for each cloud type, H92 used a multiple linear regression technique to relate the ERBE radiation budget data to the ISCCP cloud data for the 1-yr period from March 1985 to February 1986. The same procedure is used in this study to derive the sensitivity over the 6-yr study period.

b. Results

1) Cloud Forcing

(i) ERBE measurements

Figure 3 shows the spatial distribution of the study average net cloud forcing. Features to note are the regions of positive cloud forcing found adjacent to areas of deep tropical convection, over the northern midlatitude storm track and Antarctica, and the region of large negative cloud forcing found over the southern midlatitude storm track. A spatial average demonstrates that clouds cool the Pacific basin by 23 W m−2 over the 6-yr period.

The interannual variability of the spatially averaged C over the Pacific basin is plotted in Fig. 4. The results indicate a variability of less than 5% from the study average, with the largest deviations being a decrease and an increase of cloud cooling during the El Niño and the La Niña, respectively. To assist in an in-depth examination of these two seasons, Fig. 5 shows the spatial distribution of C, and Table 1 lists the globally and Pacific basin–averaged values for the El Niño, the La Niña, and the study period. The seasonal plots in Fig. 5 appear quite similar, yet there is significant geographic variability. Changes are most apparent over the equatorial Pacific and the northern high latitudes, where cloud cooling decreases and cloud warming increases, respectively, during the El Niño.

(ii) Cloud variability and cloud forcing

Table 2 lists the spatially averaged cloud amounts for the two seasons and the spatially averaged cloud amounts and sensitivity for the study period. The total cloud amount is observed to increase during the El Niño and decrease during the La Niña. Since the overall effect of clouds is to cool the earth, one might expect a corresponding increase and decrease of cloud cooling for the two regimes. However, the opposite is observed (Table 1), emphasizing that it is the variability of distinct cloud types that ultimately determines the magnitude of cloud cooling. This is the case because different cloud types have different effects on the TOA net radiative flux. The overall effect of a cloud on the TOA net radiation depends on cloud parameters such as the cloud height, vertical extent, and microphysical properties. It is also dependent on the geographic location of the cloud due to the variable solar angle and intensity.

For the 6-yr period from 1984 to 1990, the variability of both middle-thick and high-thin clouds (Fig. 6) is found to be most responsible for the measured interannual variability of C. While the spatially averaged amount of middle-thick clouds is quite small, the TOA net radiation is greatly reduced in the presence of this cloud type, as indicated by the large absolute magnitude of sensitivity (Table 2). At northern high latitudes, where middle-thick clouds are most prevalent, a large decrease is observed during the El Niño. In contrast, the presence of high-thin clouds has little effect on the TOA net radiation. During the El Niño, a drastic increase of these clouds is observed over the tropical Pacific. Since these clouds obscure cloud types that, on average, create a negative net radiation anomaly at the TOA, the result is a decrease in cloud cooling. The opposite trends in cloud variability are observed during the La Niña. The overall effect of the measured cloud variability is to decrease the magnitude of cloud cooling during the El Niño and increase the magnitude during the La Niña.

2) Meridional energy gradient

(i) ERBE measurements

Figure 7 shows the spatial distribution of the study period TOA net radiative flux (Fig. 7a), and the anomalous distribution for the El Niño (Fig. 7b) and the La Niña (Fig. 7c). During the Northern Hemisphere winter, the TOA net radiation is negative (energy deficit) to the north and positive (energy surplus) to the south of approximately 15°N (with the exception of the ice-covered surfaces of the southern high latitudes). However, on an interannual timescale (Figs. 7b,c), the numerous regions of positive and negative anomalies make it difficult to understand the effect of the ENSO phenomenon on the TOA energy balance. In an attempt to quantify this effect, the meridional energy gradient is calculated.

The results reveal an increase of the meridional energy gradient during the El Niño and a decrease during the La Niña, with respect to the study period (Table 3). During the El Niño, the trend is for a larger energy deficit northward of 15°N and a larger energy surplus southward. The opposite is measured during the La Niña.

These findings are significant because they indicate an alteration of the energy balance at the TOA. A change in the meridional energy gradient implies a modification to the magnitude of poleward energy transport. This issue is addressed in section 3.

(ii) Cloud variability and the meridional energy gradient

Many of the specific features of Figs. 7b,c are a product of interannual cloud variability. In the tropical Pacific, the anomalous distribution of the TOA net radiation is directly related to the ENSO forcing. During the El Niño, there is an increase of high-thick clouds across the equatorial Pacific. These high-thick clouds decrease the TOA net radiation, resulting in the negative anomaly that extends across the equatorial Pacific, with an exception at approximately 160°–140°W. The high-thin clouds discussed in the previous section (mainly cirrus anvils associated with deep convection) create the belt of positive anomalies to the north. Surrounding the region of increased deep convection are areas of intensified subsidence. The stronger-than-average sinking motion inhibits the formation of the high- and midlevel thin clouds that are normally present, while low-level clouds still form below the induced inversion. The overall effect observed at the TOA is an increase in low-level cloudiness at the expense of high- and middle-thin clouds. Since the TOA net radiation is reduced by the presence of low clouds to a greater degree than by high- and middle-thin clouds, a negative net anomaly is measured.

During the La Niña, the region of deep convection retreats to the western equatorial Pacific and extends to the southeast. The same analysis as above can be used to illustrate the connection between the atmospheric circulation, the distribution of cloudiness and the TOA net radiative anomaly in the equatorial Pacific. Negative net radiative anomalies are associated with the deep convective clouds and regions of increased subsidence, while positive anomalies are measured over regions of increased high-thin clouds.

Over the northern mid- to high latitudes, the anomalous distribution is closely linked to the variability of the mean position of the midlatitude storm track. El Niño episodes are characterized by a mean storm track position that is more zonally uniform and shifted toward the equator (Shabbar et al. 1997). In the winter hemisphere, the clouds associated with the storm track increase the net radiation measured at the TOA, creating a positive net radiative anomaly.

During La Niña episodes, the mean position of the storm track exhibits significant spatial variability. It is often observed to split as a result of blocking high pressure systems that occur in the eastern North Pacific. In comparison with both average and El Niño conditions, the mean storm track position and its associated positive TOA net anomaly shifts to the north. In addition, the anomalous high pressure in the eastern North Pacific is associated with intensified subsidence and increased low-level cloudiness, a fact confirmed by ISCCP data. The increase in low clouds is responsible for the negative TOA net anomaly off the western coasts of Canada and the United States.

3. Meridional energy transport

The role of the general circulation is to reduce the meridional energy gradient that is created by the geographic inhomogeneity of net radiative forces. This is accomplished by both oceanic and atmospheric energy transports. The oceanic component of the meridional energy transport is difficult to measure directly due to the lack of suitable data, although past studies have estimated it to be approximately 40% of the total required transport (Vonder Haar and Oort 1973; Carissimo et al. 1985). While this number is of significant magnitude, the present study focuses on the atmospheric component of meridional energy transport.

a. Data and analysis techniques

ERA data are analyzed to investigate the atmospheric response to interannual variations of the TOA energy balance. A description of the dataset can be found in Gibson et al. (1997).

The climate diagnostics group at the National Center for Atmospheric Research used the ERA dataset to compute the vertically integrated divergence of atmospheric energy. The procedure included a correction for the mass imbalance that occurs as a result of interpolating from model to pressure levels. Details concerning these data are available in Trenberth et al. (2001a), while information regarding the quality of the reanalyses data can be found in Trenberth et al. (2001b).

In addition to these preprocessed data, ERA pressure level data are used to calculate vertically integrated transports of energy. For this portion of the study, no correction was made for the mass imbalance. While these calculations are inherently less accurate than those that incorporate a correction, similar interannual variability is observed, with respect to the mass corrected data. In addition, the shape and the magnitude of the total and component transport curves compare well with past studies (Masuda 1988, hereinafter M88; Michaud and Derome 1991; Kann et al. 1994). Because of this qualitative agreement with previous work, we believe the uncorrected calculations contain significant and useful information.

The atmospheric energy A per unit mass can be broken down into four components, as follows,
AE
where E is the enthalpy, Φ is the gravitational potential energy, LH is the latent energy associated with phase changes of water, and KE is the kinetic energy. At times, the contribution made by KE will be neglected, due to its negligible contribution. In this case, A can be written as the moist static energy h per unit mass,
hs
where s is the dry static energy (s = E + Φ).
To better understand the physical processes at work, the total energy transport is decomposed into transport by the mean meridional circulation (MMC), stationary eddies, and transient eddies (M88), as follows,
i1520-0442-14-17-3643-e4
where [ ] represents an area-weighted zonal mean, is a time average, * is the deviation from the zonal mean, and a ′ is the deviation from the time average. Note that transport quantities are global values, by definition.

b. Results

1) Divergence of atmospheric energy

The interannual variability of the spatially averaged divergence of atmospheric energy from the Tropics and subtropics is presented in Fig. 8. The most striking feature is the large increase measured during the El Niño. Also noteworthy is a smaller absolute decrease observed during the La Niña.

Figure 9 shows the zonally integrated divergence of atmospheric energy for the El Niño and the La Niña. The positive values equatorward of approximately 45° latitude in both curves represent the transport of atmospheric energy to higher latitudes. Table 4 lists the departure from the study period average for the two seasons. The results indicate an increase of about 6% of the divergence of atmospheric energy from the Tropics and subtropics during the El Niño and a corresponding decrease of approximately 2% during the La Niña. It is important to remember that the study period values are slightly biased toward negative MEI indices (Fig. 1); therefore, it is not surprising that the deviation from the study period is larger during the El Niño than during the La Niña.

2) Meridional energy transport

(i) Transport by the MMC

Transport by the MMC is dominant in the Tropics and, to a lesser extent, the subtropics. Figure 10 shows the poleward transport of s and LH by the MMC for the two seasons. Poleward transport increases during the El Niño.

Figure 10 also serves to highlight the interannual variability of the structure of the MMC. During the El Niño, the meridional extent of the northern branch of the Hadley cell decreases, while that of the southern branch increases. The opposite occurs during the La Niña. In addition, the meridional extent of the northern Ferrel cell decreases and increases during the El Niño and the La Niña, respectively. In comparison with the study period, the overall effect is significantly increased northward transport by the northern branch of the Hadley cell, and decreased southward transport by the southern branch of the Hadley cell and the northern Ferrel cell during the El Niño. These trends are reversed during the La Niña.

(ii) Transport by stationary eddies

Figure 11 shows the poleward transport of s and LH by stationary eddies, which is mainly accomplished by planetary waves (M88). Transport is greater in both hemispheres during the El Niño. With respect to the study period, northward transport is increased by about 10%. During the La Niña, northward transport decreases by approximately 5%. The results imply strengthened and weakened planetary wave activity for the two seasons, respectively.

(iii) Transport by transient eddies

The poleward transport of s and LH by transient eddies, associated with baroclinic wave activity (M88), is shown in Fig. 12. Hemispheric differences are evident, most notably in the transport of s (Fig. 12a). Southward transport increases and decreases during the El Niño and La Niña, respectively. The opposite occurs in the Northern Hemisphere. The measured variability is a byproduct of the changing strength and location of the storm track. The maximum of northward transport of s shifts toward the equator during the El Niño. During the La Niña, a double maximum of northward transport of s, associated with the variable storm track position, results in increased northward transport.

4. Discussion and conclusions

The analysis of ERBE data during the Northern Hemisphere winter for the years of 1984–90 confirms the earlier result that clouds serve to cool the globe. A calculation for the Pacific basin illustrates that the same mechanisms are at work, as clouds are found to cool the Pacific basin by a slightly larger value (−22.85 vs −20.83 W m−2).

This study is the first to document the interannual variability of ERBE cloud forcing over the 6-yr lifetime of the scanner instruments. The results show that cloud forcing does exhibit interannual variability, with cloud cooling decreasing during the 1986/87 El Niño and increasing during the 1988/89 La Niña.

A concurrent analysis of ISCCP data reveals that the interannual variability of cloud forcing can be explained in large part by the cloud variability associated with ENSO. During an El Niño event, the relatively uniform SSTs across the central equatorial Pacific result in a merger of the atmospheric convergence zones (Pazan and Meyers 1982; Philander 1990). The zonal Walker circulation is weak during these periods, but the meridional Hadley circulation intensifies (Philander 1990). The opposite happens during a La Niña event, when the cold surface waters of the eastern tropical Pacific stretch far westward in a tongue along the equator, leading to a separation of the convergence zones (Philander 1990). The effects of these large-scale changes in the equatorial Pacific are felt at higher latitudes. Shabbar et al. (1997) identified significant changes to the position and strength of the northern midlatitude storm track. ISCCP data provides corroborative evidence of such changes. Over the mid- and high latitudes, total cloud amount anomalies in excess of ±10% are observed. A direct comparison of the ERBE cloud forcing and ISSCP cloud amount measurements reveals that the spatial variability of high-thin clouds over the tropical Pacific and midthick clouds over the northern high latitudes is most responsible for the measured changes in C.

To understand the effects of ENSO on meridional energy transport requirements, it is essential to understand how the spatial redistribution of cloudiness during ENSO modifies the earth's energy balance. This study shows that, by increasing both the surplus and the deficit of energy at the TOA in an average sense, the spatial redistribution of clouds during the 1986/87 El Niño serves to increase the meridional gradient of energy. During the 1988/89 La Niña, the meridional energy gradient decreases. Once again, these results can be understood in terms of cloud variability, both in the tropical Pacific and the northern mid- to high latitudes.

In response to the varying transport requirements, the structure and strength of the meridional transport of energy must change. Analyses of ERA data show this to be the case. The divergence of atmospheric energy from the Tropics and subtropics to higher latitudes increases by approximately 6% and decreases by about 2% during the 1986/87 El Niño and the 1988/89 La Niña, respectively. These findings are consistent with that of Sun and Trenberth (1998) who used NCEP data to determine the anomalous energy transport and atmospheric circulation changes in the tropical Pacific for the 1986/87 El Niño.

To analyze the underlying physical mechanisms, the total meridional transport is decomposed into that by the MMC, stationary eddies, and transient eddies. The results indicate that significant modifications are made to the atmospheric circulation during the study period. During the 1986/87 El Niño, the increased divergence of atmospheric energy from the Tropics and subtropics is shown to be in large part the result of an intensified Hadley circulation, a fact consistent with earlier results (Philander 1990; Oort and Yienger 1996). However, this study also identifies structural changes of the MMC both in, and poleward, of the Tropics. The 1986/87 El Niño is characterized by a decreased meridional extent of the northern Hadley and Ferrel cells and an increased meridional extent of the southern Hadley Cell. Changes of the opposite sign are found during the 1988/89 La Niña.

Interannual variability is also detected in the meridional transport by stationary and transient eddies. Planetary wave activity is found to strengthen during the 1986/87 El Niño and weaken during the 1988/89 La Niña, with respect to the 6-yr average. The variability of transport by baroclinic waves is closely tied to changes in the structure and strength of the northern midlatitude storm track. During the 1988/89 La Niña, the present study reveals that a double maximum in the meridional transport of the dry static energy by transient eddies results in increased northward transport by this mechanism.

Acknowledgments

This work was supported by ISCCP under a NOAA grant from the Office of Global Programs (OGP), DOC Grant NA67-RJ-0152. The authors would like to thank Richard Johnson, Jorge Ramirez, Angela Benedetti and the reviewers for their helpful comments.

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Fig. 1.
Fig. 1.

Multivariate ENSO Index

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 2.
Fig. 2.

ISCCP/Hartmann cloud classification

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 3.
Fig. 3.

DJF C from ERBE for the study average. The dashed vertical lines indicate the boundaries of the Pacific basin (120°E–70°W). White regions correspond to no available data

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 4.
Fig. 4.

DJF interannual variations of the spatially averaged C from ERBE

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 5.
Fig. 5.

DJF C from ERBE for (a) the El Niño and (b) the La Niña. White regions correspond to no available data

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 6.
Fig. 6.

DJF cloud amount anomaly from ISCCP for middle-thick cloud: (a) the El Niño, (b) the La Niña; and for high-thin cloud: (c) the El Niño, (d) the La Niña. White regions correspond to no available data

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 7.
Fig. 7.

DJF TOA net radiation from ERBE for (a) the study period. TOA net radiation anomaly for: (b) the El Niño and (c) the La Niña

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 8.
Fig. 8.

DJF interannual variations of the spatially averaged divergence of atmospheric energy from ERA

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 9.
Fig. 9.

DJF interannual variations of the zonally integrated divergence of atmospheric energy from ERA

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 10.
Fig. 10.

DJF interannual variations of the meridional transport by the mean meridional circulation from ERA for (a) s and (b) LH

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 11.
Fig. 11.

DJF interannual variations of the meridional transport by stationary eddies from ERA for (a) s and (b) LH

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Fig. 12.
Fig. 12.

DJF interannual variations of the meridional transport by transient eddies from ERA for (a) s and (b) LH

Citation: Journal of Climate 14, 17; 10.1175/1520-0442(2001)014<3643:IVOCFA>2.0.CO;2

Table 1.

DJF spatial and temporal average values of C from ERBE (W m−2). Seasonal values are expressed as anomalies from the study period

Table 1.
Table 2.

DJF spatial and temporal average values of cloud amounts from ISCCP (%). Seasonal values are expressed as anomalies from the study average. The sensitivity from ERBE and ISCCP is shown for the study period (W m−2 per unit area of coverage)

Table 2.
Table 3.

DJF interannual variations of the meridional energy gradient from ERBE (W). Seasonal values are expressed as anomalies from the study period

Table 3.
Table 4.

DJF interannual variations of the zonally and meridionally integrated divergence of atmospheric energy (108 W). Seasonal values are expressed as anomalies from the study period

Table 4.
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