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Mechanisms of Arctic surface air temperature change
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in response to the Madden-Julian Oscillation
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Changhyun Yoo*, Sukyoung Lee, and Steven B. Feldstein
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Department of Meteorology, The Pennsylvania State University
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University Park, Pennsylvania
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* Current affiliation: Center for Atmosphere Ocean Science, Courant Institute, New York
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University, New York
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Corresponding Author address: Changhyun Yoo, Center for Atmosphere Ocean Science,
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Courant Institute, New York University, 251 Mercer Street, New York, New York,
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10012, USA. Email: cyoo@cims.nyu.edu
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Abstract
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Using lagged composites and projections with the thermodynamic energy
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equation, this study investigates the mechanisms that drive the boreal winter Arctic
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surface air temperature (SAT) change associated with the Madden-Julian Oscillation
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(MJO). We use the Wheeler and Hendon MJO index, which divides the MJO into 8
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phases, where phase 1 (phase 5) corresponds to reduced (enhanced) convection over the
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Maritime Continent and western Pacific Ocean. It is shown that the more zonally
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localized (uniform) tropical convective heating associated with MJO phase 5 (phase 1)
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leads to enhanced (reduced) excitation of poleward propagating Rossby waves, which
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contribute to Arctic warming (cooling). Adiabatic warming/cooling, eddy heat flux, and
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the subsequent change in downward infrared radiation (IR) flux are found to be important
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for the Arctic SAT change. The adiabatic warming/cooling initiates the Arctic SAT
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change, however the subsequent eddy heat flux makes a greater contribution. The
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resulting SAT change is further amplified by alteration in downward IR. It is shown that
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changes in surface sensible and latent heat fluxes oppose the contribution by the above
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processes.
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1.
Introduction
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There is increasing support for the hypothesis that the interdecadal warming trend
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in surface air temperature (SAT) at high latitudes, often referred to as polar amplification,
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is associated with poleward propagating Rossby waves excited by tropical convection
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(Ding et al. 2011; Lee et al. 2011a; Lee et al. 2011b; Schneider et al. 2011). This linkage
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between tropical convection, Rossby wave propagation, and polar amplification has been
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observed for various time scales, ranging from intraseasonal (Lee et al. 2011b),
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interannual (Ding et al. 2011), interdecadal (Schneider et al. 2011), and even for
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statistically steady states (Lee et al. 2011a). To investigate the physical mechanism that
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accounts for this linkage, Lee et al. (2011b) performed a budget analysis using ERA-40
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reanalysis data on the interdecadal SAT trend for the 1959-2001 boreal winter seasons
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(December to February). They showed that a major contributor to polar amplification is
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enhanced dynamical warming (the sum of horizontal thermal advection plus an eddy-
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induced adiabatic warming) and increased downward infrared radiation (IR). They also
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found that this change in dynamical warming is associated with intraseasonal time scale
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tropical convection and the subsequent excitation of poleward propagating Rossby
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waves. For Antarctica, a similar result was reported in the observational and modeling
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study of Ding et al. (2011), who showed for the Austral winter that there is an increase in
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warm advection that takes place over West Antarctica via poleward propagating Rossby
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wave trains that are responding to an increased sea surface temperature over the central
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tropical Pacific Ocean.
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Yoo et al. (2011; hereafter YFL) further investigated this relationship between
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tropical convection and Arctic SAT amplification, with their focus being on the
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interdecadal trend in the Madden-Julian Oscillation (MJO; Madden and Julian 1971,
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1972, 1994). They showed that there is a statistically significant increase in the frequency
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of occurrence of MJO phases 4-6 and a corresponding decrease in the frequency of MJO
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phase 1 for the 1979-2008 extended boreal winter (November to March). For this
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calculation, they used the daily MJO index that is described in Wheeler and Hendon
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(2004) (hereafter, the WH MJO index), who divided the MJO into 8 phases, where phase
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1 (phase 5) corresponds to reduced (enhanced) convection over the Maritime Continent
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and western Pacific Ocean (see Fig. 8 in Wheeler and Hendon (2004)). In YFL, the data
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were separated into two different time periods, 1979 to 1993 (P1) and 1994 to 2008 (P2).
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The frequency of occurrence of each MJO phase was calculated by counting the number
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of days that the amplitude of the WH MJO index exceeded a threshold value of 1.5. This
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calculation was performed separately for P1 and P2. Statistically significant changes in
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the frequency of MJO phases 1 and 4 through 6 were obtained, with the frequency of
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phase 1 declining from P1 to P2 and phases 4-6 increasing over the same time period.
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These interdecadal changes in the frequency of occurrence of the MJO phases were
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shown to contribute toward the Arctic SAT amplification trend because MJO phases 4-6
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(1) are associated with Arctic warming (cooling). While the Arctic SAT trend was not
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their focus, a similar relationship between intraseasonal time scale SAT and MJO phase
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has also been reported in other studies (Vecchi and Bond 2004; Lin and Brunet 2009).
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YFL also presented evidence that the SAT changes associated with the MJO are
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attributed to the excitation of poleward propagating Rossby wave trains by tropical
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convection (Fig. 4f in YFL).
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The linkage between the MJO and the extratropical circulation has been
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previously recognized (e.g., Ferranti et al. 1990; Higgins and Mo 1997; Matthews et al.
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2004; Cassou 2008; L'Heureux and Higgins 2008; Lin et al. 2009; Johnson and Feldstein
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2010), but it is unclear as to how the MJO-driven circulation leads to extratropical SAT
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changes. In this study, we investigate the mechanisms through which the Arctic SAT
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changes in response to the MJO during the extended boreal winter. We will show 1) that
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the poleward propagating wave trains lead to changes in the extratropical eddy
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momentum flux convergence which, through thermal wind adjustment, drives changes in
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the overturning circulation that adiabatically warms or cools the Arctic depending upon
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the MJO phase, 2) that the poleward propagating wave trains are accompanied by a
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planetary-scale eddy heat flux that alters the Arctic SAT, and 3) that the Arctic SAT
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change is further amplified by changes in downward IR.
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We have organized this article in the following manner. Section 2 describes the
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data and methodology. In section 3, we illustrate the temporal evolution of the SAT
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associated with MJO phases 1 and 5 and then present a diagnostic analysis of the
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corresponding dynamical processes. We conclude with a brief discussion in section 4.
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2.
Data and Methodology
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We use the daily multivariate MJO index that is described in Wheeler and
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Hendon (2004) (hereafter, WH MJO index) and is obtained from the Bureau of
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Meteorology website (http://www.bom.gov.au/climate/mjo/). The WH MJO index
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consists of the principal components of the two leading combined EOFs of 200- and 850-
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hPa zonal wind and outgoing longwave radiation (OLR) averaged over a tropical band
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(15ºS-15ºN). The 30-year extended boreal winter ranging from 1979 to 2008 is chosen in
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order to limit our analysis to post-1979 observations, which contain modern satellite data.
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In this study, we focus on MJO phases 1 and 5. We consider the MJO as being active
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when the MJO index exceeds a value of 1.5, roughly 30% of the days in our extended-
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boreal-winter dataset.
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To examine the response to the MJO, we also make use of the European Center
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for Medium-Range Weather Forecasts ERA-Interim (1979-2009) reanalysis dataset (Dee
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et al. 2011). For each variable, the seasonal cycle is removed at each grid point by
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subtracting the first three harmonics of the calendar mean for each day. Then, we applied
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a 101-point, 5-100-day, band-pass digital filter for each day from 1979 to 2008. This 5-
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100 day window was chosen to retain synoptic-scale eddy heat and momentum fluxes
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which influence the midlatitude response to the MJO. As will be shown, although the
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planetary-scale waves dominate the response to the MJO, synoptic-scale waves also play
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an important role after about lag +10 days. Furthermore, the time scale for a tropically-
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forced poleward propagating Rossby wave packet to reach high latitudes is about 10 days
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(Hoskins and Karoly 1981). To test the sensitivity of our findings to the filtering window,
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we have also performed composite SAT calculations with 20-100 day and 30-90 day
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band pass filters, and found the spatial patterns to be rather insensitive to the chosen
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window (not shown).
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Most of the results will be presented in the form of lagged composites for MJO
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phases 1 and 5. As in YFL, the threshold criterion for these composites is a MJO index
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amplitude that exceeds a value of 1.5 for each phase. Composites SAT calculations were
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also performed using the more rigorous criteria of L'Heureux and Higgins (2008) which
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requires that the MJO signal propagate eastward with time. These SAT composites (not
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shown) were found to be very similar to those presented in the next section. Over 70% of
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the MJO cases in our simpler methodology satisfy the criteria of L'Heureux and Higgins
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(2008). Lastly, we have also calculated a MJO index based upon the first two EOFs of the
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velocity potential averaged over 15S-15N. Lag correlations indicate that the two
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principal components, PC1 and PC2, are lined up well with RMM1 and RMM2. After
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defining 8 phases of this velocity potential MJO index in a manner analogous to those of
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the WH MJO index, a composite calculation of the anomalous OLR and SAT is
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performed. The results (not shown) are very similar to those presented in the next section.
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The ERA-Interim data used in this study includes wind, temperature, specific
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humidity ( q ), downward infrared radiative (IR) flux, and surface sensible and latent heat
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fluxes. As we will show, the specific humidity and the IR flux are found to be important
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for the MJO-related Arctic SAT change. As such, we briefly discuss the reliability of
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these two fields. To the best of our knowledge, there are no error analyses in the literature
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for the ERA-Interim IR flux. Dee et al. (2011) show the rms error for the specific
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humidity ( q ) for tropical stations, but not for Arctic stations. As such, we cannot verify
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whether our Arctic values of q and IR exceed rms error bounds. Nevertheless, as we will
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show, based on physical grounds, one can be reasonably confident that the downward IR
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flux result has merit. In addition, as will be described later, the composite IR flux is
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statistically significant over a substantial area in the Arctic (see Fig. 5, right column).
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Notwithstanding the above supporting evidence, because the Arctic IR flux of the
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reanalysis dataset relies heavily on the model, the IR flux results to be presented in this
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study should be taken with caution
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3.
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a. Drivers of extratropical SAT change
Results
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Throughout this study, as described above, we will focus on MJO phases 1 and 5,
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which respectively lead to widespread Arctic cooling and warming over a time scale of 1-
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2 weeks. Compared with the other MJO phases, phase 5 (phase 1) is associated with more
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zonally localized (uniform) tropical convective heating (YFL). As was discussed in
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previous studies (Lee et al. 2011a; Lee et al. 2011b; YFL), changes in the spatial
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structure of the tropical convective heating field are linked to changes in Arctic SAT, as a
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more zonally localized (uniform) tropical heating leads to a strengthening (weakening) of
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the poleward propagating Rossby wave trains. Furthermore, we find that the power
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spectrum of the Arctic SAT resembles a first order autoregressive process with a distinct
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spectral peak near 40 days (not shown), which further strengthens the linkage between
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the MJO and Arctic SAT. Lastly, the relationships between Arctic SAT change and MJO
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phases 1 and 5 are likely to be applicable to other MJO phases, since an Arctic cooling
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(warming) of similar amplitude occurs 1-2 weeks after the MJO passes through phases 1-
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3 (4-6) (not shown).
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Figure 1, which is a replication of Fig. 3 in YFL, illustrates time-lagged
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composites of anomalous SAT associated with MJO phases 1 and 5. For phase 1, Arctic
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cooling takes place on lag +5 through lag +15 days (left panels), while phase 5 shows
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Arctic warming on lag +10 through lag +15 days (right panels). These contrasting Arctic
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SAT changes are linked to the differences in the spatial structure of the total tropical
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OLR field at lag day 0 for MJO phases 1 and 5, where the total field is defined as the sum
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of the anomalous OLR associated with the MJO plus the climatological OLR. As
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indicated in the top panels of Fig. 1, phase 5 is associated with more intense and zonally
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localized tropical convection than is phase 1. In accordance with these differences in
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OLR structure, the composite total eddy (defined here as the deviation from the zonal
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mean) geopotential fields display stronger poleward propagating Rossby waves over the
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North Pacific and North America and also stronger equatorward propagating waves over
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the North Atlantic for phase 5 (middle panels in Fig. 2) than for phase 1 (left panels in
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Fig. 2). This weakened (strengthened) poleward wave activity flux for MJO phase 1
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(phase 5) is also shown by calculating the anomalous E-P flux (Edmon et al. 1980)
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averaged over lag -3 through lag +5 days (Fig. 3). As can be seen, in the upper
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troposphere, the anomalous E-P fluxes are dominated by their planetary-scale wave
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contribution (top panels in Fig. 3), with these fluxes being mostly equatorward for MJO
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phase 1 and poleward for MJO phase 5. These results indicate that, overall, the total
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poleward wave activity flux is strengthened in MJO phase 5 and weakened in MJO phase
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1, and most of this wave activity flux is accounted for by the planetary-scale waves. In
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the middle and lower troposphere, for both MJO phase 1 and phase 5, the vertical
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component of the E-P flux is dominant, with the contribution from the planetary- and
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synoptic-scale waves being of similar amplitude. However, an examination of these
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fluxes on a day-to-day basis finds that (see Fig. 8 which shows the eddy heat flux; note
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that the vertical component of the E-P flux is proportional to the product of the eddy heat
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flux and the cosine of latitude, which results in smaller values relative those for the eddy
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heat flux in Fig. 8.) on most days the vertical component of the E-P flux is also
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dominated by its planetary-scale contribution. It is because of a change in the sign of the
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vertical component of the planetary-scale E-P flux vector over the lag -3 to lag +5 day
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interval that the time-averaged contribution can be similar to that for synoptic-scales. In
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the subarctic, there is an anomalous E-P flux convergence (divergence) for MJO phase 5
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(phase 1), indicating that there is increased (decreased) wave absorption in the subarctic
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during MJO phase 5 (phase 1) These differences in the strength of the poleward and
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equatorward propagating waves are also made evident by subtracting the phase 1
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composite from the phase 5 composite (right panels in Fig. 2), since the sign of the
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anomalies in all three sets of panels is the same..
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To investigate the processes through which the SAT changes take place, we start
from the thermodynamic energy equation,
¶T
= -u ×ÑT - N 2 HR-1w + Q ,
¶t
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(1)
where N is the buoyancy frequency defined as
N2 º
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R æ k To dTo ö
+
ç
÷,
Hè H
dz ø
(2)
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and Q is the diabatic heating. Here, R is the gas constant for dry air, H is the scale
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height, k is the ratio of the gas constant to the specific heat capacity at constant pressure
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( º R C ) , and T
p
o
(
)
is the horizontal mean temperature = To ( z ) .
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The relative timing and impact of the terms that drive the SAT change can be
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assessed quantitatively by projecting each term onto the spatial pattern of the SAT
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averaged over lag +3 through lag +11 days (see Feldstein (2003) for additional details
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about the methodology). This time interval is chosen because the time taken for
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tropically-forced Rossby wave trains to reach high latitudes is 5 to 10 days (Hoskins and
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Karoly 1981). We define the projection, Pi , as
Pi = åxij ( l ,q ) T j ( l ,q ) cosq ,
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(3)
j
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where xij is the i th term on the right-hand-side of (1), and T j is the SAT pattern
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averaged over lag +3 to lag +11 days, both at the j th grid point. We further write the
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anomalous SAT at any MJO lag day t as
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T ( l,q ,t ) = a(t)T ( l,q ) + T ¢ ( l,q ,t ) ,
(4)
æ å T ( l ,q ,t ) T ( l ,q ) cosq ö
j
÷
a (t ) = ç j
2
çè
÷ø ,
T
l
,
q
cos
q
(
)
åj j
(5)
and define a ( t ) as
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which results in T ¢ being orthogonal to T . Here, the quantity a ( t ) represents a measure
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of the similarity between the anomalous SAT pattern, T , and the time-mean SAT, T .
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After substituting (4) into (1), multiplying both sides of (1) by T j cosq , and then
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integrating over high latitudes (60°N -90°N), (1) becomes
da
å i=1 Pi ,
=
dt å T j 2 cosq
2
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(6)
j
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where i = 1 corresponds to dynamical warming and i = 2 to the residual, respectively.
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The residual is calculated by subtracting the contribution by the dynamical warming from
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da dt . The residual term includes downward IR (during the boreal winter, downward
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solar radiation is essentially zero over the Arctic) and surface heat fluxes. Unlike the
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dynamical terms, the contribution by these diabatic heating terms to da dt is not
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calculated explicitly, because doing so requires making assumptions about the vertical
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convergence of these fluxes.
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Figure 4 illustrates the projection of the composite of each term on the right-hand-
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side of (1), downward IR, surface heat flux, and specific humidity, onto the time-
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averaged SAT pattern (as defined in (3); top panels), normalized by the maximum
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projection, along with da dt and the corresponding projections (as defined in (6); bottom
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panels), as a function of lag days relative to the MJO. The top two panels in Fig. 4, which
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show normalized projections, measure the similarity between various quantities and the
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time-mean SAT pattern, while the bottom two panels in Fig. 4 show da dt along with
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the separate contribution to da dt made by the terms on the right-hand-side of (1). Also,
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it is important to note that the normalized projection curves do not show the relative
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amplitude of the individual quantities, and are presented to illustrate the relative timing of
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these quantities, especially that for the downward IR flux, specific humidity, and the
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surface heat flux. The relative amplitude of each term can be evaluated by using (6), as
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shown in the lower panel of Fig. 4. The normalized projections show that the dynamical
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warming term (black solid curve) attains its maximum projection at lag +2 days for both
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phase 1 (left panel) and phase 5 (right panel). For phase 1, both the adiabatic cooling and
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cold advection contribute to the high latitude cooling: the adiabatic cooling (dashed curve
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in the top left panel of Fig. 4), which shows its maximum projection at lag -1 days, is
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followed by cold advection (dotted curve in the same panel in Fig. 4) at approximately
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lag +3 days. As can be seen by examining the rate of change of a ( t ) (bottom left panel),
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the contribution from the adiabatic cooling (dashed curve) is relatively small, although it
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apparently initiates the SAT change. After lag +3 days, the projection of the downward
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IR (red curve in the top left panel of Fig. 4) attains its largest value. MJO phase 5 exhibits
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analogous behavior, with adiabatic warming that precedes warm advection, followed by a
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large projection by downward IR that persists for several days (lag +4 to lag +10 days).
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The contribution by the diabatic heating terms to the rate of change of a ( t ) , as
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evaluated with the residual term (see (6)), is relatively small at most lags for both MJO
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phases (blue curve in the bottom panels of Fig. 4). The projection time series of the
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downward IR and the surface heat flux (green curve in the upper panels of Fig. 4) suggest
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that the former term makes a positive contribution to the residual, and the latter term a
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negative contribution. It can thus be inferred that the downward IR amplifies and
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prolongs the Arctic SAT change, which was initiated by the dynamic warming, but that
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the positive contribution by the downward IR is partially offset by the negative
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contribution from the surface heat fluxes. Our analysis also shows that the downward IR
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is associated with a change in moisture as indicated by the very similar projection of the
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vertically averaged (500-1000 hPa) specific humidity onto the time mean SAT pattern
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(blue curve in the top panels of Fig. 4). Although sources and sinks of water vapor, such
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as evaporation and precipitation, can play an important role in determining the water
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vapor concentration, there are observational (Vecchi and Bond 2004) and modeling (Yoo
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et al. 2012) studies which found that the change in moisture in response to the MJO is, at
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least in part, driven by the moisture transport through the circulation response to the
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MJO. This finding collectively suggests the following picture: the MJO changes the
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Arctic SAT through dynamical processes, first through adiabatic warming/cooling and
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horizontal advection, and next by moisture advection which leads to the downward IR
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anomaly. The resulting SAT change is then damped by surface sensible and latent heat
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fluxes. These results are also consistent with the finding of Lee et al. (2011b), who
271
showed with time-lagged linear regression analysis that Arctic warming occurs first
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through dynamical warming and then through the downward IR, followed perhaps by
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increased cloudiness and/or moisture.
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In Fig. 5, we compare the anomalous SAT tendency associated with the MJO (left
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panels) with the corresponding anomalous dynamical warming (middle panels) and
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anomalous downward IR (right panels) at the surface, for phase 1 (upper set of panels)
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and phase 5 (lower set of panels). To highlight large-scale spatial features, these fields are
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truncated to a T21 horizontal resolution. In addition, since the dynamical warming
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projections (black solid curve in the top panels of Fig. 4) show maximum, zero, and
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minimum values on lag +2, +6, and +10 days, respectively, we display in Fig. 5 the SAT
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tendency terms on these days. As expected from Fig. 4, for both phases and all lags, the
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dynamical warming term appears to match reasonably well with the SAT tendency. For
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example, on lag +2 and lag +6 days, phase 1 shows a negative SAT tendency near 135°E
284
and 120°W, respectively. On lag +10 days, a negative anomaly covers the entire western
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Arctic Ocean. The dynamical warming term, which is negative in this region, captures the
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large-scale pattern in the SAT tendency. Similarly, the SAT tendency associated with
287
phase 5 shows good agreement with the corresponding dynamical warming term. The
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pattern correlation between the SAT tendency and the dynamical warming term for the
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domain extending over 60N-90N and averaged over lag day 0 through lag +15 days is
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0.59 (0.60) for MJO phase 1 (phase 5). In addition, the anomalies that are statistically
291
significant at the 90% confidence level for a Student’s t-test are shown (shading). For the
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downward IR, most of the same anomalies are statistically significant at the 95%
293
confidence level, which is not the case for the SAT tendency and dynamic warming
294
anomalies.
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It can be seen that the downward IR more closely resembles the SAT associated
296
with the MJO (Fig. 1), than the corresponding SAT tendency. The spatial correlations
297
between the SAT and the downward IR exceed 0.9 for all lags for the domains 30°N-
298
60°N and 30°N-90°N. Because the SAT change is found to be dynamically driven, this
299
result suggests that the change in downward IR is driven by the same dynamical
300
processes.
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b. Zonal mean diagnostics
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We next perform a diagnostic analysis to investigate how the MJO triggers the
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dynamical warming. For this purpose, we examine various zonal mean quantities for lag -
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6 through lag +10 days, which corresponds to the period that the Arctic SAT anomalies
305
and the projection of the dynamical warming terms are both large and undergo a change
306
in their signs. Zonal mean quantities are considered because 1) a zonal-mean/wave
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interaction perspective (Andrews and McIntyre 1976) allows for mechanistic
308
interpretations and 2) it is a concise approach for describing the somewhat zonally
309
uniform Arctic SAT change. Starting from (1), we take a zonal average:
310
¶[T ]
¶
= - [ v¢T ¢ ] + [TD ] - N 2 HR-1 [ w ] + [Q ] ,
¶t
¶y
(7)
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where the square bracket denotes a zonal average and the prime the deviation from the
312
zonal average. Here, D designates the horizontal divergence term, whose contribution is
313
found to be negligible (not shown).
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First, we examine the temporal evolution of anomalous zonal mean temperature
315
(shading in Fig. 6). Because the MJO tends to be cyclic, both phases show temperature
316
anomalies at negative lags, which correspond to the remnants of previous MJO phases.
317
At high latitudes, phase 1 shows a negative temperature tendency; there is a positive
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temperature anomaly until lag -2 days followed by a negative temperature anomaly that
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appears at lag day 0 and strengthens until lag +6 days. For phase 5, the high latitude
320
temperature tendency is positive from lag day 0 to lag +10 days, with the temperature
321
anomaly changing from negative to positive after lag +6 days. These high-latitude
322
temperature changes are consistent with the widespread Arctic SAT change (Fig. 1),
323
suggesting that zonal mean diagnostics can be used to investigate driving mechanisms.
324
325
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We next examine the process through which adiabatic warming takes place. For
this task, we use the zonal mean momentum equation,
¶[u]
¶
= - [ u¢v¢ ] + [ uD ] + f [ v ] + [ X ].
¶t
¶y
(8)
327
Here, X designates the zonal component of mechanical dissipation. The composite
328
anomalous zonal wind is shown in Fig. 6 (contours), while the tendency is not shown
329
because it can be inferred by comparing the zonal mean zonal winds at adjacent lag days.
330
Focusing first on the tropics, where the MJO is located, we can see a positive tendency
331
for the zonal mean zonal wind in the upper troposphere for phase 5, and a negative
332
tendency for phase 1. This is consistent with the spatial structure of the anomalous
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equatorial OLR, which corresponds to an enhanced localization of convective heating for
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phase 5 and a more zonally uniform convective heating for phase 1 (see Fig. 1); tropical
335
waves are generated by zonally asymmetric tropical heating, while overturning
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circulations such as the Hadley cell are driven by the zonally symmetric component of
337
the heating. In a two-layer GCM, Rossby waves generated by zonally varying tropical
338
heating exert an eastward acceleration in the upper layer (Suarez and Duffy 1992;
339
Saravanan 1993). It was shown that the MJO can also generate an eastward acceleration
340
in the equatorial upper troposphere (Lee 1999). In multi-level GCMs, MJO-like features
341
are found to act in a similar manner (Lee 1999; Caballero and Huber 2010). These
342
changes in the zonal mean zonal wind are driven mostly by the eddy momentum flux
343
convergence (shading in Fig. 7). For phase 5, which as discussed above is associated with
344
more zonally localized tropical heating, eddy momentum flux convergence occurs at the
345
equator (right panels in Fig. 7), while for phase 1, which is associated with more zonally
346
uniform tropical heating, eddy momentum flux divergence takes place at the equator (left
347
panels in Fig. 7).
348
In the extratropics, the anomalous zonal mean zonal wind (contours in Fig. 6)
349
shows the expected thermal wind balance; the zonal mean temperature (shading in Fig. 6)
350
shows negative and positive anomalies, respectively, on the northern and southern sides
351
of a positive wind anomaly, while opposite sign temperature anomalies are observed
352
across a negative wind anomaly.
353
The projection analysis (Fig. 4) indicates that adiabatic warming, although weak,
354
is the harbinger of the processes that result in the Arctic SAT change. Therefore, we first
355
examine the anomalous mean meridional circulation (MMC; contours in Fig. 7). It can be
17
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356
seen that thermally direct circulation cells (solid contours) occur beneath eddy
357
momentum flux divergence, while thermally indirect circulation cells (dashed contours)
358
are seen beneath eddy momentum flux convergence. For instance, at all lags, the negative
359
mass streamfunction anomaly between 10°N-30°N for phase 1 (left panels of Fig. 7) lies
360
below eddy momentum flux convergence (shading in Fig. 7) near 20°N. Similarly, up
361
until lag +8 days, phase 5 shows a positive mass streamfunction anomaly near 25°N that
362
occurs below eddy momentum flux divergence. At high latitudes, the sign of the mass
363
streamfunction anomalies are again consistent with the sign of the eddy momentum flux
364
convergence. For phase 1, the MMC adiabatically cools the Arctic from lag -4 to lag -2
365
days. As shown in Fig. 4, this adiabatic cooling takes place prior to the emergence of the
366
negative Arctic SAT anomaly at lag day 0 (shading in Fig. 6). After lag day 0, the mass
367
streamfunction anomaly becomes positive and the MMC adiabatically warms the Arctic.
368
In a similar manner, the high latitude MMC for phase 5 initially acts to adiabatically
369
warm the Arctic, followed by a period of adiabatic cooling.
370
Finally, we turn our attention to the anomalous eddy heat flux, which plays a dominant
371
role in driving the Arctic SAT change, as suggested by the time rate of change curve of
372
a ( t ) (bottom panels in Fig. 4). (As noted earlier, horizontal thermal advection is
373
essentially identical to the eddy heat flux convergence.) The eddy heat flux anomaly may
374
arise from (1) poleward propagating Rossby waves excited by the MJO heating, or (2) be
375
caused by baroclinic eddies which respond to changes in the baroclinicity of the
376
background state. To investigate these possibilities, we further decompose the eddy heat
377
flux into zonal wavenumbers 1-3 and 4-8 for all eight MJO phases. (The sum of the eddy
378
heat flux of these wavenumbers retrieves almost all of the total eddy heat flux.) In Fig. 8,
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379
the eddy heat flux for zonal wavenumbers 1-3 is shown in thin contours, while that for
380
zonal wavenumbers 4-8 is shown in thick contours. These eddy heat fluxes are
381
superimposed on the baroclinicity (indicated with shading), which is defined as the
382
negative meridional gradient of the zonal mean temperature.
383
Figure 8 shows that the anomalous eddy heat flux contribution from zonal
384
wavenumbers 1-3 dominates over that from zonal wavenumbers 4-8. In particular, the
385
anomalous eddy heat flux near 60°N, which plays an important role in the Arctic SAT
386
change, is mostly associated with zonal wavenumbers 1-3. For all 8 phases, the anomalies
387
in baroclinicity appear to respond to the eddy heat fluxes, rather than the other way
388
around with the baroclinicity influencing the eddy heat fluxes, which would be the case if
389
baroclinic instability were taking place.. For example, the increase in the planetary-scale
390
eddy heat flux for phase 5 (thin solid contours) is followed by a reduction in baroclinicity
391
(shading in blue). Similarly, for phase 1, the weakened planetary-scale eddy heat flux
392
(thin dashed contours) leads a strengthening of the baroclinicity (shading in red). Since
393
the OLR is dominated by its planetary-scale contribution (Fig. 1), these results are
394
consistent with the first possibility, which links the changes in the strength of the eddy
395
flux and poleward wave activity propagation to the spatial structure of the tropical
396
heating. Moreover, for all 8 MJO phases, the relationship between the eddy heat flux and
397
the baroclinicity suggests that the zonal mean temperature, at least in part, is driven by
398
the planetary-scale eddy heat flux.
399
In contrast to these planetary-scale waves, there are indications that zonal
400
wavenumbers 4-8, at times, respond to changes in baroclinicity. For example, for phase 5,
401
the positive synoptic scale eddy heat flux anomaly at lag day 0 near 50°N coincides with
19
DRAFT – Journal of Climate
402
a positive baroclinicity. Analogous behavior can be seen in phases 2, 4, 6, 7, and 8.
403
However, such correspondence is lacking in phases 1 and 3.
404
4.
Conclusions and Discussion
405
This study investigated the mechanisms that drive the extratropical SAT changes
406
associated with the MJO through the use of lagged composites and projections with the
407
thermodynamic energy equation. Consistent with previous studies (Lee et al. 2011a; Lee
408
et al. 2011b; YFL), we found that the zonal structure of tropical heating plays a critical
409
role in determining the sign of Arctic SAT change. It was shown that the more zonally
410
localized (uniform) tropical heating associated with MJO phase 5 (phase 1) leads to
411
enhanced (reduced) excitation of poleward propagating Rossby waves, which contribute
412
to Arctic warming (cooling) through the following three processes:
413
1) The enhanced poleward Rossby wave activity propagation associated with MJO
414
phase 5 results in an increased eddy momentum flux convergence at the equator
415
and divergence over the Arctic. Focusing on high latitudes, this results in a
416
deceleration of the zonal-mean zonal wind. Thermal wind adjustment, in response
417
to these zonal wind changes, leads to the inducement of a thermally direct MMC
418
that warms the Arctic. For MJO phase 1, the opposite wave propagation
419
characteristics lead to the inducement of a thermally indirect MMC, which cools
420
the Arctic.
421
2) The enhanced (reduced) poleward activity propagation associated with MJO
422
phase 5 (phase 1) is accompanied by an increased (decreased) poleward heat flux.
20
DRAFT – Journal of Climate
423
These changes to the eddy heat flux are dominated by zonal wavenumbers 1-3.
424
The contribution by the eddy heat fluxes to Arctic SAT change is greater than that
425
by the MMC.
426
427
3) The Arctic SAT change is further amplified by changes in downward IR, which is
connected in part to alterations in specific humidity.
428
It is also shown that the impact of the above three processes is opposed by surface
429
sensible and latent heat fluxes.
430
This study provides further insight into intraseasonal Arctic SAT amplification
431
that is driven by tropical convection. Apparently, positive surface albedo feedback
432
(Budyko 1969; Sellers 1969), which is associated with snow and ice cover retreats, is not
433
contributing to the warming because the surface heat fluxes act to damp the surface
434
warming driven by the dynamical processes and downward IR. In addition, as suggested
435
in previous studies (Johnson and Feldstein 2010; YFL), the accumulation of many
436
intraseasonal time scale events can contribute to interdecadal time scale change.
437
Therefore, the results of this study support the findings of Lee et al. (2011b) who showed
438
that intraseasonal time scale dynamical process can have an important impact on polar
439
amplification.
440
While inessential to this study, it is worthwhile to note that phase 5 shows a
441
positive zonal mean zonal wind anomaly (thin contours in the right panels of Fig. 6) on
442
the poleward side of the climatological subtropical jet near 30N (thick contours in the
443
panel for lag +4 days) and a negative anomaly on the equatorward side of the jet.
444
Analogous behavior with opposite sign can be seen for phase 1 (left panels in Fig. 6).
445
This is interesting because observational and modeling studies have reported a similar
21
DRAFT – Journal of Climate
446
zonal wind trend associated with climate change (Kushner et al. 2001; Lorenz and
447
DeWeaver 2007; Archer and Caldeira 2008; Lu et al. 2008). Also, during the 1979-2008
448
boreal winter, the frequency of occurrence of MJO phase 5 (phase 1) increased
449
(decreased) (Fig. 2 in YFL). The results of this study suggest that this interdecadal trend
450
in the zonal wind may be in part driven by these changes in the frequency of MJO phases
451
1 and 5.
452
The results of this observational study lead to further questions that need to be
453
addressed with model simulations. First, with lagged composites of observational data, it
454
is difficult to evaluate the effect of one particular phase in isolation. This is because the
455
time scale of one MJO phase is about 5 days, while that for tropically forced Rossby
456
waves to reach high latitudes is about 10 days (Hoskins and Karoly 1981). Therefore, the
457
influence of adjacent MJO phases is unavoidable unless the tropical heating is specified
458
to mimic one particular phase throughout the model integration. Second, the causal
459
relationships between the tropical convection and extratropical SAT change can be better
460
validated in model simulations with controlled unrelated physical processes. To address
461
these questions, initial value calculations, with MJO-like tropical heating, will be
462
presented in an upcoming paper.
463
Acknowledgments
464
This study is supported by National Science Foundation Grants ATM-0852379,
465
AGS-1036858, and by National Oceanic and Atmospheric Administration Grant
466
NA100AR4310251.
22
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467
References
468
Andrews, D. G., and M. E. McIntyre, 1976: Planetary Waves in Horizontal and Vertical
469
Shear: The Generalized Eliassen-Palm Relation and the Mean Zonal Acceleration.
470
J. Atmos. Sci., 33, 2031-2048.
471
472
473
474
Archer, C. L., and K. Caldeira, 2008: Historical trends in the jet streams. Geophys. Res.
Lett., 35, L08803, doi: 10.1029/2008gl033614.
Budyko, M. I., 1969: The effect of solar radiation variations on the climate of the Earth.
Tellus, 21, 611-619.
475
Caballero, R., and M. Huber, 2010: Spontaneous transition to superrotation in warm
476
climates simulated by CAM3. Geophys. Res. Lett., 37, L11701, doi:
477
10.1029/2010gl043468.
478
479
Cassou, C., 2008: Intraseasonal interaction between the Madden-Julian Oscillation and
the North Atlantic Oscillation. Nature, 455, 523-527, doi: 10.1038/nature07286.
480
Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: configuration and
481
performance of the data assimilation system. Quart. J. Roy. Met. Soc., 137, 553-
482
597, doi: 10.1002/qj.828.
483
Ding, Q., E. J. Steig, D. S. Battisti, and M. Kuttel, 2011: Winter warming in West
484
Antarctica caused by central tropical Pacific warming. Nature Geosci, 4, 398-403,
485
doi: 10.1038/ngeo1129.
486
487
Edmon, H. J., B. J. Hoskins, and M. E. McIntyre, 1980: Eliassen-Palm Cross Sections for
the Troposphere. J. Atmos. Sci., 37, 2600-2616.
23
DRAFT – Journal of Climate
488
489
Feldstein, S. B., 2003: The dynamics of NAO teleconnection pattern growth and decay.
Quart. J. Roy. Met. Soc., 129, 901-924.
490
Ferranti, L., T. N. Palmer, F. Molteni, and E. Klinker, 1990: Tropical-Extratropical
491
Interaction Associated with the 30-60 Day Oscillation and Its Impact on Medium
492
and Extended Range Prediction. J. Atmos. Sci., 47, 2177-2199.
493
494
495
496
497
498
Held, I. M., 1975: Momentum Transport by Quasi-Geostrophic Eddies. J. Atmos. Sci., 32,
1494-1497.
Higgins, R. W., and K. C. Mo, 1997: Persistent North Pacific Circulation Anomalies and
the Tropical Intraseasonal Oscillation. J. Climate, 10, 223-244.
Hoskins, B. J., and D. J. Karoly, 1981: The steady-state linear response of a spherical
atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38, 1175-1196.
499
Johnson, N. C., and S. B. Feldstein, 2010: The Continuum of North Pacific Sea Level
500
Pressure Patterns: Intraseasonal, Interannual, and Interdecadal Variability. J.
501
Climate, 23, 851-867, doi:10.1175/2009JCLI3099.1.
502
503
Kushner, P. J., I. M. Held, and T. L. Delworth, 2001: Southern Hemisphere Atmospheric
Circulation Response to Global Warming. J. Climate, 14, 2238-2249.
504
L'Heureux, M. L., and R. W. Higgins, 2008: Boreal Winter Links between the Madden-
505
Julian Oscillation and the Arctic Oscillation. J. Climate, 21, 3040-3050,
506
doi:10.1175/2007JCLI1955.1.
507
508
Lee, S., 1999: Why Are the Climatological Zonal Winds Easterly in the EquatorialUpper
Troposphere? J. Atmos. Sci., 56, 1353-1363.
24
DRAFT – Journal of Climate
509
Lee, S., S. Feldstein, D. Pollard, and T. White, 2011a: Do Planetary Wave Dynamics
510
Contribute
to
Equable
511
10.1175/2011jcli3825.1.
Climates?
J.
Climate,
24,
2391-2404,
doi:
512
Lee, S., T. Gong, N. Johnson, S. Feldstein, and D. Pollard, 2011b: On the possible link
513
between tropical convection and the Northern Hemisphere Arctic surface air
514
temperature
515
10.1175/2011jcli4003.1.
change
between
1958-2001.
Journal
of
Climate,
516
Lin, H., and G. Brunet, 2009: The Influence of the Madden-Julian Oscillation on
517
Canadian Wintertime Surface Air Temperature. Mon. Wea. Rev., 137, 2250-2262,
518
doi:10.1175/2009MWR2831.1.
519
Lin, H., G. Brunet, and J. Derome, 2009: An Observed Connection between the North
520
Atlantic Oscillation and the Madden-Julian Oscillation. J. Climate, 22, 364-380,
521
doi:10.1175/2008JCLI2515.1.
522
Lorenz, D. J., and E. T. DeWeaver, 2007: Tropopause height and zonal wind response to
523
global warming in the IPCC scenario integrations. J. Geophys. Res., 112, D10119,
524
doi: 10.1029/2006jd008087.
525
Lu, J., G. Chen, and D. M. W. Frierson, 2008: Response of the Zonal Mean Atmospheric
526
Circulation to El Niño versus Global Warming. J. Climate, 21, 5835-5851,
527
doi:10.1175/2008JCLI2200.1.
528
529
530
531
Madden, R. A., and P. R. Julian, 1971: Detection of a 40-50 Day Oscillation in the Zonal
Wind in the Tropical Pacific. J. Atmos. Sci., 28, 702-708.
——, 1972: Description of Global-Scale Circulation Cells in the Tropics with a 40-50
Day Period. J. Atmos. Sci., 29, 1109-1123.
25
DRAFT – Journal of Climate
532
533
——, 1994: Observations of the 40-50-Day Tropical Oscillation‚ Review. Mon. Wea.
Rev., 122, 814-837.
534
Matthews, A. J., B. J. Hoskins, and M. Masutani, 2004: The global response to tropical
535
heating in the Madden–Julian Oscillation during the northern winter. Quart. J.
536
Roy. Met. Soc., 130, 1991-2011, doi: 10.1256/qj.02.123.
537
538
Saravanan, R., 1993: Equatorial Superrotation and Maintenance of the General
Circulation in Two-Level Models. J. Atmos. Sci., 50, 1211-1227.
539
Schneider, D., C. Deser, and Y. Okumura, 2011: An assessment and interpretation of the
540
observed warming of West Antarctica in the austral spring. Climate Dynamics, 1-
541
25, doi: 10.1007/s00382-010-0985-x.
542
543
544
545
Sellers, W. D., 1969: A global climate model based on the energy balance of the Earthatmospheric system. Journal of Applied Meteorology, 86, 392-400.
Suarez, M. J., and D. G. Duffy, 1992: Terrestrial Superrotation: A Bifurcation of the
General Circulation. J. Atmos. Sci., 49, 1541-1554.
546
Vecchi, G. A., and N. A. Bond, 2004: The Madden-Julian Oscillation (MJO) and
547
northern high latitude wintertime surface air temperatures. Geophys. Res. Lett.,
548
31, L04104, doi: 10.1029/2003gl018645.
549
Wheeler, M. C., and H. H. Hendon, 2004: An All-Season Real-Time Multivariate MJO
550
Index: Development of an Index for Monitoring and Prediction. Mon. Wea. Rev.,
551
132, 1917-1932.
552
Yoo, C., S. Feldstein, and S. Lee, 2011: The impact of the Madden-Julian Oscillation
553
trend on the Arctic amplification of surface air temperature during the 1979-2008
554
boreal winter. Geophys. Res. Lett., 38, L24804, doi: 10.1029/2011gl049881.
26
DRAFT – Journal of Climate
555
556
Yoo, C., S. Lee, and S. Feldstein, 2012: Arctic response to an MJO-like tropical heating
in an idealized GCM. J. Atmos. Sci., submitted.
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557
Figure List
558
Figure 1. Total OLR composite on lag day 0 (top), with lagged composites of SAT on
559
lag days 0, 5, 10, and 15 for MJO phases 1 (left) and 5 (right). Solid contours are
560
positive, dashed contours negative, and the zero contours are omitted. Positive
561
(negative) values above the 95% confidence level for a Student’s t-test are shaded in
562
red (blue). .................................................................................................................. 30
563
Figure 2. Lagged composites of the zonal-mean-subtracted total geopotential field on lag
564
days 0, 5, 10, and 15 for phase 1 (left), phase 5 (middle), and phase 5 minus phase 1
565
(right). Solid contours are positive, dashed contours negative, and the zero contours
566
are omitted. For the right column, positive (negative) values above the 95%
567
confidence level for a Student’s t-test are shaded in light (dark) gray. .................... 31
568
Figure 3. The time-averaged (lag -3 thorugh lag +5 days) composites of the planetary-
569
scale (top panels) and synoptic-scale (bottom panels) E-P flux (vectors) and their
570
divergence (contours) for MJO phase 1 (left panels) and MJO phase 5 (right panels).
571
The contour interval is 5 m s-2. Solid contours are positive, dashed contours
572
negative, and the zero contours are omitted.............................................................. 32
573
Figure 4. Projections of dynamical warming (black solid curve), adiabatic warming
574
(dashed curve), horizontal thermal advection (dotted curve), downward IR (red
575
curve), surface heat flux (green curve), and specific humidity (blue curve) onto the
576
time averaged SAT patterns for phase 1 (top left panel) and phase 5 (top right
577
panel). Each projection is normalized by its own maximum value. The rate of
578
change of a ( t ) (red curve) and the projection terms on the right-hand-side of (6),
28
DRAFT – Journal of Climate
579
such as dynamical warming (black solid curve), which is comprised of the sum of
580
adiabatic warming (dashed curve) and horizontal thermal advection (dotted curve),
581
along with the residual (blue curve), are shown in the bottom panels. Values have
582
been multiplied by 1 ´ 10-6........................................................................................ 33
583
Figure 5. Lagged composites of SAT tendency (left), dynamical warming (middle), and
584
downward IR (right) for MJO phase 1. All fields are truncated to a T21 horizontal
585
resolution. Lag days 2, 6, 10, and 14 are shown. Solid contours are positive, dashed
586
contours negative, and the zero contours are omitted. Positive (negative) values
587
above the 90% confidence level for a Student’s t-test are shaded in red (blue). ...... 34
588
Figure 6. Lagged composites of zonal mean zonal wind (thin contours) and zonal mean
589
temperature (shading), along with the climatological zonal mean zonal wind (thick
590
contours on the lag +4 day panels), for MJO phase 1 (left) and phase 5 (right). Lag
591
days -6,-4,-2, 0, 2, 4, 6, 8, and 10 are shown. Solid contours are positive, dashed
592
contours negative, and the zero contours are omitted. The contour interval is 0.3 m s-
593
1
for thin contours and 10 m s-1 for thick contours. ................................................... 36
594
Figure 7. As for Fig. 6, except for the eddy momentum flux convergence (shading), and
595
the zonal mean mass streamfunction (contours). The contour interval is 2 ´ 109 s-1. 37
596
Figure 8. Vertically averaged (500-1000 hPa) eddy heat flux for zonal wavenumber 1-3
597
(thin contours) and zonal wavenumber 4-8 (thick contours) superimposed on
598
baroclinicity (shading). The contour interval is 5 ´ 10-8 K m s-1. ............................. 38
29
DRAFT – Journal of Climate
599
600
Figure 1. Total OLR composite on lag day 0 (top), with lagged composites of SAT on
601
lag days 0, 5, 10, and 15 for MJO phases 1 (left) and 5 (right). Solid contours are
602
positive, dashed contours negative, and the zero contours are omitted. Positive (negative)
603
values above the 95% confidence level for a Student’s t-test are shaded in red (blue).
30
DRAFT – Journal of Climate
Figure 2. Lagged composites of the zonal-mean-subtracted total geopotential field on lag days 0, 5, 10, and 15 for phase 1 (left),
phase 5 (middle), and phase 5 minus phase 1 (right). Solid contours are positive, dashed contours negative, and the zero contours are
omitted. For the right column, positive (negative) values above the 95% confidence level for a Student’s t-test are shaded in light
(dark) gray.
31
DRAFT – Journal of Climate
Figure 3. The time-averaged (lag -3 thorugh lag +5 days) composites of the planetaryscale (top panels) and synoptic-scale (bottom panels) E-P flux (vectors) and their
divergence (contours) for MJO phase 1 (left panels) and MJO phase 5 (right panels). The
contour interval is 5 m s-2. Solid contours are positive, dashed contours negative, and the
zero contours are omitted.
32
DRAFT – Journal of Climate
Figure 4. Projections of dynamical warming (black solid curve), adiabatic warming
(dashed curve), horizontal thermal advection (dotted curve), downward IR (red curve),
surface heat flux (green curve), and specific humidity (blue curve) onto the time averaged
SAT patterns for phase 1 (top left panel) and phase 5 (top right panel). Each projection is
normalized by its own maximum value. The rate of change of a ( t ) (red curve) and the
projection terms on the right-hand-side of (6), such as dynamical warming (black solid
curve), which is comprised of the sum of adiabatic warming (dashed curve) and
horizontal thermal advection (dotted curve), along with the residual (blue curve), are
shown in the bottom panels. Values have been multiplied by 1 ´ 10-6.
33
DRAFT – Journal of Climate
Figure 5. Lagged composites of SAT tendency (left), dynamical warming (middle), and
downward IR (right) for MJO phase 1. All fields are truncated to a T21 horizontal
resolution. Lag days 2, 6, 10, and 14 are shown. Solid contours are positive, dashed
contours negative, and the zero contours are omitted. Positive (negative) values above the
90% confidence level for a Student’s t-test are shaded in red (blue).
34
DRAFT – Journal of Climate
Figure 5. Continued. Lagged composites of SAT tendency (left), dynamical warming
(middle), and downward IR (right) for MJO phase 5.
35
DRAFT – Journal of Climate
Figure 6. Lagged composites of zonal mean zonal wind (thin contours) and zonal mean temperature (shading), along with the
climatological zonal mean zonal wind (thick contours on the lag +4 day panels), for MJO phase 1 (left) and phase 5 (right). Lag days 6,-4,-2, 0, 2, 4, 6, 8, and 10 are shown. Solid contours are positive, dashed contours negative, and the zero contours are omitted. The
contour interval is 0.3 m s-1 for thin contours and 10 m s-1 for thick contours.
36
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Figure 7. As for Fig. 6, except for the eddy momentum flux convergence (shading), and the zonal mean mass streamfunction
(contours). The contour interval is 2 ´ 109 s-1.
37
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Figure 8. Vertically averaged (500-1000 hPa) eddy heat flux for zonal wavenumber 1-3
(thin contours) and zonal wavenumber 4-8 (thick contours) superimposed on baroclinicity
(shading). The contour interval is 5 ´ 10-8 K m s-1.
38