The value of AHTEQ varies from 2.1 PW northward in February to 2.3 PW southward in August with an annual average of 0.1 PW southward. The vast majority (over 99%) of the seasonal variations in cross-equatorial atmospheric heat transport are associated with the zonal and time averaged meridional overturning circulation at the equator (i.e., the Hadley cell), which reverses seasonally (Dima and Wallace 2003). The seasonal variations in cross-equatorial heat transport associated with the stationary and transient eddies are two orders of magnitude smaller in magnitude (not shown). 7 K in September and a minimum of ?0.9 K in March; it lags the insolation by approximately 3 months and lags both PCent and AHTEQ by approximately one month. The annual average ?SST value is 0.9 K, which corresponds with the maximum tropical SSTs being located north of the equator in the annual average.
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The seasonal variations in PCent and AHTEQ are strongly anticorrelated (as anticipated from Fig. 1) with an R 2 value of 0.99 and a slope of ?2.7 ± 0.6° PW ?1 . This result suggests that seasonal migrations in both PPenny and AHTEQ primarily reflect the seasonal migration of the Hadley cell. This interpretation is also supported by analysis of the seasonal migration of the overturning streamfunction and the partitioning of AHTEQ into latent, sensible, and potential components (not shown); the total AHTEQ is always of the same sign as the potential energy heat transport and is opposed by the sensible and latent heat transport as would be expected from a thermally direct circulation in a stably stratified column with moisture and temperature decreasing with height. The linear best fit in Fig. 3 passes close to but not through the origin with a y intercept of 1.2°N. This offset is not anticipated from our idealized model presented in the introduction and suggests that, although the vast majority of seasonal variations in PCent and AHTEQ are explained by meridional shifts in the Hadley cell, other phenomena influence either the precipitation and/or atmospheric heat transport. We speculate that monsoonal circulations that are related to zonal inhomogeneities in coastlines and atmospheric circulations-and are thus poorly captured by our zonal average analysis-may bias the precipitation centroid farther north than what would be defined from the Hadley cell–related precipitation only.
Seasonal variations in PPenny and ?SST are strongly correlated (note that the green ?SST x axis in Fig. 3 has been inverted) with an R 2 value of 0.94 and a slope of 3.3° K ?1 . The seasonal correlation between PPenny and ?SST is slightly smaller than that between PCent and AHTEQ because ?SST lags the other two variables by approximately 1 month, leading to an elliptical pattern in the ?SST (green crosses) scatterplot whereas the AHTEQ (red crosses) scatterplot falls nearly on the linear best fit. The y intercept of the linear best fit between PPenny and ?SST is ?1.4° and is not anticipated a priori. Rather, one might suppose that, if SST determined ITCZ location, a SST distribution that is symmetric about the bbw hookup sites equator (?SST = 0) would lead to an ITCZ on the equator (PCent = 0). Instead, the observations suggest that the ITCZ is located south of the equator when there is no interhemispheric contrast of tropical SSTs.
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Seasonal variations in AHTEQ are driven by hemispheric asymmetries in energy input into the atmosphere and can be diagnosed from Eqs. (4) and (5). Ultimately, seasonal variations in AHTEQ result from the seasonal migration of the insolation maximum between the hemispheres although the vast majority of the seasonal variations in insolation are stored in the ocean (Fasullo and Trenberth 2008); the hemispheric asymmetry of net shortwave flux at the TOA [?SWOnline,TOA? in Eq. (4)] has a seasonal amplitude of 22.4 PW and is primarily (83%) balanced by the hemispheric asymmetry of ocean heat storage (?OHT + S?) with a seasonal magnitude of 18.5 PW out of phase with insolation. Therefore, we chose to recast the interhemispheric contrast of the atmospheric energy budget in terms of the absorption of shortwave radiation in the atmosphere (?SWABS?) and the nonsolar exchange of energy between the surface and the atmosphere (?SHF?) as expressed in Eq. (5) (Donohoe and Battisti 2013). 4.