Abstract
In this paper principal component analysis (PCA) and singular value decomposition (SVD) are used to defne the importance of the variables contributing to the relationship between the transient latent and sensible heat fluxes and to show their temporal and spatial variation. SVD is ofered as an alternative means of isolating spatial and temporal structures in data with the advantage that it can depict simultaneous space-time variations that are aggregates of the results produced by PCA. Both methods of analysis produced two vey important uncorrelated modes of variability in Janua y and July, indicating that the transient heat fluxes are injuenced by fm controlling factors. We suggest that these modes of variability represent the influences of the meridional temperature gradient, atmospheric moisture, and activity within the source and sink regions of the transient heat fluxes. The physical relationships between the heat fluxes that appear to represented by the statistical modes of variability are discussed. The latitudinal imbalance of energy that arises from unequal radiative heating is in part redressed by the poleward transport of energy by the atmosphere. Poleward airflow transfers warmer, more moist air toward colder, drier regions. Much of this transport takes place during winter when the equator-pole gradient of temperature (and energy) is maximized. The flux of energy is therefore necessary to maintain existing global temperature distributions. Much of the energy transported is in the form of latent and sensible heat, and the main agents of transfer in the extratropics are the quasi-stationary eddies (semipermanent features of the general circulation, for example, the Icelandic and Aleutian Lows) and transient eddies (for example, baroclinic eddies, midlatitude wave This work was completed while Marilyn Raphael was on sabbatical at the National Center for Atmospheric Research, where Steve Cherry was a postdoctoral student. The authors thank the CAS group at NCAR for the funding and data that made this work possible. They also thank the three anonymous reviewers for their helpful comments on earlier drafts of this paper. Steve Cherry was supported by the NSF through the Geophysical Statistics Project at NCAR.
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