SEASONAL CYCLE
Introduction
I have a very strong interest in the study of the seasonal cycle of the
atmosphere/ocean system. Since generally speaking the seasonal cycle is of
much larger amplitude than interannual variations, it would seem that a better
understanding of the former may aid in understanding the latter. The
construction of anomalies (from the seasonal cycle), while a useful
simplification in many contexts, is nonetheless an artificiality since the
physical system responds to the total (seasonal + anomaly) signal.
Singularities & The Semiannual Cycle
My earliest work in this area
(Lanzante, 1980;
Lanzante and Harnack, 1982a)
involved the "January thaw" which was purported by folklore to be a brief
period of warming in eastern North America during mid-winter. Subsequent work
(Lanzante, 1983a;
Lanzante, 1985)
placed this "singularity" in the
broader context of the low-frequency evolution of the large-scale general
circulation of the atmosphere. It appears that the "January thaw" as well as
another singularity inspired by folklore, "Indian summer", are associated
with the global semi-annual cycle which has its largest signal in the
region of the Asiatic monsoon. Several mechanisms have been proposed for
semiannual signals but the actual cause(s) and nature of the connections
between tropical and extratropical regions have yet to be determined.
Oceanic Mixed Layer
The extratropical oceans provide another venue for study of the seasonal
cycle, although not related to the above. In some regions of the extratropical
oceans the upper oceanic thermal structure undergoes interesting seasonal
variations. In these regions (for example the extratropical North Pacific)
during the cold season the mixed layer of the ocean is deep (~ several hundred
meters) in response to both mechanically (wind) and thermally (latent/sensible
heat flux) induced vertical mixing. As the warming season progresses both
types of forcing decrease due to diminished cyclonic activity and vertical
gradients. During spring a transition to a much shallower mixed layer (~10's
of meters) may occur rather suddenly. For my M.S. thesis work
I attempted to employ a physically motivated
(Lanzante and Harnack, 1983)
statistical scheme to try to predict summer SST in the extratropical
North Pacific based on the consequences of the reduction in mixed layer
depth. While this exercise was not successful, it produced some
useful diagnostic results. It was doomed by the simplicity of the approach
and the limitations of the available data. More recent work by Alexander and
Deser (1995), using a simple physical model seems to confirm the basic thesis.
Some years ago I returned to this area in a collaborative effort with Mike Alexander of CIRES, located in Boulder, CO, and Gabriel Lau of GFDL through the NOAA/Universities Collaborative Project for Climate Diagnosis using General Circulation Models. Mike has extensive experience with simple models of the oceanic mixed layer. Mike and his colleague Jamie Scott have coupled one such model to a GFDL R30 atmospheric model for use in diagnostic studies. I have performed several sizable ensembles of experiments using this coupled model. Diagnostic analyses of these experiments by affiliated personnel will continue for some time, although at the moment I am not personally involved. Results from these experiments were reported in an extensive review paper written recently by Mike (Alexander et al. 2002).
Plans
I hope some time in the future to return to analyzing the ensembles of
coupled model experiments described above.
But, in addition to these oceanic mixed layer modeling experiments, I plan to
examine the nature of the seasonal cycle from another angle (motivated by
current real-time monitoring of the seasonal cycle of surface temperature)
using observed data. In this context I hope to show that much of the evolution
of the seasonal cycle/short-term climate anomalies can be characterized by
jumps (or regime changes). In the future I hope to extend this new approach
to GCM studies as well. Some time in the future I would also like to build on
some of my earlier studies of singularities through more comprehensive data
analyses as well as GCM simulations.
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