Geoscience Reference
In-Depth Information
volume and quality of data make it impossible to give adequate answers to the ques-
tions enumerated above. In this connection, anxiety is aroused because of the degra-
dation of the systems of conventional meteorological observations, taking place during
the last decades, which are of importance also for calibration of the satellite remote
sensing results. Therefore, even calculations of decadal mean values of climate
parameters are dif
cult for some regions of Africa and vast regions of theWorld Ocean.
Discussing the observed regularities of global climate change with time and its
causes, Wallace (1998) noted the
first-priority to consider the following problems:
(1) periodic climate change due to variations of extra-atmospheric solar radiation;
(2) quasi-periodic climate variability (its most vivid manifestation
—
quasi-bien-
nial oscillations in the equatorial stratosphere);
(3) ENSO event (in view of a wide range of frequencies, this event cannot be
considered quasi-periodic);
(4) inter-decadal climate variations, which are to a great extent determined by the
internal intra-seasonal and intra-annual variability of the climate system;
(5) climate variability on time scales from inter-decadal to centennial;
(6) analysis of statistical signi
cance of estimates of unprecedented events and
“
”
shifts of regimes
in the light of time-dependent series of many climatic
parameters; and
(7)
revealing the phase relationships between climate change on tine scales from
inter-annual to inter-decadal.
An important fact is that most of climate variability can be described by a
separate consideration of dependencies on time and space coordinates. In view of
an exceptional complexity of the climate system, with its numerous degrees
of freedom and a multitude of feedbacks, highly regular structures and modes
of climate evolution can be rather an exception than a rule.
schemes of
parametrization for reconstructing the structure and evolution of climate anomalies
without super
“
Rough
”
fl
uous detail should have a higher degree of stability. Important cli-
matic
considered in solving the problems of detection and forecast of
global climate change should be seen
“
signals
”
. A much more com-
plicated problem than usually supposed is an assessment of statistical signi
“
with the naked eye
”
cance
of some quantitative characteristics of climate variability, especially unprecedented
events and
from the data on time series of limited duration (as a
rule, in view of time-dependence of such series).
Apparently, one of the perspective directions of studies of climatic time-
dependence and related catastrophic events of the type of the tropical storm Katrina,
which 13 years after Hurricane Andrew was the most powerful in the history of
Miami (Florida), caused the USA a huge economic damage, completely sub-
merging New Orleans and ruining a huge amount of constructions in late August
2005, is a search of connections between temperature variations of different scales
in different water bodies of the World Ocean. For instance, Chang et al. (2000) and
Yamagata et al. (2004) have shown that there is a stable correlation between
changes of water surface temperature in the Indian and Paci
“
shifts of regime
”
c Oceans, which
especially strongly manifest themselves in the season of monsoons in the Indian
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