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reside in the atmosphere. In this case it follows from the formula for T
2
that the
atmospheric temperature should decrease by 0.84
°
C/year.
Some experts, instead of the index
ʲ
, consider the factor of atmospheric turbidity
B
T
,de
ning it as a ratio of the coef
cient of attenuation of solar energy in the real
atmosphere
ʱ
r
to the coef
cient of attenuation in an ideal atmosphere
ʱ
I
:
B
T
=
cients of attenuation
by water vapor and by aerosols, respectively. The following estimates are assumed
in GIMS:
ʱ
r
/
ʱ
I
=(
ʱ
I
+
ʱ
W
− ʱ
A
)/
ʱ
I
, where
ʱ
W
and
ʱ
A
are the coef
8
<
3
:
0 in mid-latitudes
;
B
T
¼
3
:
5 in tropical latitudes
;
:
2
:
0 at reduced contents of dust and water vapour
:
es to the fact that the desire of
many experts to accurately and completely take into account all possible feedbacks
and compounds of the climate system leads to complicated mathematical problems,
the solution of which a huge amount of data is needed, and in most cases the solutions
of the respective equations turn out to be unstable. Therefore, the use of these
complicated models as a unit of the global model of the GIMS, leads to a negative
result, that is, to impossibility to construct an ef
An experience of the global climate modeling testi
cient model. The most encouraging
approach is to combine the climate models with the data of global monitoring. The
scheme of this combination is very simple. The existing surface and satellite systems
of monitoring the climate-forming processes cover some part of the cells {
Ξ
ij
} of the
Earth surface. Over these cells, measurements are made of temperature, cloudiness,
water vapor content, aerosols and gases, albedo, and various parameters of energy
fl
fluxes. Use of simple climate models and of methods of spatial and temporal inter-
polations enables one to reconstruct, based on these measurements, a complete
pattern of distribution of climatic parameters over the whole territory
Ξ
.
1.9 Conclusion
Main idea of global information-modeling technology was proposed by Krapivin
et al. (1982). First versions of the GIMS were successfully tested in Former USSR
(Russia, Moldova, Uzbekistan, Turkmenistan), where different applied tasks were
solved (Krapivin and Phillips 2001a; Chukhlantsev et al. 2004; Krapivin et al.
2007c; Krapivin and Shutko 2012; Shutko et al. 2010):
earlier detection of the forest fire isolated areas;
monitoring of surface soil moisture in the interests of agriculture;
determination of depth to a shallow water table (down to 2 m in humid areas and
down to 3
5 m in arid/dry areas); and
-
assessment of underground moistening level.
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