Agriculture Reference
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main processes of future climate formation. Because of this assumption,
such forecasts only have a weak scientific basis, and results obtained with
this technique should only be used for the very near future. We would
not expect such forecasts to provide reliable results, for example, on the
daily dynamics of the meteorological parameters in the vegetation grow-
ing season. For this reason the results of calculations with detailed crop
productivity models using such a climate change scenario cannot be consid-
ered to be reliable. Using parameterized techniques for agrometeorological
assessments based on integrated indices would be more justified for this
purpose.
Pa
leoclimatic Reconstruction
[442
The third method of future climate forecasting is paleoclimatic reconstruc-
tion, which has been used mainly by Russian researchers. The essence of
this method is that the characteristic regularities of the earth's climatic
regime in the last warm geological epoch can be assumed to apply to future
climatic conditions. Such analogs, reconstructions of temperature and pre-
cipitation, are used in the Holocene climatic optimum (about 7000 years
ago), in the Riss-Wuerm (Eemian) Interglacial period (about 125,000 years
ago), and in the Pliocene Optimum (3-4 million years ago). It is known that
the globally averaged surface air temperature in these epochs was about
1.2°C higher (Holocene optimum), about 2°C higher (Riss-Wuerm Inter-
glacial), and 3.5°C higher (Pliocene optimum) than in the middle of the
last century (Borzenkova et al., 1987; Budyko et al., 1994). According to
modern forecasts based on climate models, these values of the mean sur-
face air temperature can be expected to be reached in 2010, 2030, and
2050, respectively (Houghton et al., 2001). If the paleoclimatic analogs
are to be used in agroclimatic assessments, it is necessary to appreciate that
they cannot supply the high accuracy of spatial and temporal resolution.
At the best, for temperature, paleoreconstructions can provide only semi-
annual temperature resolution, and for atmospheric precipitation we can
only use them to estimate the changes in its mean annual values. There-
fore, the agroclimatological techniques using the complex dynamic crop
productivity models, which require the day-to-day information for the in-
put meteorological parameters, cannot be directly based on paleoanalog
scenarios.
The difficulties involved in all these three methods of climate modeling
lead us to the conclusion that, at the present time, the technique of agro-
climatological assessments should be to use established submodels based
on empirical agrometeorological indices. This is concerned with the assess-
ments of their mean values and in particular the estimation of the abnormal
agroclimatic phenomena with which droughts are associated. A major part
of such empirical techniques should be the analysis of the actual informa-
tion about the variation of crop productivity and the relevant meteorolog-
ical factors, principally the surface air temperature and the precipitation.
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