chapter - Atmospheric and Oceanic Science
chapter - Atmospheric and Oceanic Science
chapter - Atmospheric and Oceanic Science
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
which parameters of the GEV distributions show statistically-significant evidence<br />
of trend, using (for example) statistical methods described by Coles (2001). Other<br />
alternatives are statistical analysis of rainfall intensities that exceed some threshold<br />
value (POT: “peaks-over-threshold” analysis) along lines described by Clarke<br />
(2003) <strong>and</strong> Coles (2001).<br />
Rainfall records are in general longer than discharge records in rivers, <strong>and</strong> are<br />
free from some of their complications (increased abstraction; impounding by reservoirs;<br />
changing relationships between river level <strong>and</strong> discharge; effects of sediment<br />
deposition <strong>and</strong> removal; etc). However, similar analyses are also required for runoff<br />
data. These will require not only a station-by-station analysis of individual runoff<br />
records from selected, good-quality sites, but also a spatial analysis to take account<br />
of spatial correlation between flood flows. Appropriate statistical tools for such<br />
analyses are not well developed (for example, methods for fitting GEV distributions<br />
to spatially-correlated flows that also contain time-trends need to be explored).<br />
1.6. Interdecadal variability<br />
Introduction<br />
Superimposed to the climatic trends forced by changes in the concentrations<br />
of greenhouse effect gases, there are variations of interdecadal scale that hinder the<br />
climatic projections for the lapse that they are most required, the next 30 years. The<br />
MCG that have shown certain ability to simulate the global climatic trends of the<br />
last one hundred years, have not been that successful in describing the interdecadal<br />
fluctuations for the same period, Thus, it cannot be guaranteed that model simulations<br />
will capture the future interdecadal variability. This is because some of these<br />
fluctuations are caused by the internal variability of the system, <strong>and</strong> are unpredictable.<br />
In spite of it, in many cases, when these fluctuations reach certain magnitude,<br />
their later evolution can be assessed.<br />
In certain cases, regional climate variables as precipitation or temperature can<br />
be related to explanatory variables (such as variables derived from sea-surface temperature<br />
analysis or large scale or planetary circulation indexes) <strong>and</strong> when these<br />
variables undergo low-frequency (decadal variability), they may have certain<br />
potential for developing hydrological scenarios of the next ten to twenty years in<br />
La Plata basin. Remarkable results in this sense were reported by Robertson et al.<br />
(2001) for the summer season streamflow of the Paraná at Corrientes <strong>and</strong> for the<br />
whole region by Kayano (2003). These methods are based on the low frequency<br />
change of the sea surface temperature in regions that are related to La Plata basin<br />
precipitation <strong>and</strong> one example is developed in <strong>chapter</strong> 14.<br />
13