Making Climate Forecasts Matter (1999) / Chapter Skim
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2 Climate Forecasting and Its Uses
2 Climate Forecasting and Its Uses
Pages 18-37
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From page 18... ...
The characteristic time scale for changes in weather in the mid-latitudes is a few days or less. In the tropics, especially over the ocean, the weather tends to be much steadier, with sunny weather and steady trade winds punctuated by an hour of daily downpour (usually in the late afternoon)
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From page 19... ...
The strongest known pattern of interannual variability in the earth's climate system is E1 Nino/Southern Oscillation (ENSO) : it consists of both a warming and a cooling of the waters of the equatorial Pacific Ocean occurring irregularly every few years and a concomitant set of worldwide climatic changes that statistically depend on these changes of sea surface temperature in the equatorial Pacific.
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ET 0 60E 120E 180 120W 60W FIGURE 2-1. Typical rainfall and temperature patterns associated with the warm phases of ENSO conditions for the Northern Hemisphere winter season.
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From page 21... ...
. These boundary conditions are the sea surface temperature, sea ice coverage, land ice, snow cover, the amount of vegetation cover on land, and soil moisture.
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How Have Climate Forecasts Been Made Previously? There is a long history of trying to predict the climate, just as there was a long history of weather prediction before the advent of numerical weather prediction.
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From page 23... ...
. Sea surface temperature provides a convenient example of how climate forecasts are made, and the basic idea applies for the other boundary conditions as well (sea ice, land ice, snow cover, soil moisture, vegetative cover, etc.~.
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From page 24... ...
In practice, the time scales of the atmosphere are short compared with those of the ocean so that the surface winds and subsurface temperatures (at various depths) are assimilated into an ocean model to gain an estimate of the initial state of the ocean alone.
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From page 25... ...
correlates with sea surface temperature in both the tropical Pacific and subtropical Atlantic (the predictors) , and statistical forecast schemes using both of these these predictors have proven useful in predicting rainfall in the Brazilian northeast (e.g., Hastenrath, 1990; Uvo et al., 1998~.
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From page 26... ...
When SST in the eastern Pacific increases (during warm phases of ENSO) , the regions of persistent precipitation expand eastward into the central and eastern Pacific and may affect the west coast of South America while moving away from the western Pacific, causing droughts in the normally wet regions around the Indonesian archipelago.
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From page 27... ...
Persistence provides a good forecast for a few months in fact, it is hard for any existing forecast scheme to outperform the forecast of persistence over this time scale. The coupled forecasting model has a rather large nowcast error that arises when the models are coupled: the ocean data generate surface winds in the model that are slightly inconsistent with the observed surface winds.
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From page 28... ...
The dashed line gives the correlation skill of the model under the original initialization procedures and the thin black line gives the correlation skill under improved initialization procedures. The lower diagrams represent the root mean square error between the forecast and observed NINO3 index.
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From page 29... ...
Only in the tropical Pacific do we have a system built specifically for climate prediction. There are regions of the world in which an inadequacy of ocean data implies that relevant SST cannot be reliably predicted by numerical means.
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From page 30... ...
This section discusses current and potential uses of ENSO forecasts and some possible new directions in making climate prediction more useful. From Tropical Pacific SST to Other Quantities In theory, because the coupled atmosphere and ocean have global extent, a model that predicts SST in the tropical Pacific should also predict SST and the concomitant atmospheric response (temperature, pressure, precipitation)
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From page 31... ...
The three numbers in each box represent forecast probabilities that the predicted precipitation is above normal by more than one standard deviation, within one standard deviation of normal, and more than one standard below normal, respectively. Source: http:// iri.ucsd.edu/forecast/net_asmt/ that, even though the ENSO phase is warm, and the southern states were expected to have above-normal precipitation (see Figure 2-1)
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From page 32... ...
Such forecasts are useful for agriculture, sanitation and sewer management, hydroelectric power generation, river transportation, flood control, forest fire control, and mosquito control. Some users desire monthly averaged temperature forecasts for a season to a year in advance.
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From page 33... ...
. Although no climate forecast scheme can predict a specific storm even a season in advance, mesoscale models embedded in larger-scale climate prediction models can indicate that the conditions under which storms form may be present and give some indications of where they might form and of their likely frequency.
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From page 34... ...
precipitation in northeast Brazil is negatively correlated with SST in the tropical Pacific, it is more strongly positively correlated with SST in the subtropical South Atlantic and negatively correlated with SST in the subtropical North Atlantic (Uvo et al., 1998~. On longer time scales, SST in the North and South Atlantic varies out of phase and affects rainfall in the Sahel.
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From page 35... ...
Processes for Identifying Usable Knowledge Until now, research decisions on how to improve seasonal-tointerannual climate prediction have been made entirely by the community of climate scientists. Great advances in understanding and predictive skill have been achieved that may have substantial social benefit.
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From page 36... ...
Two strategies might be used to bring scientific output and users' needs closer together. One relies on developing quantitative models of the sensitivity of the outcomes of weather-sensitive human activities to climate variation and using these models to identify the climatic parameters to which particular sectors or groups are highly sensitive or vulnerable.
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From page 37... ...
2. The skill of climate predictions varies by geographic region, by climate parameter, and by time scale.
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