## 533: Tailoring

The
**
tailoring
**
options provide a number of ways of providing flexibility in how the forecasts are expressed. The
standardisation options provide different ways of comparing the forecast to a set of references, and of defining how the
category thresholds are communicated. By selecting the "no standardisation" option, the forecasts are expressed in the original
units of the input Y data, but these can be converted to anomalies, standardised anomalies, standardised indices (suitable for
the Standardised Precipitation Index, SPI) or, if the
Zero Bound
option is switched on, to
percentage departures from average. If the % of average standardisation option is selected, and the zero bound option is
subsequently switched off, the standardisation is switched off (a warning is provided). The forecasts and saved data, and the
category thresholds will be expressed in whichever standardisation option is selected. The standardised indices option can be
switched on or off after calculations have already been performed only if the calculations are performed with the
Transform Y Data
switched on, and if the
Transformation
option was set to the gamma distribution. It is therefore best to select
standardised indices before calculating results.

The
**
tailoring
**
menu option also allows you to specify the prior probabilities of the above- and below- normal categories,
or to use thresholds defined in physical values (mm, for example) instead, or to use previous years' observations. By default,
the prior probabilities are set at 33% so that the boundaries between the categories are the terciles of the climatological
distribution, but these probabilities can be reset, allowing probabilities for more extreme rainfall events to be
calculated, for example. However, it should be noted that errors in estimating the thresholds for extreme events can become
large, so changes in the calculated probabilities may be inaccurate. If the absolute thresholds are set, and the lower
threshold is set to be larger than the upper threshold, the two are swapped without warning. The values of the thresholds are
assumed to be in the same units as the values of the (possibly standardised) Y input data. If the standardisation option is set
to "anomalies" and absolute thresholds are used, below-normal rainfall could be set as 100 mm less than average by setting the
lower threshold to -100. The reference year option sets the larger of the observed values for the two years as the threshold
for the "above-normal" category, and the smaller as the threshold for the "below-normal category". Note that it is possible
that the one-year may represent the upper threshold for one location but the lower threshold for another location. This option
is useful for answering questions such as "What is the probability that there will be more rainfall than last year?" Or "What
is the probability that it will be colder than in 1980?"