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HOME > CPC Outlook Archive - Forecast Distribution File
Degree Days Outlook

CPC Outlook Archive

Forecast Distribution File

File names:

cpcllftd.YYYY.dat - Temperature Distribution file for year YYYY
cpcllfpd.YYYY.dat - Precipitation Distribution file for year YYYY
cpcllftd.dat - Temperature Distribution file for most recent month
cpcllfpd.dat - Precipitation Distribution file for most recent month

The tables give the estimated high frequency skill (skill in predicting the year to year variations), the mean, standard deviation, and the exceedence threshold values for given probability levels. (98,95,90,80,70,60,50,40,30,20,10,5, and 2 percentile levels).

These data are derived from the outlooks issued monthly by CPC, together with an estimate of their skill obtained from the tools used for the prediction.

The forecasts issued on a particular month are grouped together. There are 2 header records followed by multiple data records (Rows) per monthly forecast. Forecasts are for three month target seasons, defined by forecast issue time and lead.
The first line on the header record gives the month, day and year (mmdd yyyy) of forecast issue time, followed by the number of groups and the number of forecast locations in each group. The final number is a forecast type id flag. 950 is a number assigned to identify seasonal temperature forecasts. 951 identifies seasonal precipitation forecasts.
The second header label gives column definitions. Each forecast issue time has its own 2 line header record

Column: label: Definition
1-2: year mn Year and month number that forecast was issued. 1=Jan, 2=Feb. Forecasts are issued around mid-month.
3: lead Approximate lead time of forecast in months - rounded upward, An actual lead time of about one-half month (the shortest lead on the outlooks) is rounded to lead=1, for example. The valid target season can be found by adding lead months to the initial time listed in column 1 and 2, adjusting for year changes.
4: cd: The forecast location to which data apply. See regdict.txt for definitions.
5: r: The correlation skill estimate of this forecast. These are approximate high frequency (year-to-year) correlations, and are not accurate for measuring the trend skill. The actual forecast (including trend prediction) is more skillful than this value indicates.
6-18: 98,95,90,etc Temperatures expected (Forecast) to be exceeded by the percent of time listed in the column label.
19: F mean: The forecast mean value for the target period.
20: C mean: The climatological mean value.
21: F sd Forecast standard deviation. Temperatures are assumed normal, however precipitation is transformed by a power transformation (See col. 23). These columns give the values of the transformed precipitation units and are not in inches!!!! The precipitaion must be transformed before these values can be used
22: c sd Climatological expected value. See important note on column 21description above for Precipitation files.
23: power (Precipitation only) The power transformation value is stored here. The transformed variable, is (precip)**power Where **power indicates raised to the power of the value found in column 23. The transformed variable is approximately Gaussian with mean = median of untransformed variable (col. 12) and standard deviation in transformed units given in columns 21 and 22.

The final line in the data set is denoted by a 9999 in the years position - followed by the data set name of the cd location dictionary file.

Data Set Use
These data are designed to be used in quantitative analysis of CPC forecasts. The forecasts are only estimates of the distribution implied by the long lead outlooks and are derived from the tercile probability anomalies (Forecasts for above, near, and below median). The distribution is most accurate in the vicinity of these tercile boundaries (33 and 66 percent probability of exceedence). Particular caution should be used in the interpretation probabilities below about 10% or above 90%.


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Page last modified: December 12, 2002
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