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Combine Climate Stations <br />There are six sets of key climate stations listed in Table 1 for which the physical station location <br />in the Arkansas River Basin moved during the SPDSS study period and/or combining the data <br />for the two stations was determined to be appropriate. The combined stations, with the <br />difference in elevation and distances, are listed below in Table 3. <br />Table 3 <br />Combined Key Climate Stations <br />Independent Time Series (Old Station) Dependent Time Series (New Station) <br />l <br />i <br /> <br />Station Name and ID Period of <br /> <br />Record <br />Station Name and ID Period of <br /> <br />Record 1 <br />Distance E <br />on <br />evat <br />Differences ~ <br />Springfield 8 S 1948 - 1964 Springfield 7 WSW 1956 -2002 9.4 miles 120 feet <br />Pueblo WB Airport 1948 - 1954 Pueblo Memorial Airport 1954 - 2003 8.0 miles 90 feet <br />Rye 1948 - 1992 Rye 1 SW 1997 - 2003 0.9 miles 295 feet <br />Limon 10 SSW 1918 - 1971 Limon 1971 - 1999 4.3 miles 5 feet <br />Salida 3 W 1970 - 1984 Salida 1948 - 2003 1.9 miles 330 feet <br />Leadville 1948 - 1982 Leadville Lake County AP 1976 - 2003 1.5 miles 5 feet <br />The combined data sets were created using the fillFromTSO TSTooI commands, which copies <br />data from the independent time series (old station) to replace missing values in the dependent <br />time series (new station). The setOutputPeriodO command determines the period of record for <br />the dependent time series and must be used in conjunction with the filling command. With this <br />method, data from the dependent time series (new station) are used during any period where the <br />two stations have overlapping data. TSTooI assigns the name and ID of the dependent time <br />series to the combined station. In most instances, combining two stations did not complete the <br />period of record and further steps, as described below, were taken to fill the remaining missing <br />data. <br />2. Investigate and Determine Appropriate Methods for Filling Missing Monthly Data. <br />Missing climate data can be filled using techniques adopted in previous DSS modeling efforts, <br />which generally involved filling missing data using regression with stations located in close <br />proximity. In SPDSS Task 53, several different regression techniques were tested to determine <br />which technique provided predicted or filled data that best matched historical data. It was <br />recommended in Task 53 that the monthly linear regression technique be used to fill both <br />temperature and precipitation monthly data. <br />Task 76 8 2.doc 6 of 17 <br />