P1.3
Sensor Averaging for the Determination of Daily Tmax and Tmin Temperature: Experiments with Model and Field Data
K. G. Hubbard, Univ. of Nebraska, Lincoln, NE; and X. Lin and C. B. Baker
Sensor averaging is a filtering method to determine the daily maximum and minimum surface temperature in the era of analog thermometer used in historical climate networks. This filtering can be considered as a process of a surface temperature time-series (either continuous in an analog thermometer or discrete in a digital thermometer) in such a way that the daily maximum or minimum value assigned at a given time is weighted by the values that occurred at other times. We use simulated time series signals to compare the daily Tmax and Tmin when we implemented different weighted functions for filtering. The field observations with specific thermometers were also investigated for better understanding the sensor averaging. The results are useful for clarifying the context of surface temperature uncertainty in instrumental records and for possibly establishing a standard method used in future high quality long-term climate monitoring networks.
Poster Session 1, IOAS-AOLS Poster Session 1
Monday, 30 January 2006, 2:30 PM-4:00 PM, Exhibit Hall A2
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