In this paper\ we analyze the biochemical oxygen demand data collected over two years from McDowell Creek\ Charlotte\ North Carolina\ U[S[A[\ by \_tting an autoregressive model with time!dependent coe.cients[ The local linear smoothing technique is developed and implemented to estimate the coe.cient
THE AUTOREGRESSIVE MODEL OF CLIMATOLOGICAL TIME SERIES: AN APPLICATION TO THE LONGEST TIME SERIES IN PORTUGAL
✍ Scribed by LEITE, SOLANGE MENDONÇA; PEIXOTO, JOSÉ PINTO
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 565 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0899-8418
No coin nor oath required. For personal study only.
✦ Synopsis
The autoregressive model is extremely useful for the representation of many geophysical time series. The present paper deals, in the first place, with the analysis of sets of meteorological observations (temperature and precipitation) made sequentially in time, from 1856 to 1994, at equidistant time intervals At = 1 year. The best fitting is an autoregressive model of order 45. A thorough discussion of the temperature observation time series is presented, showing two main salient features: an approximately 0.6"C secular trend during the past century and a definite warming in the 1980s and early 1990s. The estimated values of temperature and precipitation are compared with the observed data series.
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