Modeling satellite ozone data. (English) Zbl 0843.62105

Niu, Xufeng; Tiao, George C.

J. Am. Stat. Assoc. 90, No. 431, 969-983 (1995).

Summary: Starting in the early 1970s, the decline in column ozone over much of the earth has received much attention. Satellite ozone data, with the advantage of global coverage, now play an important role in assessing long-term trends in ozone distributions. We consider a class of space-time regression models for the analysis of satellite data on a fixed latitude, which take into account temporal and longitudinal dependence of the observations. The models can be used to test the uniformity of long-term trends in different longitudinal ozone series. Using the property of circular matrices, explicit expressions of the likelihood functions are obtained. Asymptotic properties of the parameter estimates are briefly discussed. A diagnostic method is proposed to tentatively select the orders in the noise terms of the models. The space-time regression models are applied to the total ozone mapping spectrometer data for trend assessment.

MSC:

62P99	Applications of statistics
86A32	Geostatistics
62M10	Time series, auto-correlation, regression, etc. in statistics (GARCH)
62N99	Survival analysis and censored data
86A10	Meteorology and atmospheric physics

Keywords:

conditional likelihood function; vector AR processes; ozone distributions; space-time regression models; satellite data; uniformity of long-term trends; circular matrices; likelihood functions; diagnostic method; total ozone mapping spectrometer data