Climate fluctuations in time and space

Abstract

Satellite imagery of weather was a major breakthrough in the technology of synoptic weather forecasts. Historically, the Earth's climate has experienced dramatic changes, and re- searchers have found that long-term weather patterns do exist. Such long-term changes in weather patterns have very small variations in total atmospheric variables and cannot be observed directly. Complicated space-time detection of low energy signals is required and can be done only by compu- tationally processing space-time data. In this paper, new statistical methods for processing such data are discussed and applied so as to create images of long-term changes in climate over space. Using the historical Central England temperature (CET) time series, we clearly identified temporal scales of 2 to 5 yr and longer than 13 yr. Using monthly global temperature records obtained from the National Climatic Data Center's Global Historical Climatology Network, a long-term average temperature profile along latitude was identified. Global maps of trends of deviations from the average tempera- ture profile display slowly increasing temperatures over a major part of the world. Maps of 2 to 5 yr scales display deviations similar to those observed during an El Nino event and provide the opportu- nity for explanation and prediction of weather anomalies in different regions of the world. In this paper, we utilize recent achievements in the technology of processing 3-dimensional data, i.e. in the separation of scales greater than 1 yr in monthly global temperature records. The Kolmogorov- Zurbenko spline filter allows for direct selection of scales in time and space to obtain a smooth out- come without the application of any models.