Abstract: Short-term earthquake prediction using thermal infrared image from satellite is mainly based on the illumination on the satellite image, which reflects abnormal temperature rise in the atmosphere near the earth surface. This prediction method, however, is restricted when it is cloudy because the satellite cannot ascertain whether there is abnormal temperature rise near the earth surface covered with cloud. By analyzing meteorological data, we know that temperature decrease due to cloud or other meteorological factors cannot change the tendency of temperature rise near the earth surface before earthquake occurrence. Although it is cloudy in the vicinity of the epicenter before some earthquakes occur, temperature can still rise more than 10℃. The curves of temperature rise can be divided into 3 sections (section A, B and C). Among them, sections A and C denote the changes in temperature before its abnormal rise and after earthquakes, respectively. Most of them have a positive correlativity with the time of sunshine; especially in section A the relation is more common. In section B rise of temperature near the surface before an earthquake occurs, however, has no obvious correlativity with the time of sunshine. Hence, all this continuous temperature rise or wavy temperature rise which is unrelated to cloud amount mainly is not due to sunlight or meteorological factors, but is an earthquake precursor related to underground stress function, gas release, and instantaneously changing electric field. Therefore improving the capability of systematic observation of temperature rise under cloud is an effective way to improve earthquake prediction using thermal infrared image.

Key words: Temperature rise, Cloud, Thermal infrared, Earthquake prediction