Possible Abnormal Phenomenon of the Atmospheric Water Vapor before Hengchun Earthquake

PIERS ONLINE, VOL. 6, NO. 1, 2010 21 Possible Abnormal Phenomenon of the Atmospheric Water Vapor before Hengchun Earthquake Yuntao Ma 1, 3, Yiyang Zhao 1, Shanjun Liu 1, and Lixin Wu 1, 2 1 Institute for Geoinformatics & Digital Mine Research, Northeastern University Shenyang 110004, China 2 Academe of Disaster Reduction and Emergency Management, Beijing Normal University Beijing 100875, China 3 School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, China Abstract Earthquake is the major natural disaster that human beings are facing. The complexity of the earthquake pregnancy remains the earthquake prediction an unresolved problem. Low density of observation stations and small coverage of observation do not provide the necessary information for earthquake predictions. But satellite space monitoring techniques, which have such advantages as wide coverage, rich information, dynamic and high resolution, can provide more comprehensive seismic precursor information. There have been many studies and achievements on satellite thermal infrared, cloud, geoelectricity, gravity and magnetism abnormities before earthquakes, yet there has been little concern about the atmospheric water vapor abnormity during earthquakes. In this paper we analyzed the atmospheric water vapor anomaly during Hengchun earthquake by use of the MODIS satellite data. The study results indicated that there was possible water vapor anomaly to appear during Hengchun earthquake, but further studies are still needed to conduct. 1. INTRODUCTION With the use of satellite remote sensing technology in earthquake prediction, there have been a lot of explorations and researches carried on by many scholars on satellite thermal infrared anomalies before and after earthquakes and a variety of thermal anomaly extraction methods put forward [1 10]. For example, in the case of Hengchun earthquake on December 26, 2006 in Taiwan, Shanjun Liu analyzed thermal infrared satellite data from FY-2C and found there were thermal anomalies over the oceans around epicenter before and after the earthquake [12]. C. Filizzola proposed a robust approach for estimator of thermal infrared radiance anomalies [13]. However, there have been relatively few studies in the atmospheric water vapor anomalies before and after earthquakes. S. Dey analyzed the water vapor of the Gujarat earthquake, found that water vapor over the epicentral region increased just before the earthquake whereas over the ocean, water vapor increased after the earthquake [14]. Lihua Cui analyzed atmospheric water vapor of the Wenchuan earthquake and found that water vapor along the faults increased 11 days before the earthquake [15]. In this paper, We carried out analysis of the atmospheric water vapor, and found that the possible negative anomalies of atmospheric water vapor appeared surrounding the epicenter before and after Hengchun earthquake. 2. DATA AND PROCESSING China Taiwan Region is located in rendezvous site of Philippine Sea Plate, The South China Sea plate and the Eurasian Plate. Special and complex tectonic stress environment leads Taiwan to be the Multi-earthquake region in China. There have been some moderately strong even violent earthquakes annually. The Hengchun earthquake of magnitude 7.2 occurred at 20:26 (12:26 UTC) on December 26, 2006 was the main shock. The epicenter was located at 120.6 E and 21.9 N. After the main shock, there were continuous aftershocks occurred four times in 14 hours (respectively, Ms 6.7 at 20:34 (12:34 UTC), Ms 5.0 at 23:41 (15:41 UTC), Ms 5.0 at 01:35 (17:35 UTC) and Ms 5.3 at 10:30 (2:30 UTC) in the next day). 2.1. MODIS Data Range The data of the earthquake were the TERRA/MODIS image data downloaded from GODDARD SPACE FLIGHT CENTER (http://ladsweb.nascom.nasa.gov/). The data which we used were surface reflectance of 19th band, atmospheric window of 2nd band and the thermal radiation

PIERS ONLINE, VOL. 6, NO. 1, 2010 22 intensity of 31st band. The data set was in resolution of 1 km 1 km. Data range: {Date Range: [2003-11-10, 2004-1-10], [2004-11-10, 2005-1-10], [2005-11-10, 2006-1-10 ], [2006-11-10, 2007-1-10]; time range: [01:00,04:25]; latitude and longitude range: 12 N 30 N, 112 E 130 E.} 2.2. Retrieval of Atmospheric Water Vapor Content and Brightness Temperature Atmospheric water vapor content is the quality of all water vapor on per unit area, the height on per unit area can be understood as an extension of up to infinite, unit is g cm 2. The atmospheric water vapor was produced by two channels of MODIS, 2nd and 19th bands. The retrieval of brightness temperature played two main roles, one was to generate the ocean surface brightness temperature map to view the thermal distribution and the other was to judge the distribution of clouds over the ocean. In the retrieval of water vapor, we also made a judgment if the pixels were interfered by clouds; the retrieval results assigned zero value directly. Brightness temperature was calculated by 31st band of MODIS data. 2.3. Processing The atmospheric water vapor content in a region is closely related with the speed of evaporation and the speed of evaporation under the stable conditions of water supply is mainly due to the temperature. Then the temperature in a large region is affected by the topography, the feature type, solar radiation, weather, seasonal changes and many non-shock factors while the temperature of a small area may also be subject to some external influence, such as human activities, construction activities and etc. So is the atmospheric water vapor content. We used statistical method of a large area as background datum to determine whether there was a water vapor anomaly in a small area during the earthquake (small area lies in large area). Statistical method of a large area as background datum referred to the paper Pre-earthquake Thermal Infrared Anomaly Recognition Method and Quantitative Analysis Model written by Dr. Jinping Li [11]. We conducted a change to the method of that paper in which the anomaly recognition and quantitative extraction method as a unit based on the pixel has become the anomaly recognition method as a unit based on the region. The procedures are as following: 1) Suppose the mean water vapor content in a small area can be expressed as the following formula: W = W r + W (1) where W and W r represent the mean water vapor content in a small area and a large area respectively, W is the value of changes in water vapor affected by the external force in a small area. 2) The mean ( W ) and the standard deviation (σ ( W )) of the variation of water vapor in a small region (the same period of the previous three years) are calculated so as to get the background trend of a small area. n W i i=1 W = (2) n n ( Wi W ) 2 i=1 σ ( W ) = (3) n 1 3) The daily anomaly index of a small area can be calculated as: W I i = W i W σ ( W ) (4) 4) If W I i > 1.5, the small area is considered to be an anomaly area. 3. RESULTS AND DISCUSSION We extracted the atmospheric water vapor content and the brightness temperature from MODIS data set that we choose. The atmospheric water vapor data and the brightness temperature data were converted into the color maps by the density slice. Some atmospheric water vapor data were excluded because of the influence of the cloud. By visual interpretation of the color maps, we found that the water vapor content was at about 2.0 g cm 2 surrounding epicenter at the same period of

PIERS ONLINE, VOL. 6, NO. 1, 2010 11/08/2006 11/17/2006 11/24/2006 23 11/27/2006 12/03/2006 12/08/2006 12/15/2006 12/17/2006 12/26/2006 12/27/2006 12/28/2006 01/04/2007 Figure 1: The maps of atmospheric water vapor in the South China Sea. White point indicates the position of the epicenter; Yellow lines show the faults; Cyan polygon represents the small region we chosen; Red polygon represents the large region as the reference background. Table 1: The anomaly index of small area in seismogenic year. W = 0.137 g cm 2, Date W Wr 2006-11-08 2.490 2.299 2006-11-09 2.797 2.701 2006-11-10 1.954 1.624 2006-11-15 2.005 2.178 2006-11-16 2.621 2.449 2006-11-17 2.757 2.360 2006-11-18 2.610 2.532 2006-11-24 1.863 2.008 2006-11-27 2.333 2.151 2006-11-29 1.666 1.646 2006-12-03 1.798 1.671 2006-12-04 2.105 1.842 2006-12-06 2.279 1.890 2006-12-07 2.730 2.222 2006-12-08 2.448 2.331 2006-12-14 2.474 2.127 σ ( W ) = 0.204 g cm 2, Unit: W Ii Date W 0.265 2006-12-15 1.683-0.200 2006-12-17 0.801 0.949 2006-12-18 0.903-1.519 2006-12-19 1.472 0.176 2006-12-20 1.583 1.274 2006-12-22 1.069-0.287 2006-12-25 1.514-1.381 2006-12-26 0.891 0.224 2006-12-28 1.268-0.571 2006-12-29 1.343-0.046 2007-01-02 1.814 0.620 2007-01-04 2.441 1.237 2007-01-05 1.925 1.819 2007-01-06 1.689-0.096 2007-01-07 1.566 1.029 g cm 2 Wr W Ii 1.937 1.914 1.053 1.906 0.983 1.063 1.324 0.058 1.694 1.214 1.079 0.716 1.408 0.151 1.160 1.990 1.101 0.151 1.255 0.238 1.801 0.606 2.245 0.291 1.838 0.243 1.537 0.076 1.483 0.264

PIERS ONLINE, VOL. 6, NO. 1, 2010 24 the previous three years before the earthquake, the distribution of the water vapor had no obvious anomaly along the fault zone. However, Fig. 1 shows the phenomenon of water vapor low-value appeared in the South China Sea region on December 15, 2006, 11 days before the earthquake, which was consistent until the end of year. The minimum appeared on December 17, 2006, and the water vapor value was only 0.801 g cm 2, less than half the mean value. The second smallest value was only 0.891 g cm 2, also did not meet the half mean value on the day of earthquake. The water vapor values returned to the level of about 2.0 g cm 2 after January 2, 2007. Then we calculated that W of the small area minus the large area (chosen by us in Fig. 1) was equal to 0.137 g cm 2 and σ ( W ), standard deviation, was equal to 0.204 g cm 2. After calculating the anomaly index of small area in seismogenic year (Table 1), we found that from December 15th to 26th, the anomaly index was negative apart from December 19th that was equal to 0.058. On December 15th and December 17th, the anomaly index reached 1.914 and 1.906 respectively. It reached 1.990 on the December 26th when the earthquake happened. According to the brightness temperature map retrieved from MODIS, We found that there were thermal phenomena in the earthquake. Prof. Shanjun Liu also has such report on Hengchun earthquake thermal anomalies. However the water vapor negative anomalies emerged not because of thermal anomalies during the earthquake. 4. CONCLUSION The analysis of atmospheric water vapor has shown anomalous behavior during the earthquake. The result shows that: 1) In Hengchun earthquake in Taiwan, there was no phenomena of the increase in water vapor before and after the earthquake, but the phenomena of the reduction in water vapor and the negative anomalies. 2) There are some shortcomings to the anomaly analysis method of regional background reference such as it can not detect abnormal range, the choice of reference region and non-reference region is impacted from Human factors as well. The reason for water vapor negative anomalies in the South China Sea nearby the epicenter is not very clear. Detailed investigations of atmospheric water vapor content and its temporal variations prior and after earthquakes which occur especially near the ocean are required to continue to study in other earthquakes. ACKNOWLEDGMENT This work is supported by the National Natural Science Foundations of China (No. 50774017) and the Liaoning Province Technology Project (2008231001) REFERENCES 1. Gorny, V. I., The earth outgoing IR radiation as an indicator of seismic activity, Proc. Acad. Sci. USSR, Vol. 30, No. 1, 67 69, 1988. 2. Tronin, A. A., Satellite thermal survey-a new tool for the study of seismoactive regions, INT. J. Remote Sensing, Vol. 17, No. 8, 1439 1455, 1996. 3. Tronin, A. A., Remote sensing and earthquakes: A review, Physics and Chemistry of the Earth, Vol. 31, 138 142, 2006. 4. Qiang, Z. J., X. D. Xu, and C. G. Dian, Thermal infrared anomaly precursor of impemding earthquake, Chinese Science Bulletin, Vol. 36, No. 4, 319 323, 1991. 5. Qiang, Z. J and C. G. Dian, Satellite thermal infrared impending temperature increase precursor of Gonghe earthquake of magnitude 7.0, Qinghai Province, Geoscience, Vol. 6, No. 3, 297 300, 1992. 6. Ouzounov, D. and F. Freund, Mid-infrared emission prior to strong earthquakes analyzed by remote sensing data, Advances in Space Research, Vol. 33, 268 273, 2004. 7. Tramutoli, V., V. Cuomob, C. Filizzola, et al., Assessing the potential of thermal infrared satellite surveys for monitoring seismically active areas: The case of Kocaeli earthquake. August 17, 1999, Remote Sensing of Environment, Vol. 96, 409 426, 2005. 8. Freund, F. T., Rocks that crackle and sparkle and glow: Strange pre-earthquake phenonmena, Journal of Scientific Exploration, Vol. 17, 37 71, 2003. 9. Pulinets, S. A., V. D. Ouzouno, A. V. Kareline, et al., The physical nature of thermal anomalies observed before strong earthquakes, Physics and Chemistry of the Earth, Vol. 31, 143 153, 2006.

PIERS ONLINE, VOL. 6, NO. 1, 2010 25 10. Wu, L. X., S. J. Liu, Y. H. Wu, et al., Precursors for fracturing and failure-part 1: IRR image abnormalities, Int. J. Rock Mech. & Min. Sci., Vol. 43, No. 3, 473 482, 2006. 11. Li, J. P., L. X. Wu, S. J. Liu, et al., Pre-earthquake thermal infrared anomaly recognition method and quantitiative analysis model, Journal of China University of Mining & Technology, Vol. 37, No. 6, 1 6, 2008. 12. Liu, S. J., L. X. Wu, J. P. Li, et al., Features and mechanisms of the satellite thermal infrared anomaly before Hengchun earthquake in Taiwan region, Science & Technology Review, Vol. 25, No. 6, 2007. 13. Filizzola, C., N. Pergola, C. Pietrapertosa, et al., Robust satellite techniques for seismically active areas monitoring: A sensitivity analysis on September 7th 1999 Athens s earthquake, Physics and Chemistry of the Earth, Vol. 29, 517 527, 2004. 14. Dey, S., S. Sarkar, and R. P. Singh, Anomalous changes in columu water vapor after Gujarat earthquake, Advances in Space Research, Vol. 33, 274 278, 2004. 15. Cui, L. H., Study on Anomaly of Remote Sensing Information and Mechanism before the Wenchuan Earthquake, Hebei Polytechnic University, 1 63, 2008.