A preliminary evaluation of surface latent heat flux as an earthquake precursor

• Main Authors: W. Zhang, J. Zhao, W. Wang, H. Ren, L. Chen, G. Yan
• Format: Article
• Language: English
• Published: Copernicus Publications 2013-10-01
• Series: Natural Hazards and Earth System Sciences
• Online Access: http://www.nat-hazards-earth-syst-sci.net/13/2639/2013/nhess-13-2639-2013.pdf
• ISSN: 1561-8633; 1684-9981

The relationship between variations in surface latent heat flux (SLHF) and marine earthquakes has been a popular subject of recent seismological studies. So far, there are two key problems: how to identify the abnormal SLHF variations from complicated background signals, and how to ensure that the anomaly results from an earthquake. In this paper, we proposed four adjustable parameters for identification, classified the relationship and analyzed SLHF changes several months before six marine earthquakes by employing daily SLHF data. Additionally, we also quantitatively evaluate the long-term relationship between earthquakes and SLHF anomalies for the six study areas over a 20 yr period preceding each earthquake. The results suggest the following: (1) before the South Sandwich Islands, Papua, Samoa and Haiti earthquakes, the SLHF variations above their individual background levels have relatively low amplitudes and are difficult to be considered as precursory anomalies; (2) after removing the clustering effect, most of the anomalies prior to these six earthquakes are not temporally related to any earthquake in each study area in time sequence; (3) for each case, apart from Haiti, more than half of the studied earthquakes, which were moderate and even devastating earthquakes (larger than <i>M</i>_w = 5.3), had no precursory variations in SLHF; and (4) the correlation between SLHF and seismic activity depends largely on data accuracy and parameter settings. Before any application of SLHF data on earthquake prediction, we suggest that anomaly-identifying standards should be established based on long-term regional analysis to eliminate subjectivity. Furthermore, other factors that may result in SLHF variations should also be carefully considered.