كليدواژه :
زمين لرزه , يونسفر , آنامولي , TEC , تي دو-هتلينگ
چكيده فارسي :
زمين لرزه ها سالانه خسارتهاي جاني و مالي عظيمي به مردم جهان وارد ميكنند. از اينرو دانشمندان همواره به دنبال يافتن راهكاري براي شناسايي زمان و مكان اين پديده، پيش از وقوع آن هستند. اين در حالي است كه فعاليتهاي لرزهاي زمين باعث ايجاد تغييرات ناهنجاري در پارامترهاي يونسفري، پيش از رخداد زمين لرزه هاي بزرگ ميشوند. همين امر سبب شده است كه امروزه بررسي تغييرات يونسفري به يكي از روشهاي مهم پيشبيني زمينلرزه تبديل شود. در اين مقاله براي شناسايي تغييرات يونسفري-لرزهاي از دادههايTEC حاصل از نقشههاي جهاني يونسفر (GIM) استفاده شده است. روش آماري مورد استفاده براي كشف تغييرات ناهنجار يونسفري، آزمون تيدو-هتلينگ چندمتغيره ميباشد. در اين مقاله براي اولين بار از اين روش به منظور بررسي ارتباط تغييرات يونسفري و زمين لرزه استفاده شده است. جهت بررسي كارايي اين آزمون در كشف تغييرات ناهنجار يونسفري-لرزهاي 12 زمينلرزه با بزرگاي گشتاوري بزرگتر و يا مساوي 6 كه در سال 2010 رخ داده، مورد مطالعه قرار گرفتهاند. مطابق با نتايج حاصل، اين آزمون آماري موفق به شناسايي آنامولي يونسفري-لرزهاي در 9 مورد از زمين لرزه هاي مورد مطالعه شده است. اين آنامولي ها عموماً در اطراف مركز زمين لرزه ها مشاهده شده و اغلب يك هفته پيش از زلزله ها قابل شناسايي هستند. همچنين به طور كلي نتايج نشان ميدهد انجام آزمون تيدو-هتلينگ در سطح اطمينان 99% نسبت به سطح اطمينان 95% در اين مطالعه كارآمدتر بوده است.
چكيده لاتين :
The fact of matter is that, aannually, earthquakes create huge losses in life and property to people all around world. On average, about one earthquake with magnitude of and fifteen earthquakes with magnitude of occur in the world. So, scientists are always looking for a way to identify the time and place of the event before its occurrence in order to reduce damages and injuries. Earthquake is seismic geophysical phenomena which including irregular, nonlinear and complex processes that's why there is no simple approach to predict its parameters. However, this is a known fact that before large earthquakes occurrence, seismic activity of the Earth can cause abnormal variations in ionospheric parameters. Hence nowadays, study on ionospheric variations has become one of the most important ways to predict earthquakes. Nowadays, as regards development spatial and temporal resolution of TEC data (that is extracted from GPS and other satellites) seismo-ionospheric studies are rapidly improving. In this paper, in order to identify seismo-ionospheric variations, the TEC data has extracted from global ionospheric maps (GIM) associated with the CODE center. The statistical method that has utilised to detect abnormal ionospheric variations is multivariate T2-Hotelling test for two samples. T2-Hotelling test is a very powerful test for detect the unusual changes of mean of two samples. The first sample which TEC reference values has extracted from it,includ data of the 44 to 15 days before the earthquake, then days has removed with high level of solar and geomagnetic activities ( or ). Second sample has formed from four days, finally for investigating this point that whether the difference between the mean of reference sample and second sample’s mean is significant or not, T2-Hotelling test has used. If the test rejectes, it means that difference is abnormal, otherwise it is usual. Abnormal difference may be through the earthquake. In this paper, this method has used for investigating the relation between the ionospheric abnormal variations and earthquakes, for the first time. In order to evaluate the ability of the test to detect seismo-ionospheric variation, 12 earthquakes with the magnitude greater than or equal 6 that occurred in 2010 has studied. Whereas solar activities in the year 2010 were low and several major earthquakes occured in this year, so that this year has selected for study. Given that the behavior of the ionosphere at diverse latitudes is very different, earthquakes have chosen with various latitudes.Also earthquakes have selected from areas with good IPP coverage. According to the results, this statistical test can detect seismo-ionospheric anomaly for 9 cases of studied earthquakes. These anomalies have generally observed around the center of earthquakes and these are often identifiable a week before the earthquakes (for Haiti, Drake, Honshu, Mexico and Ecuador earthquakes). Another important point is that anomaly of Ecuador earthquake, despite its great depth (206.7 km) is well identified. Results generally indicate that T2-Hoteling test at confidence level of 99%, has been more effective in this study.
