scholarly journals The outgoing longwave radiation analysis of medium and strong earthquakes

Author(s):  
Bo Su ◽  
Hao Li ◽  
Weiyu Ma ◽  
Jing Zhao ◽  
Qi Yao ◽  
...  
2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Hong-Chun Wu ◽  
Ivan N. Tikhonov

Satellite data of thermal images revealed the existence of thermal fields, connected with big linear structures and systems of crust faults. The measuring height of outgoing longwave radiation is located to the range of jet stream. This work describes a possible link between strong earthquakes and jet streams in two regions. The front or tail ends of jet groups maintain their position for 6 or more hours in the vicinity of epicenters of strong (<em>M</em>&gt;6.0) earthquakes in 2006-2010. The probability of observing a stationary jet stream behavior is estimated in 93.6% of the cases on one sixhour map and in 26.7% of cases - on two adjacent maps. The median of distribution of distances between epicenters and the relevant positions of jet stream corresponds to 36.5 km. Estimates of cumulative probability of realization of prediction were 24.2% for 10 days, 48.4% for 20 days, 66.1% for 30 days, 87.1% for 40 days, 93.5% for 50 days and 100% during 70 days. The observed precursory effects are of considerable interest for possible use for real short-term prediction of earthquakes.


2019 ◽  
Vol 131 ◽  
pp. 01072
Author(s):  
Ling Lin ◽  
Xiangzeng Kong ◽  
Nan Li

Many studies on the relationship between outgoing longwave radiation (OLR) data observed by National Oceanic and Atmospheric Administration Satellites (NOAA) with strong earthquakes are based on a certain zone or a couple of earthquakes. But it’s hard to know if the algorithm works by looking at just one earthquake. In this paper, after algorithm analysis of OLR signals based on martingale theory during the 10 years from 2009 to 2018, a time series analysis of re-anomaly screening for the 10 years’ data is proposed. The experimental results show that this method can be more effective in the statistical analysis of historical data and further improve the reliability of prediction.


2021 ◽  
Vol 13 (11) ◽  
pp. 2201
Author(s):  
Hanlin Ye ◽  
Huadong Guo ◽  
Guang Liu ◽  
Jinsong Ping ◽  
Lu Zhang ◽  
...  

Moon-based Earth observations have attracted significant attention across many large-scale phenomena. As the only natural satellite of the Earth, and having a stable lunar surface as well as a particular orbit, Moon-based Earth observations allow the Earth to be viewed as a single point. Furthermore, in contrast with artificial satellites, the varied inclination of Moon-based observations can improve angular samplings of specific locations on Earth. However, the potential for estimating the global outgoing longwave radiation (OLR) from the Earth with such a platform has not yet been fully explored. To evaluate the possibility of calculating OLR using specific Earth observation geometry, we constructed a model to estimate Moon-based OLR measurements and investigated the potential of a Moon-based platform to acquire the necessary data to estimate global mean OLR. The primary method of our study is the discretization of the observational scope into various elements and the consequent integration of the OLR of all elements. Our results indicate that a Moon-based platform is suitable for global sampling related to the calculation of global mean OLR. By separating the geometric and anisotropic factors from the measurement calculations, we ensured that measured values include the effects of the Moon-based Earth observation geometry and the anisotropy of the scenes in the observational scope. Although our results indicate that higher measured values can be achieved if the platform is located near the center of the lunar disk, a maximum difference between locations of approximately 9 × 10−4 W m−2 indicates that the effect of location is too small to remarkably improve observation performance of the platform. In conclusion, our analysis demonstrates that a Moon-based platform has the potential to provide continuous, adequate, and long-term data for estimating global mean OLR.


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