scholarly journals A martingale-based temporal analysis of pre-earthquake anomalies at Jiuzhaigou, China, in the period of 2009-2018

2019 ◽  
Vol 131 ◽  
pp. 01072
Author(s):  
Ling Lin ◽  
Xiangzeng Kong ◽  
Nan Li
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Outgoing Longwave Radiation ◽  
Historical Data ◽  
Longwave Radiation ◽  
Temporal Analysis ◽  
Algorithm Analysis ◽  
Martingale Theory ◽  
Strong Earthquakes ◽  
The Relationship

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.

scholarly journals The Relationship Between Cloud Cover and Outgoing Longwave Radiation in the Southern of Vietnam

2018 ◽  
Vol 34 (1S) ◽  
Author(s):  
Chu Thi Thu Huong ◽  
Bui Thi Hop ◽  
Tran Dinh Linh ◽  
Vu Thanh Hang
Keyword(s):  
Spatial Distribution ◽  
Rainy Season ◽  
Outgoing Longwave Radiation ◽  
Cloud Cover ◽  
Temporal Evolution ◽  
El Nino ◽  
Longwave Radiation ◽  
Downward Trend ◽  
La Nina ◽  
The Relationship

Abstract: Based on the data that has the resolution is 1,00×1,00of the Outgoing Longwave Radiation (OLR) and the cloud cover from NCEP/NCAR in the 1981 – 2012 period, the relationship between the cloud cover and the OLR in the Southern of Vietnam wasinvestigated when analyze and compare the spatial distribution, temporal evolution and their correlation. The results show that the characteristics of the spatial distribution and the year cycle of cloud cover and OLR are inversely correlated. The region or time that the cloud cover is great, the OLR is small and vice versa. In the Southern of Vietnam, the OLR value isgreatest(or smallest) in the dry (or rainy) season and in the El-Nino (La-Nina) years. In addition, during the 1981-2012period, the OLR in this region shows a downward trend about 3.6 W/m2/decade, while the cloud cover tends to increase by 0.2%/decade. Keywords: Cloud cover, Outgoing Longwave Radiation, the Southern of Vietnam.

scholarly journals Development of the HIRS Outgoing Longwave Radiation Climate Dataset

2007 ◽  
Vol 24 (12) ◽  
pp. 2029-2047 ◽  
Author(s):  
Hai-Tien Lee ◽  
Arnold Gruber ◽  
Robert G. Ellingson ◽  
Istvan Laszlo
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Outgoing Longwave Radiation ◽  
Longwave Radiation ◽  
Radiation Budget ◽  
Validation Data ◽  
The Earth ◽  
Data Record ◽  
Earth Radiation Budget ◽  
Earth Radiation

Abstract The Advanced Very High Resolution Radiometer (AVHRR) outgoing longwave radiation (OLR) product, which NOAA has been operationally generating since 1979, is a very long data record that has been used in many applications, yet past studies have shown its limitations and several algorithm-related deficiencies. Ellingson et al. have developed the multispectral algorithm that largely improved the accuracy of the narrowband-estimated OLR as well as eliminated the problems in AVHRR. NOAA has been generating High Resolution Infrared Radiation Sounder (HIRS) OLR operationally since September 1998. In recognition of the need for a continuous and long OLR data record that would be consistent with the earth radiation budget broadband measurements in the National Polar-orbiting Operational Environmental Satellite System (NPOESS) era, and to provide a climate data record for global change studies, a vigorous reprocessing of the HIRS radiance for OLR derivation is necessary. This paper describes the development of the new HIRS OLR climate dataset. The HIRS level 1b data from the entire Television and Infrared Observation Satellite N-series (TIROS-N) satellites have been assembled. A new radiance calibration procedure was applied to obtain more accurate and consistent HIRS radiance measurements. The regression coefficients of the HIRS OLR algorithm for all satellites were rederived from calculations using an improved radiative transfer model. Intersatellite calibrations were performed to remove possible discontinuity in the HIRS OLR product from different satellites. A set of global monthly diurnal models was constructed consistent with the HIRS OLR retrievals to reduce the temporal sampling errors and to alleviate an orbital-drift-induced artificial trend. These steps significantly improved the accuracy, continuity, and uniformity of the HIRS monthly mean OLR time series. As a result, the HIRS OLR shows a comparable stability as in the Earth Radiation Budget Satellite (ERBS) nonscanner OLR measurements. HIRS OLR has superb agreement with the broadband observations from Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) in the ENSO-monitoring regions. It shows compatible ENSO-monitoring capability with the AVHRR OLR. Globally, HIRS OLR agrees with CERES with an accuracy to within 2 W m−2 and a precision of about 4 W m−2. The correlation coefficient between HIRS and CERES global monthly mean is 0.997. Regionally, HIRS OLR agrees with CERES to within 3 W m−2 with precisions better than 3 W m−2 in most places. HIRS OLR could be used for constructing climatology for applications that plan to use NPOESS ERBS and previously used AVHRR OLR observations. The HIRS monthly mean OLR data have high accuracy and precision with respect to the broadband observations of ERBE and CERES. It can be used as an independent validation data source. The uniformity and continuity of HIRS OLR time series suggest that it could be used as a reliable transfer reference for the discontinuous broadband measurements from ERBE, CERES, and ERBS.

scholarly journals Comparison of the Long-Range Climate Memory in Outgoing Longwave Radiation over the Tibetan Plateau and the Indian Monsoon Region

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongping Shen ◽  
Jun Shi ◽  
Yadong Lei
Keyword(s):  
Time Series ◽  
Outgoing Longwave Radiation ◽  
Cloud Cover ◽  
Indian Monsoon ◽  
Longwave Radiation ◽  
The Tibetan Plateau ◽  
Monsoon Region ◽  
Scaling Exponents ◽  
High Cloud ◽  
Indian Monsoon Region

Based on the detrended fluctuation analysis (DFA) method, scaling behaviors of the daily outgoing longwave radiation (OLR) from 1979 to 2015 over the Tibetan Plateau (TP) and the Indian Monsoon Region (IMR) are analyzed. The results show that there is long-term memory for the OLR time series over the TP and IMR. The long-range memory behaviors of OLR over TP are stronger than those over IMR. The averaged values of the scaling exponents over TP and IMR are 0.71 and 0.64; the maximum values in the two regions are 0.81 and 0.75; the minimum values are 0.59 and 0.58. The maximum frequency counts for scaling exponents occur in the range of 0.625 and 0.675 both in TP and in IMR. The spatial distribution of the scaling exponents of the OLR sequence is closely related to the conditions of climatic high cloud cover in the two areas. The high cloud cover over TP is obviously less than that of IMR. In addition, the scaling behaviors of OLR over TP and IMR are caused by the fractal characteristics of time series, which is further proved by randomly disrupting the time series to remove trends and correlation.

scholarly journals An Evaluation of Northern Australian Wet Season Rainfall Bursts in CMIP5 Models

2018 ◽  
Vol 31 (19) ◽  
pp. 7789-7802 ◽  
Author(s):  
Sugata Narsey ◽  
Michael J. Reeder ◽  
Christian Jakob ◽  
Duncan Ackerley
Keyword(s):  
Outgoing Longwave Radiation ◽  
Climate Models ◽  
Longwave Radiation ◽  
Cmip5 Models ◽  
Madden Julian Oscillation ◽  
Wet Season ◽  
The North ◽  
Coupled Climate Models ◽  
The Tropics ◽  
The Relationship

The simulation of northern Australian wet season rainfall bursts by coupled climate models is evaluated. Individual models produce vastly different amounts of precipitation over the north of Australia during the wet season, and this is found to be related to the number of bursts they produce. The seasonal cycle of bursts is found to be poor in most of the models evaluated. It is known that northern Australian wet season bursts are often associated with midlatitude Rossby wave packets and their surface signature as they are refracted toward the tropics. The relationship between midlatitude waves and the initiation of wet season bursts is simulated well by the models evaluated. Another well-documented influence on the initiation of northern Australian wet season bursts is the Madden–Julian oscillation (MJO). No model adequately simulated the tropical outgoing longwave radiation temporal–spatial patterns seen in the reanalysis-derived OLR. This result suggests that the connection between the MJO and the initiation of northern Australian wet season bursts in models is poor.

scholarly journals Detecting Thermal Anomalies of Earthquake Process Within Outgoing Longwave Radiation Using Time Series Forecasting Models

2020 ◽  
Vol 63 (5) ◽  
Author(s):  
Dulin Zhai ◽  
Xueming Zhang ◽  
Pan Xiong
Keyword(s):  
Time Series ◽  
Outgoing Longwave Radiation ◽  
Time Series Data ◽  
Arima Model ◽  
Longwave Radiation ◽  
Time Series Forecasting ◽  
Series Data ◽  
Jiuzhaigou Earthquake ◽  
Forecasting Models ◽  
Mexico Earthquake

  The catastrophic damages caused by the Jiuzhaigou earthquake in China of August 8, 2017 and the Mexico earthquake of September 20, 2017 have revealed some important weaknesses of currently operational earthquake-monitoring and forecasting systems. In this work, six time series forecasting models were applied to detect pre-earthquake anomalies within infrared outgoing longwave radiation. After comparing their prediction results using non-seismic time series data, the autoregressive integrated moving average (ARIMA) model was selected as the optimal model, and then a new prediction method based on this ARIMA model was proposed. The results show that the values observed on July 27 and August 5 before the Jiuzhaigou earthquake in China exceed the confidence interval for prediction and reaches the maximum on August 5, 2017. This indicates the infrared outgoing longwave radiation (IR-OLR) anomalies before the Jiuzhaigou earthquake in China. For the Mexico earthquake, pre-earthquake IR-OLR anomalies are detected on September 14, 18, and 19, and reaches the maximum on September 14, 2017. This demonstrates that the proposed time series forecasting model based on ARIMA could be an effective method for earthquake anomalies detection within infrared outgoing longwave radiation.

scholarly journals Relationship of the Arctic and Antarctic Oscillations to the Outgoing Longwave Radiation

2003 ◽  
Vol 16 (10) ◽  
pp. 1583-1592 ◽  
Author(s):  
A. J. Miller ◽  
S. Zhou ◽  
S-K. Yang
Keyword(s):  
Numerical Model ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Outgoing Longwave Radiation ◽  
Longwave Radiation ◽  
Sea Surface ◽  
Radiation Budget ◽  
The Arctic ◽  
Relationship Of ◽  
The Relationship

Abstract While several mechanisms have been suggested to account for the association of the Arctic and Antarctic Oscillations (AO/AAO) with atmospheric parameters, this paper focuses on the relationship with the atmospheric outgoing longwave radiation (OLR). The main objective of this paper is to demonstrate through AO/AAO composite analysis that the NCEP–NCAR reanalysis OLR agrees with the independent observations of the NASA Earth Radiation Budget Experiment (ERBE) broadband satellite instruments both in zonal averages and in geographically mapped space, and to verify AO/AAO characterized general circulations derived from models and analyses. The results indicate several pronounced areas of storminess that are AO/AAO dependent. One is the well-known variation over the North Atlantic Ocean toward Europe. Also, several major areas are indicated in the tropical region—one in the Indian Ocean and the others in the west and central Pacific Ocean. In addition to demonstrating that the signals are statistically significant, also tested is the relationship of the features to other well-known tropical forcing mechanisms: the Madden–Julian oscillation (MJO) and the El Niño–La Niña sea surface temperature variations. It is shown that the tropical features do, in fact, have a strong relationship to the MJO, which indicates an additional tropical–extratropical interaction. With regard to the sea surface temperature, no correlation associated with the AO/AAO variability is seen. These associations with the cloudiness and atmospheric radiation budget suggest that if there is to be improvement of numerical model forecasts to an extended time period that numerical model radiation physics will have to be taken into consideration and improved.

scholarly journals On the decadal increase in the tropical mean outgoing longwave radiation for the period 1984-2000

2004 ◽  
Vol 4 (5) ◽  
pp. 1419-1425 ◽  
Author(s):  
D. Hatzidimitriou ◽  
I. Vardavas ◽  
K. G. Pavlakis ◽  
N. Hatzianastassiou ◽  
C. Matsoukas ◽  
...  
Keyword(s):  
Time Series ◽  
Outgoing Longwave Radiation ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Atmospheric Temperature ◽  
Tropical Region ◽  
Transfer Model ◽  
Cloud Data ◽  
Low Level ◽  
High Level

Abstract. In the present paper, we have calculated the outgoing longwave radiation at the top of the atmosphere (OLR at TOA) using a deterministic radiation transfer model, cloud data from ISCCP-D, and atmospheric temperature and humidity data from NCEP/NCAR reanalysis, for the seventeen-year period 1984-2000. We constructed anomaly time-series of the OLR at TOA, as well as of all of the key input climatological data, averaged in the tropical region between 20°N and 20°S. We compared the anomaly time-series of the model calculated OLR at TOA with that obtained from the ERBE S-10N (WFOV NF edition 2) non-scanner measurements. The model results display very similar seasonal and inter-annual variability as the ERBS data, and indicate a decadal increase of OLR at TOA of 1.9±0.2Wm-2/decade, which is lower than that displayed by the ERBS time-series (3.5±0.3Wm-2). Analysis of the inter-annual and long-term variability of the various parameters determining the OLR at TOA, showed that the most important contribution to the observed trend comes from a decrease in high-level cloud cover over the period 1984-2000, followed by an apparent drying of the upper troposphere and a decrease in low-level cloudiness. Opposite but small trends are introduced by a decrease in low-level cloud top pressure, an apparent cooling of the lower stratosphere (at the 50mbar level) and a small decadal increase in mid-level cloud cover.

scholarly journals Jet streams anomalies as possible short-term precursors of earthquakes with M>6.0

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Hong-Chun Wu ◽  
Ivan N. Tikhonov
Keyword(s):  
Outgoing Longwave Radiation ◽  
Longwave Radiation ◽  
Cumulative Probability ◽  
Jet Stream ◽  
Short Term ◽  
Jet Streams ◽  
Strong Earthquakes ◽  
Thermal Fields ◽  
Precursors Of Earthquakes ◽  
Short Term Prediction

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.

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