scholarly journals Relative Contribution of Greenhouse Gases and Ozone-Depleting Substances to Temperature Trends in the Stratosphere: A Chemistry–Climate Model Study

2010 ◽  
Vol 23 (1) ◽  
pp. 28-42 ◽  
Author(s):  
Richard S. Stolarski ◽  
Anne R. Douglass ◽  
Paul A. Newman ◽  
Steven Pawson ◽  
Mark R. Schoeberl
Keyword(s):  
Time Series ◽  
Greenhouse Gases ◽  
Climate Model ◽  
Time Series Data ◽  
Temperature Time Series ◽  
Series Data ◽  
Future Evolution ◽  
The Past ◽  
Ozone Depleting Substances ◽  
Temperature Time

Abstract The temperature of the stratosphere has decreased over the past several decades. Two causes contribute to that decrease: well-mixed greenhouse gases (GHGs) and ozone-depleting substances (ODSs). This paper addresses the attribution of temperature decreases to these two causes and the implications of that attribution for the future evolution of stratospheric temperature. Time series analysis is applied to simulations of the Goddard Earth Observing System Chemistry–Climate Model (GEOS CCM) to separate the contributions of GHGs from those of ODSs based on their different time-dependent signatures. The analysis indicates that about 60%–70% of the temperature decrease of the past two decades in the upper stratosphere near 1 hPa and in the lower midlatitude stratosphere near 50 hPa resulted from changes attributable to ODSs, primarily through their impact on ozone. As ozone recovers over the next several decades, the temperature should continue to decrease in the middle and upper stratosphere because of GHG increases. The time series of observed temperature in the upper stratosphere is approaching the length needed to separate the effects of ozone-depleting substances from those of greenhouse gases using temperature time series data.

Pemodelan dan Peramalan Deret Waktu Studi Kasus: Suhu Permukaan Laut di Selatan Jawa Timur

2017 ◽  
Vol 1 (2) ◽  
pp. 187-199
Author(s):  
Hutomo Atman Maulana ◽  
Muliah Muliah ◽  
Maria Zefaya Sampe ◽  
Farrah Hanifah
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sample Size ◽  
Time Series Data ◽  
Temperature Time Series ◽  
Sea Surface ◽  
Series Data ◽  
Forecast Time ◽  
Temperature Time

The sea surface temperature is one of the important components that can determine the potential of the sea. This research aims to model and forecast time series data of sea surface temperature by using a Box-Jenkins method. Data in this research are the sea surface temperatures in the South of East Java (January 1983-December 2013) with sample size of 372. 360 data will be used for modeling which is from January 1983 to December 2012, and data in 2013 will be used for forecasting. Based on the results of analysis time series, the appropriate models is SARIMA(1,0,0) (1,0,1)12 where can be written as Yt = 0,010039 + 0,734220Yt−1 + 0,014893Yt−12 − (0,734220)(0,014893)Yt−13 + 0,940726et−12 with  MSE of 0.07888096.Keywords: Sea surface temperature, time series, Box-Jenkins method

Motor Shell Temperature Prediction Based on ARIMA

2013 ◽  
Vol 397-400 ◽  
pp. 997-1000 ◽  
Author(s):  
Meng Tao Huang ◽  
Xing Mei Gao
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Arima Model ◽  
Temperature Time Series ◽  
Operating Conditions ◽  
Series Data ◽  
Strong Correlations ◽  
Shell Temperature ◽  
Equipment Failures ◽  
Temperature Time

Temperature is an important parameter representing the motor operating conditions. Temperature monitoring data are time series data, which have strong correlations in time. From the perspective of mathematical statistics, these correlations of time series were analyzed using EViews6.0 software in this paper. Through the establishment of ARIMA model, the motor shell temperature time series was predicted.The final prediction model is ARIMA(1,1,2). Simulation shows that ARIMA model has high predict precision and can be used to predict the temperature of motor shell, which can help to detect equipment failures, avoiding the losses caused by motor faults.

Numerical modeling of the natural and anthropogenic factors influence on the past and future changes in polar, mid-latitude and tropical ozone

2020 ◽  
Author(s):  
Sergei Smyshlyaev ◽  
Polina Blakitnaya ◽  
Maxim Motsakov ◽  
Vener Galin
Keyword(s):  
Solar Activity ◽  
Greenhouse Gases ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Stratospheric Ozone ◽  
Stratospheric Aerosol ◽  
Anthropogenic Factors ◽  
The Past ◽  
Ozone Depleting Substances ◽  
Natural And Anthropogenic Factors

<p>The INM RAS – RSHU chemistry-climate model of the lower and middle atmosphere is used to compare the role of natural and anthropogenic factors in the observed and expected variability of stratospheric ozone. Numerical experiments have been carried out on several scenarios of separate and combined effects of solar activity, stratospheric aerosol, sea surface temperature, greenhouse gases, and ozone-depleting substances emissions on ozone for the period from 1979 to 2050. Simulations for the past and present periods are compared to the results of ground-based and satellite observations, as well as MERRA and ERA-Interim re-analysis. Estimation of future ozone changes are based on different scenarios of changes in solar activity and emissions of ozone-depleting substances and greenhouse gases, as well as the possibility of large volcanic aerosol emissions at different periods of time.</p>

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