Mann-Kendall trend analysis of tropospheric ozone and its modeling using ARIMA

被引：48

作者：

Chattopadhyay, Goutami ^{[3
]}

Chakraborthy, Parthasarathi ^{[2
]}

Chattopadhyay, Surajit ^{[1
]}

机构：

[1] Pailan Coll Management & Technol, Dept Comp Applicat, Kolkata 700104, India

[2] Pailan Coll Management & Technol, Dept Business Adm, Kolkata 700104, India

[3] Bengal Engn & Sci Univ, Dept Math, Sibpur 711103, Howrah, India

来源：

THEORETICAL AND APPLIED CLIMATOLOGY | 2012年 / 110卷 / 03期

关键词：

SOLAR ULTRAVIOLET-RADIATION; NEURAL-NETWORK MODELS; TIME-SERIES; CLIMATE-CHANGE; VARIABILITY; IMPACT; TEMPERATURE; PREDICTION; DYNAMICS; IRRADIANCE;

D O I：

10.1007/s00704-012-0617-y

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

The present work reports studies on the spatial distribution of tropospheric ozone extending over both southern and northern hemispheres. This study is based on a univariate approach to the spatial data series obtained at regular spatial intervals. Mann-Kendall's (MK) trend analysis has been carried out to discern the trend within the spatial distribution of the tropospheric ozone, and it has been observed that in all seasons, except monsoon (JJAS), there is a linear trend within the spatial distribution. Studying both monthly and seasonal behavior through autoregressive integrated moving average (ARIMA), it has been revealed that ARIMA (0,2,2) can be used as a representative of the spatially distributed tropospheric ozone over southern and northern hemispheres. The representative model has been confirmed through the study of Willmott's index and prediction yield.

引用

页码：321 / 328

页数：8

共 61 条

[1] Performance of GCMs for seasonal prediction over India-a case study for 2009 monsoon [J].

Acharya, Nachiketa ;

Kar, Sarat C. ;

Mohanty, U. C. ;

Kulkarni, Makarand A. ;

Dash, S. K. .

THEORETICAL AND APPLIED CLIMATOLOGY, 2011, 105 (3-4) :505-520

[2] On the altitude dependence of solar effective UV [J].

Alexandris, D ;

Varotsos, C ;

Kondratyev, KY ;

Chronopoulos, G .

PHYSICS AND CHEMISTRY OF THE EARTH PART C-SOLAR-TERRESTIAL AND PLANETARY SCIENCE, 1999, 24 (05) :515-517

[3] Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone [J].

Bandyopadhyay, G. ;

Chattopadhyay, S. .

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2007, 4 (01) :141-149

[4] Impacts of chemistry-aerosol coupling on tropospheric ozone and sulfate simulations in a general circulation model [J].

Bell, N ;

Koch, D ;

Shindell, DT .

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2005, 110 (D14) :1-12

[5]

Box G E. P., 2007, Time Series Analysis: Forecasting and Control, V4th

[6] ON THE DISPROPORTIONATE ROLE OF TROPOSPHERIC OZONE AS A FILTER AGAINST SOLAR UV-B RADIATION [J].

BRUHL, C ;

CRUTZEN, PJ .

GEOPHYSICAL RESEARCH LETTERS, 1989, 16 (07) :703-706

[7] SURFACE OZONE IN ATHENS, GREECE, AT THE BEGINNING AND AT THE END OF THE 20TH-CENTURY [J].

CARTALIS, C ;

VAROTSOS, C .

ATMOSPHERIC ENVIRONMENT, 1994, 28 (01) :3-8

[8] Univariate approach to the monthly total ozone time series over Kolkata, India: autoregressive integrated moving average (ARIMA) and autoregressive neural network (AR-NN) models [J].

Chattopadhyay, Goutami ;

Chattopadhyay, Surajit .

INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (03) :575-583

[9] Comparative study among different neural net learning algorithms applied to rainfall time series [J].

Chattopadhyay, Surajit ;

Chattopadhyay, Goutami .

METEOROLOGICAL APPLICATIONS, 2008, 15 (02) :273-280

[10] Prediction of mean monthly total ozone time series - application of radial basis function network [J].

Chattopadhyay, Surajit .

INTERNATIONAL JOURNAL OF REMOTE SENSING, 2007, 28 (18) :4037-4046

← 1 2 3 4 5 6 7 →