Semiparametric Estimation and Testing of the Trend of Temperature Series

The application of a partially linear model to global and hemispheric temperature series is proposed. Partially linear modelling allows the trend to take a very general form rather than imposing the restriction of linearity seen in existing studies. The removal of the linearity restriction is based on the fact that it is well accepted that a significant trend is present in global temperature series. The model will allow for the data to "speak for themselves" with regard to the form of the trend. The results initially reveal that a linear trend does not approximate well the behaviour of global or hemispheric temperature series. This is further confirmed through a formal testing procedure. Copyright Royal Economic Society 2006

[1]  P. Anglin,et al.  SEMIPARAMETRIC ESTIMATION OF A HEDONIC PRICE FUNCTION , 1996 .

[2]  Henry L. Gray,et al.  Selecting a Model for Detecting the Presence of a Trend , 1995 .

[3]  Xiaogu Zheng,et al.  Structural Time Series Models and Trend Detection in Global and Regional Temperature Series , 1999 .

[4]  P. Bloomfield Trends in global temperature , 1992 .

[5]  Henry L. Gray,et al.  Global warming and the problem of testing for trend in time series data , 1993 .

[6]  P. Jones,et al.  The influence of ENSO on global temperatures , 1989 .

[7]  J. Zheng,et al.  A consistent test of functional form via nonparametric estimation techniques , 1996 .

[8]  F. H. Schweingruber,et al.  Influence of volcanic eruptions on Northern Hemisphere summer temperature over the past 600 years , 1998, Nature.

[9]  P. Robinson ROOT-N-CONSISTENT SEMIPARAMETRIC REGRESSION , 1988 .

[10]  R. Sepanski,et al.  TRENDS '90: A compendium of data on global change , 1991 .

[11]  Gordon R. Richards Change in Global Temperature: A Statistical Analysis , 1993 .

[12]  Xiaogu Zheng,et al.  Trend Detection in Regional-Mean Temperature Series: Maximum, Minimum, Mean, Diurnal Range, and SST , 1997 .

[13]  David Parker,et al.  Interdecadal changes of surface temperature since the late nineteenth century , 1994 .

[14]  J. Räisänen CO2-Induced Changes in Interannual Temperature and Precipitation Variability in 19 CMIP2 Experiments , 2002 .

[15]  John J. Seater World Temperature-Trend Uncertainties and Their Implications for Economic Policy , 1993 .

[16]  B. Dawson,et al.  INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) , 2008 .

[17]  J. Molenaar,et al.  Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter , 1995 .

[18]  T. Wigley,et al.  Reasons for Larger Warming Projections in the IPCC Third Assessment Report , 2002 .

[19]  J. Houghton,et al.  Climate change 1995: the science of climate change. , 1996 .

[20]  Thomas B. Fomby,et al.  NOTES AND CORRESPONDENCE The Application of Size-Robust Trend Statistics to Global-Warming Temperature Series , 2002 .

[21]  Joel L. Horowitz,et al.  An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative , 2001 .

[22]  Zhijie Xiao,et al.  A nonparametric test for changing trends , 2005 .

[23]  J. Houghton,et al.  Climate change 1992 : the supplementary report to the IPCC scientific assessment , 1992 .

[24]  T. V. Ommen,et al.  Observed climate variability and change , 2002 .

[25]  Leonard M. Adleman,et al.  Proof of proposition 3 , 1992 .

[26]  Francis W. Zwiers,et al.  Detection of climate change and attribution of causes , 2001 .

[27]  J. Hansen,et al.  Global trends of measured surface air temperature , 1987 .

[28]  Qi Li,et al.  Consistent model specification tests for time series econometric models , 1999 .

[29]  Chris D. Jones,et al.  The Carbon Cycle Response to ENSO: A Coupled Climate–Carbon Cycle Model Study , 2001 .

[30]  R. McKitrick The Search for Warming in Global Temperatures: Data, Methods and Unresolved Questions , 2001 .

[31]  E. Mammen,et al.  Comparing Nonparametric Versus Parametric Regression Fits , 1993 .

[32]  J. Beersma,et al.  A Simple Test for Equality of Variances in Monthly Climate Data , 1999 .

[33]  Zong-ci Zhao,et al.  Climate change 2001, the scientific basis, chap. 8: model evaluation. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change IPCC , 2001 .

[34]  W. Härdle,et al.  Kernel regression smoothing of time series , 1992 .

[35]  Adaptive estimation in partially linear autoregressive models , 2000 .

[36]  Clive W. J. Granger,et al.  Semiparametric estimates of the relation between weather and electricity sales , 1986 .

[37]  Y. Chen [The change of serum alpha 1-antitrypsin level in patients with spontaneous pneumothorax]. , 1995, Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases.

[38]  Wolfgang Härdle,et al.  Partially Linear Models , 2000 .

[39]  Jiti Gao,et al.  Nonlinear Time Series: Semiparametric and Nonparametric Methods , 2019 .

[40]  P. Jones,et al.  The Effect of Urban Warming on the Northern Hemisphere Temperature Average , 1989 .

[41]  Yongmiao Hong,et al.  Consistent Specification Testing via Nonparametric Series Regression , 1995 .

[42]  Suojin Wang,et al.  A simple consistent bootstrap test for a parametric regression function , 1998 .