NDLI: Evaluating explanatory models of the spatial pattern of surface climate trends using model selection and bayesian averaging methods

Content Provider	Springer Nature Link
Author	McKitrick, Ross Tole, Lise
Copyright Year	2012
Abstract	We evaluate three categories of variables for explaining the spatial pattern of warming and cooling trends over land: predictions of general circulation models (GCMs) in response to observed forcings; geographical factors like latitude and pressure; and socioeconomic influences on the land surface and data quality. Spatial autocorrelation (SAC) in the observed trend pattern is removed from the residuals by a well-specified explanatory model. Encompassing tests show that none of the three classes of variables account for the contributions of the other two, though 20 of 22 GCMs individually contribute either no significant explanatory power or yield a trend pattern negatively correlated with observations. Non-nested testing rejects the null hypothesis that socioeconomic variables have no explanatory power. We apply a Bayesian Model Averaging (BMA) method to search over all possible linear combinations of explanatory variables and generate posterior coefficient distributions robust to model selection. These results, confirmed by classical encompassing tests, indicate that the geographical variables plus three of the 22 GCMs and three socioeconomic variables provide all the explanatory power in the data set. We conclude that the most valid model of the spatial pattern of trends in land surface temperature records over 1979–2002 requires a combination of the processes represented in some GCMs and certain socioeconomic measures that capture data quality variations and changes to the land surface.
Starting Page	2867
Ending Page	2882
Page Count	16
File Format	PDF
ISSN	09307575
Journal	Climate Dynamics
Volume Number	39
Issue Number	12
e-ISSN	14320894
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-06-15
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	GCM testing Spatial trend patterns Climate data contamination, spatial autocorrelation Non-nested tests Encompassing tests Bayesian model averaging Geophysics/Geodesy Oceanography Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing

A European pattern climatology 1766–2000

Spatial grids for hurricane climate research

Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations

Critical influence of the pattern of Tropical Ocean warming on remote climate trends

SST and circulation trend biases cause an underestimation of European precipitation trends

Climate simulations based on a different-grid nested and coupled model

GCM intercomparison of global cloud regimes: present-day evaluation and climate change response

The impact of lateral boundary data errors on the simulated climate of a nested regional climate model

Evaluating explanatory models of the spatial pattern of surface climate trends using model selection and bayesian averaging methods

Similar Documents

Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing

A European pattern climatology 1766–2000

Spatial grids for hurricane climate research

Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations

Critical influence of the pattern of Tropical Ocean warming on remote climate trends

SST and circulation trend biases cause an underestimation of European precipitation trends

Climate simulations based on a different-grid nested and coupled model

GCM intercomparison of global cloud regimes: present-day evaluation and climate change response

The impact of lateral boundary data errors on the simulated climate of a nested regional climate model

Evaluating explanatory models of the spatial pattern of surface climate trends using model selection and bayesian averaging methods