Statistical intercomparison of global climate models: A common principal component approach with application to GCM data

Technical Report · Sat May 01 04:00:00 UTC 1993

DOI:https://doi.org/10.2172/10173301· OSTI ID:10173301

Sengupta, S K; Boyle, J S

Variables describing atmospheric circulation and other climate parameters derived from various GCMs and obtained from observations can be represented on a spatio-temporal grid (lattice) structure. The primary objective of this paper is to explore existing as well as some new statistical methods to analyze such data structures for the purpose of model diagnostics and intercomparison from a statistical perspective. Among the several statistical methods considered here, a new method based on common principal components appears most promising for the purpose of intercomparison of spatio-temporal data structures arising in the task of model/model and model/data intercomparison. A complete strategy for such an intercomparison is outlined. The strategy includes two steps. First, the commonality of spatial structures in two (or more) fields is captured in the common principal vectors. Second, the corresponding principal components obtained as time series are then compared on the basis of similarities in their temporal evolution.

• Research Organization: Lawrence Livermore National Lab., CA (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 10173301
• Report Number(s): UCRL-ID--114222; ON: DE93017951
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
290301
54 ENVIRONMENTAL SCIENCES
540110
ATMOSPHERIC CIRCULATION
BASIC STUDIES
CLIMATE MODELS
CLIMATES
CLIMATIC CHANGE
COMPARATIVE EVALUATIONS
FORECASTING
GENERAL CIRCULATION MODELS
GLOBAL ASPECTS
REGIONAL AND GLOBAL ENVIRONMENTAL ASPECTS
TIME-SERIES ANALYSIS