Köppen bioclimatic evaluation of CMIP historical climate simulations

Köppen bioclimatic classification relates generic vegetation types to characteristics of the interactive annual-cycles of continental temperature (T) and precipitation (P). In addition to predicting possible bioclimatic consequences of past or prospective climate change, a Köppen scheme can be used...

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Bibliographic Details
Published in:Environmental research letters 2015-06, Vol.10 (6), p.64005
Main Authors: Phillips, Thomas J, Bonfils, Céline J W
Format: Article
Language:English
Subjects:
bioclimate
Bioclimatology
Biometeorology
Climate change
Climate models
CMIP
ENVIRONMENTAL SCIENCES
Hydrologic data
Köppen
metrics
Performance measurement
Precipitation
Simulation
simulations
Vegetation
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Summary:Köppen bioclimatic classification relates generic vegetation types to characteristics of the interactive annual-cycles of continental temperature (T) and precipitation (P). In addition to predicting possible bioclimatic consequences of past or prospective climate change, a Köppen scheme can be used to pinpoint biases in model simulations of historical T and P. In this study a Köppen evaluation of Coupled Model Intercomparison Project (CMIP) simulations of historical climate is conducted for the period 1980-1999. Evaluation of an example CMIP5 model illustrates how errors in simulating Köppen vegetation types (relative to those derived from observational reference data) can be deconstructed and related to model-specific temperature and precipitation biases. Measures of CMIP model skill in simulating the reference Köppen vegetation types are also developed, allowing the bioclimatic performance of a CMIP5 simulation of T and P to be compared quantitatively with its CMIP3 antecedent. Although certain bioclimatic discrepancies persist across model generations, the CMIP5 models collectively display an improved rendering of historical T and P relative to their CMIP3 counterparts. In addition, the Köppen-based performance metrics are found to be quite insensitive to alternative choices of observational reference data or to differences in model horizontal resolution.
ISSN:1748-9326
1748-9326
DOI:10.1088/1748-9326/10/6/064005