MRI_CGCM3: MRI-CGCM3 temperature and forcing dataset.

In eirikmn/INLA.climate: Full Bayesian analysis of radiative forcing climate model

MRI-CGCM3 temperature and forcing dataset.

Description

This is the MRI-CGCM3 temperature dataset. Also includes radiative forcing data obtained by combining the MRI-CGCM3 forcing data from Forster et al. (2013) and Hansen et al. (2010) such that the 18-yr moving averages are equal. The forcing slope coefficient when assuming a 1% annual increase of CO2, which is used to estimate the TCR, is 3.2.

Usage

data(MRI_CGCM3)

Format

The data is a list that contains these objects:

Year

Time index denoting the year of the observations.

Temperature

Annual global mean surface temperature.

Forcing

Annual adjusted radiative forcing.

References

Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Tanaka, T. Y., Shindo, E., Tsujino, H., Deushi, M., Mizuta,465R., Yabu, S., Obata, A., Nakano, H., Koshiro, T., Ose, T., and Kitoh, A. 2012: A New Global Climate Model of the Meteorological ResearchInstitute: MRI-CGCM3 –Model Description and Basic Performance–, J. Meteorolog. Soc. Jpn. Ser. II, 90A, 23–64.

Hansen, J. and Ruedy, R. and Sato, M. and and Lo, K. 2010: Global surface temperature change, Rev. Geophys., 48, RG4004, doi:10.1029/2010RG000345.

Forster, P. M., T. Andrews, P. Good, J. M. Gregory, L. S. Jackson, and M. Zelinka, 2013: Evaluating adjusted forcing and modelspread for historical and future scenarios in the cmip5 generation of climate models. Journal of Geophysical Research: Atmo-spheres, 118 (3), 1139–1150, doi:10.1002/jgrd.50174

Examples

# Load data
data(MRI_CGCM3, package = "INLA.climate")

#Plot temperature
plot(MRI_CGCM3$Year,MRI_CGCM3$Temperature)

#Plot forcing
plot(MRI_CGCM3$Year,MRI_CGCM3$Forcing)

eirikmn/INLA.climate documentation built on Feb. 6, 2023, 11:41 a.m.