Correction to “Temperature dependent climate projection deficiencies in CMIP5 models”

Authors

  • Jens H. Christensen,

    Corresponding author
    1. Danish Climate Centre, Danish Meteorological Institute, Copenhagen, Denmark
    • Corresponding author: J. H. Christensen, Danish Climate Centre, Danish Meteorological Institute, Lyngbyvej 100, DK-2100 Copenhagen Ø, Denmark. (jhc@dmi.dk)

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  • Fredrik Boberg

    1. Danish Climate Centre, Danish Meteorological Institute, Copenhagen, Denmark
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Errata

This article corrects:

  1. Temperature dependent climate projection deficiencies in CMIP5 models Volume 39, Issue 24, Article first published online: 28 December 2012

[1] In the paper “Temperature dependent climate projection deficiencies in CMIP5 models” by Christensen and Boberg (Geophys. Res. Lett., 39, L24705, doi:10.1029/2012GL053650, 2012), Figure 2 has incorrect values for the temperature change on the y axis for regions 6–10, 15–17, 20, 21, and 23–26. This also affects Table 2 and Figure S2 for the regions in question (Table 1 and Figure 1).

Table 1. Regional Statistics Extracted From Figure 1a
 Slope [°C]ΔT Slope = 0σΔT Slope = 0math formulaσΔT1 – ΔT0/ math formula
  • a

    First column lists the region. The second column gives the slope of the linear fits shown in the figures; first value for the near future and the second value for the far future. Slopes statistically different from zero (at the 95% confidence level) are shown in bold. The third and fourth columns list temperature changes deduced from the potential model with no differential temperature bias (curve parallel to the diagonal in Figure 1 and hence represented by a zero value on the horizontal axes in Figure 2) and associated standard deviations, respectively. The fifth and sixth columns give the ensembles mean temperature change and standard deviations, irrespectively the value on the horizontal axis. The seventh column shows the relative reduction (in percent) in the regional warming, where bold faced numbers represent changes statistically significant at the 95% confidence level.

11.51/3.041.95/3.030.60/0.932.07/3.280.60/0.966.0/7.7
20.42/2.072.14/3.220.66/1.052.18/3.400.63/1.041.7/5.2
32.45/3.881.58/2.590.38/0.611.97/3.210.54/0.8619.9/19.4
42.14/3.141.85/2.970.46/0.742.05/3.260.54/0.869.9/9.1
54.00/7.341.88/2.970.50/0.772.00/3.190.57/0.935.9/6.8
60.28/0.661.58/2.520.35/0.571.60/2.560.34/0.561.1/1.6
70.27/0.321.40/2.440.48/0.851.80/2.910.52/0.8622.2/16.1
80.21/0.371.26/1.990.31/0.561.58/2.570.30/0.5520.3/22.4
9–0.15/–0.321.41/2.280.29/0.471.40/2.250.28/0.46–0.8/–1.2
10–2.41/–3.151.49/2.430.47/0.761.37/2.260.50/0.79–9.1/–7.2
111.35/2.311.77/2.680.65/0.961.99/3.050.65/0.9810.8/12.1
121.77/3.041.72/2.490.58/0.822.06/3.090.65/0.9716.9/19.4
132.17/3.831.80/2.780.54/0.782.09/3.300.62/0.9513.9/15.6
140.96/1.941.71/2.550.47/0.681.99/3.120.48/0.7514.1/18.2
150.75/0.961.69/2.730.32/0.581.55/2.540.34/0.589.4/–7.3
160.03/0.091.52/2.450.28/0.471.52/2.450.27/0.460.1/0.3
17–0.04/–0.031.69/2.690.34/0.531.68/2.690.33/0.52–0.2/–0.1
181.51/2.712.09/3.280.77/1.182.23/3.520.75/1.156.1/7.0
191.84/3.181.73/2.660.47/0.692.09/3.300.55/0.8517.5/19.2
201.75/2.951.87/2.980.52/0.752.09/3.350.61/0.9310.4/11.0
211.74/3.071.72/2.690.51/0.762.04/3.260.58/0.9215.8/17.4
221.40/4.161.57/2.410.47/0.701.70/2.800.47/0.797.8/14.2
230.74/1.311.16/1.910.28/0.471.44/2.420.34/0.5919.6/20.8
240.10/0.201.26/1.990.32/0.531.31/2.090.31/0.514.0/5.2
251.66/2.881.34/2.160.32/0.501.53/2.500.41/0.6712.6/13.4
260.35/1.221.30/2.080.30/0.521.32/2.160.29/0.521.7/3.6
Figure 1.

Projected temperature change for the 50% warmest months given as a function of temperature bias slope for 26 subregions. Blue symbols represent temperature change for 2021–2050 relative to 1961–2000, whereas the red symbols denote temperature change for 2071–2100 relative 1961–2000. The temperature bias slope is defined as the slope Tbias/Tobs relative to the diagonal for the 50% warmest months extracted from Figure 1 in Christensen and Boberg, 2012. Linear fits are added to each subregion. The inserted crosses for each panel represent an estimate of the associated standard deviation for the individual models.

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