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What can we learn about climate feedbacks from short-term climate variations? Cover

What can we learn about climate feedbacks from short-term climate variations?

Tellus
Volume 65 (2013): Issue 1
By:   
Open Access
|Dec 2013
Figures & tables

Figures & Tables

Table 1. List of the CMIP3 models used in this study. The models with asterisk in their name have included volcanic forcing in their 20C3M experiments

Number Model name Originating group Country 1 ccma_cgcm3_1 Canadian Centre for Climate Modeling and Analysis Canada 2 cnrm_cm3 Centre National de Recherches Météorologiques (Météo France) France 3 gfdl_cm2_0* Geophysical Fluid Dynamics Laboratory (NOAA) USA 4 gfdl_cm2_1* Geophysical Fluid Dynamics Laboratory (NOAA) USA 5 giss_model_e_h* Goddard Institute for Space Studies (NASA) USA 6 giss_model_e_r* Goddard Institute for Space Studies (NASA) USA 7 inmcm3_0* Institute of Numerical Mathematics Russia 8 ispl_cm4 Institut Pierre Simon Laplace France 9 miroc3_2_hires* Center for Climate System Research Japan 10 miroc3_2_medres* Center for Climate System Research Japan 11 mpi_echam5 Max Planck Institute for Meteorology Germany 12 mri_cgcm2_3_2a* Meteorological Research Institute Japan 13 ncar_ccsm3_0* National Center for Atmospheric Research USA

Table 2. Global average CMIP3 multi-model mean (MM) feedbacks and interdecile range (IDR: the difference between the 90th and the 10th percentile of the model estimates) calculated based on long-term and short-term climate variability (see text for details). Results are also shown for the ERA-Interim, JRA-25 re-analyses. For the short-term feedbacks, the 2σ least squares fit uncertainty is indicated, as well. Units are Wm2K−1

Planck response Lapse rate Water vapour Surface albedo Cloud Net a) Long-term  CMIP3 MM (2101–2130) vs (1970–2000) −3.24 −0.84 1.88 0.27 0.56 −1.36  IDR 0.09 0.72 0.51 0.21 1.04 1.06 b) Short-term  CMIP3 MM±2σ ‘20C’ (1970–2000) −3.18±0.04 −0.58±0.19 1.78±0.15 0.22±0.06 0.73±0.30 −1.03±0.39  IDR 0.19 1.07 1.11 0.38 1.36 1.46  ERA-Interim (1979–2009) −2.96±0.04 0.11±0.16 0.86±0.14 0.12±0.04 0.33±0.82* −1.54±0.85  JRA-25 (1979–2009) −3.15±0.04 0.34±0.20 1.37±0.16 0.20±0.06 0.86±1.10* −0.38±1.13

[i] *Calculated over the period 2001–2009.

Fig. 1. 

Global maps of all the radiative feedbacks (Planck, lapse rate, water vapour, surface albedo, cloud and net) of the CMIP3 multi-model mean, calculated based on their response from long-term climate changes due to the increase in greenhouse gas forcing. Units are in Wm−2K−1.

Fig. 2. 

Global maps of all the radiative feedbacks of the CMIP3 multi-model mean calculated based on their response from short-term climate variability. Units are in Wm−2K−1.

Fig. 3. 

Global maps of the long-term (left panels) and short-term (right panels) cloud (longwave, shortwave and net) feedbacks. Units are in Wm−2K−1.

Fig. 4. 

Radiative feedbacks (Planck, water vapour, lapse-rate, the combined water vapour plus lapse-rate feedback, surface albedo, cloud and net), computed for each of the CMIP3 models (in grey) and the multi-model mean (in black) for the long-term climate change experiments. The CMIP3 models and multi-model mean feedbacks (and their 2σ confidence intervals) computed based on the short-term variations are denoted in pink and black dots, respectively. Results from the ERA-Interim and JRA-25 re-analyses are shown in blue and green, respectively. Units are in Wm−2K−1.

Fig. 5. 

Global maps of the interdecile range of the CMIP3 models for the long-term feedbacks. Units are in Wm−2K−1.

Fig. 6. 

Global maps of the interdecile range of the CMIP3 models for the short-term feedbacks. Units are in Wm−2K−1.

Table 3. Global average feedbacks (model mean and interdecile range) calculated for only three of the CMIP3 models with the most realistic ENSO representation (Oldenborgh et al., 2005), (gfdl_cm2_1, 9: miroc3_2_hires, 11: mpi_echam5: see text). Units are Wm2K−1

Subset of CMIP3 models Planck response Lapse rate Water vapour Surface albedo Cloud Net a) Long-term  MM (2101–2130) vs (1970–2000) −3.24 −0.91 1.90 0.30 0.56 −1.45  IDR 0.02 0.25 0.26 0.09 0.71 0.80 b) Short-term  Subset MM±2σ ‘20C’ (1970–2000) −3.22±0.04 −0.75±0.18 1.87±0.13 0.32±0.06 0.66±0.36 −1.11±0.62  IDR (subset) 0.10 0.64 0.58 0.15 0.73 0.83

Table 4. Global average multi-model mean (MM) feedbacks (in Wm2K−1), interdecile range (IDR) and correlation in respect to the ‘20C’ feedbacks, calculated based on the ‘AMIP’ (atmosphere-only) climate simulations

AMIP simulations (1980–2000) Planck response Lapse rate Water vapour Surface albedo Cloud Net MM −3.17 −0.69 1.74 0.21 0.47 −1.44 IDR 0.27 0.98 0.85 0.17 2.59 2.78 Correlation coefficient 0.24 0.51 0.60 0.50 0.83 0.76

[i] Results are based on 9 models (see A.3 in the Appendix).

Table 5. Global average multi-model mean (MM) feedbacks (in Wm2K−1) and interdecile range (IDR) calculated based on the ‘20C’ CMIP3 climate simulations for three different time periods

Planck response Lapse rate Water vapour Surface albedo Cloud Net ‘20C’ MM, IDR 1990–2000 −3.19, 0.52 −0.64, 2.05 1.79, 1.96 0.22, 0.31 0.27, 3.36 −1.55, 4.05 1970–2000 −3.18, 0.19 −0.58, 1.07 1.78, 1.11 0.22, 0.38 0.73, 1.36 −1.03, 1.46 1950–2000 −3.19, 0.15 −0.65, 0.84 1.82, 1.21 0.22, 0.31 0.71, 1.15 −1.10, 1.44
Fig. 7. 

Latitudinal variation of the short-term, feedbacks for the CMIP3 multi-model mean (black line) and the ERA-Interim (in orange) and JRA-25 (in green) reanalyses. The grey shaded area denotes the CMIP3 inter-model spread. Notice that the cloud feedbacks have been computed using both re-analyses and satellite CERES top of the atmosphere radiation fluxes (see text for details) for the period from 2001 to 2009. Units are in Wm−2K−1.

Table A.1 Global average “long-term” climate feedbacks (in Wm2K−1) for each of the CMIP3 models

GHG Models Planck response Lapse rate Water vapour Surface albedo Cloud Net 1 ccma_cgcm3_1 −3.25 −1.06 2.12 0.30 0.91 −0.98 2 cnrm_cm3 −3.25 −0.91 1.96 0.28 0.67 −1.25 3 gfdl_cm2_0 −3.22 −0.79 1.91 0.35 0.12 −1.63 4 gfdl_cm2_1 −3.25 −1.04 2.07 0.24 0.12 −1.86 5 giss_model_e_h −3.29 −1.14 2.00 0.07 0.51 −1.84 6 giss_model_e_r −3.28 −1.09 1.95 0.15 0.57 −1.70 7 inmcm3_0 −3.19 −0.37 1.59 0.35 0.26 −1.35 8 ispl_cm4 −3.26 −0.78 1.84 0.25 1.16 −0.80 9 miroc3_2_hires −3.23 −0.73 1.74 0.35 1.01 −0.86 10 miroc3_2_medres −3.23 −0.77 1.72 0.30 0.9 −1.08 11 mpi_echam5_run1 −3.23 −0.95 1.9 0.31 0.54 −1.43 12 mri_cgcm2_3_2a_run1 −3.23 −0.75 2.01 0.24 0.54 −1.2 13 ncar_ccsm3_0_run1 −3.19 −0.51 1.61 0.36 −0.01 −1.75

Table A.2. Global average “short-term” climate feedbacks (in Wm2K−1) and their 2σ least squares fit uncertainty, for each of the CMIP3 models

ENSO Models Planck response Lapse rate Water vapour Surface albedo Cloud Net 1 ccma_cgcm3_1 −3.17±0.04 −0.74±0.12 1.99±0.10 0.11±0.06 0.90±0.16 −0.90±0.24 2 cnrm_cm3 −3.34±0.04 −1.11±0.22 2.45±0.18 0.01±0.06 1.35±0.26 −0.64±0.43 3 gfdl_cm2_0 −3.12±0.04 −0.23±0.18 1.45±0.12 0.45±0.08 0.07±0.26 −1.38±0.36 4 gfdl_cm2_1 −3.23±0.04 −0.66±0.18 1.86±0.12 0.29±0.06 0.21±0.24 −0.52±0.34 5 giss_model_e_h −3.20±0.04 −0.46±0.16 1.68±0.12 0.15±0.04 0.32±0.26 −0.51±0.34 6 giss_model_e_r −3.14±0.04 −0.30±0.16 1.08±0.14 0.07±0.04 0.16±0.32 −2.13±0.40 7 inmcm3_0 −3.08±0.04 −0.04±0.16 1.50±0.14 0.28±0.06 0.72±0.30 −0.63±0.38 8 ispl_cm4 −3.20±0.04 −0.81±0.20 2.02±0.14 0.21±0.06 1.23±0.24 −0.55±0.38 9 miroc3_2_hires −3.15±0.04 −0.39±0.18 1.51±0.12 0.43±0.06 1.12±0.26 −0.48±0.34 10 miroc3_2_medres −3.15±0.04 −0.54±0.22 1.69±0.16 0.18±0.08 0.75±0.32 −1.06±0.44 11 mpi_echam5 −3.27±0.04 −1.19±0.18 2.24±0.14 0.24±0.06 0.66±0.30 −1.32±0.40 12 mri_cgcm2_3_2a −3.20±0.04 −0.76±0.18 2.30±0.20 0.07±0.06 1.52±0.44 −0.07±0.52 13 ncar_ccsm3_0 −3.14±0.04 −0.26±0.16 1.34±0.12 0.37±0.06 0.50±0.30 −0.19±0.38

Table A.3. Global average “short-term” climate feedbacks (in Wm2K−1) and their 2σ least squares fit uncertainty, computed based on the AMIP model simulations

ENSO Models Planck response Lapse rate Water vapour Surface albedo Cloud Net 1 cnrm_cm3 −3.16±0.06 −1.08±0.24 1.89±0.24 0.09±0.08 1.11±0.46 −1.16±0.58 2 gfdl_cm2_1 −3.2±0.06 −0.61±0.24 1.61±0.24 0.23±0.08 −0.76±0.46 −2.73±0.58 3 giss_model_e_r −3.29±0.06 −0.65±0.28 1.71±0.24 0.14±0.08 −0.07±0.32 −2.16±0.50 4 inmcm3_0 −3.02±0.06 −0.23±0.22 1.32±0.16 0.25±0.10 −0.15±0.36 −1.83±0.48 5 ipsl_cm4 −3.14±0.06 −0.34±0.42 1.68±0.30 0.26±0.10 0.32±0.40 −1.22±0.68 6 miroc3_2_hires −3.19±0.06 −1.21±0.48 1.92±0.26 0.18±0.08 1.05±0.40 −1.25±0.70 7 mpi_echam5 −3.16±0.04 −0.88±0.30 1.93±0.24 0.25±0.06 0.35±0.62 −1.52±0.74 8 mri_cgcm2_3_2a −3.28±0.06 −0.9±0.32 2.17±0.30 0.23±0.06 1.83±0.66 0.05±0.78 9 ncar_ccsm3_0 −3.1±0.08 −0.27±0.32 1.43±0.24 0.23±0.06 0.53±0.50 −1.18±0.66
DOI: https://doi.org/10.3402/tellusa.v65i0.18887 | Journal eISSN: 3035-9554
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Language: English
Page range: 18887 - 18887
Submitted on: May 3, 2012
Accepted on: Dec 1, 2012
Published on: Dec 1, 2013
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
feedbacks,
long-term,
ENSO,
climate change,
radiative kernels

© 2013 Symeon Koumoutsaris, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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