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Why is climate sensitivity to polar radiative forcings larger than to tropical radiative forcings
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Several previous studies have shown that the climate sensitivity (global mean temperature change per unit global mean radiative forcing) to external forcing is larger for forcing that is concentrated in higher latitudes than in lower latitudes. This is due to differences in radiative feedback processes accompanying the surface temperature change and amplifying the climate change.  The present study investigates the cause for the larger climate sensitivity to radiative forcing imposed in polar regions as compared to lower latitudes using a climate modelling framework. We use the NCAR CAM4 model coupled to a slab ocean model and make a systematic quantitative comparison of the individual climate feedbacks (water vapor, Planck, lapse rate, albedo, and cloud) for three experiments in which we increase the solar insolation separately in three latitude bands:  60°N to 90°N (Arctic case), 20°S to 20°N (Tropical case), and 90°S to 60°S (Antarctic case). The global mean radiative forcing is nearly the same (~4.1 Wm-2) in the three cases. Our results show that the climate sensitivity, which varies inversely with the feedback parameter, is nearly twice and thrice the tropical case for the Arctic and Antarctic cases, respectively. The differences arise mostly due to water vapor, lapse rate, and cloud feedbacks, which vary significantly in the three cases (Table 1). Planck feedback does not vary much among the cases (-2.77, -3.05, -2.81 Wm-2K-1 for the Arctic, Tropical, and Antarctic simulation, respectively), but the albedo feedback is twice for the Arctic (0.5 Wm-2K-1) case when compared to the  tropical (0.23 Wm-2K-1) and Antarctic (0.20 Wm-2K-1) cases. Understanding climate response to latitudinally varying radiative forcing patterns is valuable for understanding the effects of solar radiation modification (SRM) techniques which have been proposed as a potential option to offset global warming effects of increased atmospheric CO2 concentrations. Our study indicates that the lapse rate, water vapor, and cloud feedbacks, and hence the total climate sensitivity, could strongly depend on the region of changed insolation in SRM approaches. Table 1. The annual average effective radiative forcing, global average surface temperature change, climate sensitivity (calculated as the ratio of surface temperature change and the radiative forcing), the albedo, Planck, lapse rate, water vapor, and cloud feedbacks for the ‘Arctic’, ‘Tropical’, and ‘Antarctic’ experiments. The baseline simulation is a  preindustrial simulation with a CO2 concentration of 284.7 ppm and solar constant of 1361 W m-2.
 
Arctic
Tropical
Antarctic
Radiative forcing (Wm-2)
4.16
4.17
4.05
Surface temperature change (K)
4.04
1.74
5.14
Climate sensitivity (K/Wm-2)
0.97
0.42
1.27
Albedo feedback (Wm-2K-1)
0.51
0.23
0.20
Planck feedback (Wm-2K-1)
-2.79
-3.07
-2.82
Lapse rate feedback (Wm-2K-1)
0.38
-0.93
0.01
Water vapor feedback (Wm-2K-1)
0.92
1.86
1.01
Cloud feedback (Wm-2K-1)
0.16
-0.41
0.38
 
Title: Why is climate sensitivity to polar radiative forcings larger than to tropical radiative forcings
Description:
Several previous studies have shown that the climate sensitivity (global mean temperature change per unit global mean radiative forcing) to external forcing is larger for forcing that is concentrated in higher latitudes than in lower latitudes.
This is due to differences in radiative feedback processes accompanying the surface temperature change and amplifying the climate change.
 The present study investigates the cause for the larger climate sensitivity to radiative forcing imposed in polar regions as compared to lower latitudes using a climate modelling framework.
We use the NCAR CAM4 model coupled to a slab ocean model and make a systematic quantitative comparison of the individual climate feedbacks (water vapor, Planck, lapse rate, albedo, and cloud) for three experiments in which we increase the solar insolation separately in three latitude bands:  60°N to 90°N (Arctic case), 20°S to 20°N (Tropical case), and 90°S to 60°S (Antarctic case).
The global mean radiative forcing is nearly the same (~4.
1 Wm-2) in the three cases.
Our results show that the climate sensitivity, which varies inversely with the feedback parameter, is nearly twice and thrice the tropical case for the Arctic and Antarctic cases, respectively.
The differences arise mostly due to water vapor, lapse rate, and cloud feedbacks, which vary significantly in the three cases (Table 1).
Planck feedback does not vary much among the cases (-2.
77, -3.
05, -2.
81 Wm-2K-1 for the Arctic, Tropical, and Antarctic simulation, respectively), but the albedo feedback is twice for the Arctic (0.
5 Wm-2K-1) case when compared to the  tropical (0.
23 Wm-2K-1) and Antarctic (0.
20 Wm-2K-1) cases.
Understanding climate response to latitudinally varying radiative forcing patterns is valuable for understanding the effects of solar radiation modification (SRM) techniques which have been proposed as a potential option to offset global warming effects of increased atmospheric CO2 concentrations.
Our study indicates that the lapse rate, water vapor, and cloud feedbacks, and hence the total climate sensitivity, could strongly depend on the region of changed insolation in SRM approaches.
 Table 1.
The annual average effective radiative forcing, global average surface temperature change, climate sensitivity (calculated as the ratio of surface temperature change and the radiative forcing), the albedo, Planck, lapse rate, water vapor, and cloud feedbacks for the ‘Arctic’, ‘Tropical’, and ‘Antarctic’ experiments.
The baseline simulation is a  preindustrial simulation with a CO2 concentration of 284.
7 ppm and solar constant of 1361 W m-2.
 
Arctic
Tropical
Antarctic
Radiative forcing (Wm-2)
4.
16
4.
17
4.
05
Surface temperature change (K)
4.
04
1.
74
5.
14
Climate sensitivity (K/Wm-2)
0.
97
0.
42
1.
27
Albedo feedback (Wm-2K-1)
0.
51
0.
23
0.
20
Planck feedback (Wm-2K-1)
-2.
79
-3.
07
-2.
82
Lapse rate feedback (Wm-2K-1)
0.
38
-0.
93
0.
01
Water vapor feedback (Wm-2K-1)
0.
92
1.
86
1.
01
Cloud feedback (Wm-2K-1)
0.
16
-0.
41
0.
38
 .
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