Climate model description and simulations

Our model simulations exercise a standard configuration of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, v. 3.1, which includes a finite-volume dynamical core, a grid that is 2° in latitude by 2.5° in longitude, 26 vertical levels, an interactive land surface and a thermodynamic sea ice model (Collins et al. 2006). The land surface model computes fluxes of energy and water based on plant type and stomatal apertures adjusted to balance carbon assimilation by photosynthesis and water loss through evaporation. The sea ice model computes the local thermodynamic balances between heat fluxes and ice formation and melting, but does not include the movement of sea ice.

First, we simulated a control climate using specified observed sea surface temperatures (Levitus 1982). In this mode, we can diagnose the energy fluxes into and out of the ocean as calculated by the atmosphere model, and compute the implied ocean heat transport. Then we represent the surface of the ocean as a layer of water with varying thicknesses as specified by observed ocean mixed-layer depths. At the base of this layer, we apply the ocean heat transport computed earlier. In this way, sea surface temperatures can vary as a result of computed surface fluxes while specifying the ocean heat transport.

The only change made to the model code as distributed by NCAR was to allow for different spectrally neutral fractional reductions in incoming solar radiation in different latitude bands.

To explore the importance of non-linearities in the climate system related to the spatial scale and the amount of reduction of solar flux incident on the Earth, seven experimental and two control simulations were conducted with this modelling tool (Table 13.1). All simulations were run for 70 elapsed model years, with the first 40 years being discarded and the last 30 years being used to compute climate statistics.

The 1 x CO2 simulation is the control climate, with 280 ppm of CO2 in the atmosphere and the normal amount of sunshine. The 2 x CO2 simulation is with doubled atmospheric CO2 content climate and the normal amount of sunshine. The Global_1.84 has doubled atmospheric CO2 content, but with a uniform global 1.84 per cent reduction in solar radiation at the top of the atmosphere, approximately the amount needed to offset the global mean temperature effect of a doubling of atmospheric CO2 content. We then performed two more simulations focusing on the Arctic: one with a 10 per cent reduction in insolation north of 61° N (Arc-tic61_0.37) and the other with a 25 per cent reduction in insolation north of 71° N (Arctic71_0.37). Both of these cases deflect approximately 0.37 per cent of the global sunlight incident on the Earth. (To avoid a computational instability, the Global_1.84 simulation and a corresponding control simulation were performed

Table 13.1 Description of simulations. Simulations include two that differ only by CO2 amount ( 1 x CO2 and 2 x CO2), and simulations for a world with twice the CO2 in which solar insolation is decreased at various levels globally, or north of 61° N, or north of 71° N. Simulations are designed to differ from other simulations in only one respect.

Table 13.1 Description of simulations. Simulations include two that differ only by CO2 amount ( 1 x CO2 and 2 x CO2), and simulations for a world with twice the CO2 in which solar insolation is decreased at various levels globally, or north of 61° N, or north of 71° N. Simulations are designed to differ from other simulations in only one respect.

Global mean

Atmospheric CO2

insolation

Region of

Insolation reduction

concentration

reduction

insolation

in engineered region

Simulation

(ppm)

(%)

reduction

(%)

1 x CO2

28O

0

-

2 x CO2

56O

0

-

-

Arctic61_0.37

56O

0.37

61° N-90°

N

10

Arctic71_0.37

56O

0.37

71° N-90°

N

25

Global_1.84

56O

1.84

global

1.84

Global_0.73

56O

0.73

global

0.73

Arctic61_1.84

56O

1.84

61° N-90°

N

50

Arctic71_0.73

56O

0.73

71° N-90°

N

50

using ocean heat fluxes reduced by 10 per cent in nine (out of more than 9000) ocean grid cells, with the heat uptake redistributed zonally so as to preserve total meridional heat transport. The model represents a surface ocean layer at the base of which there is specified average ocean heat transport, based on simulations made with observed sea surface temperatures. This approach generally works well for simulations with increased radiative forcing, but for decreased radiative forcing situations can occur where the ocean heat transport is greater than what the atmosphere can easily supply, resulting in non-physical state with a very cold single grid cell near the Galapagos Islands. A 10 per cent tweak to the implied zonal heat transport in the cells neighbouring the 'bad' point was enough to 'fix' the problem.)

To explore non-linearities in the climate system, we performed additional simulations. For each of three pairs of simulations, the top-of-atmosphere solar insolation has been reduced by nearly the same amount, with the spatial distribution of this reduction differing for the two members of the pair (Table 13.1). For example, both the Arctic61_1.84 and Global_1.84 simulations have the top-of-atmosphere insolation reduced by 1.84 per cent (i.e. by 3.2 PW), but the Arctic61_1.84 simulation applies this reduction in insolation power only north of 61o N whereas the Global_1.84 simulation reduces insolation power by this same amount through a fractional reduction in incoming sunlight over the entire Earth.

mm = significant change at 0.05 level

1012345 6 7

temperature change (°C)

Figure 13.1 Annual mean temperature changes in the (a, b) 2 x CO2 and (c, d) GlobaL1.84 simulations. Shown are temperature changes from the 1 x CO2 cases (a, c) and areas where the temperature change is statistically significant at the 0.05 level (b, d). This idealized climate engineering simulation indicates that relatively simple climate engineering may be able to diminish temperature changes in most of the world (see also colour plate).

mm = significant change at 0.05 level

1012345 6 7

temperature change (°C)

Figure 13.1 Annual mean temperature changes in the (a, b) 2 x CO2 and (c, d) GlobaL1.84 simulations. Shown are temperature changes from the 1 x CO2 cases (a, c) and areas where the temperature change is statistically significant at the 0.05 level (b, d). This idealized climate engineering simulation indicates that relatively simple climate engineering may be able to diminish temperature changes in most of the world (see also colour plate).

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