 Okay, here is our one-layer energy balance model. Right now it's set for the default settings of the various feedback factors. The cloud feedback factor is set at a modestly negative value of minus 0.83. The water vapor feedback factor is 2, and the ice albedo feedback factor is 0.5. So these two, the water vapor feedback and the ice albedo feedback, are set at positive values. The cloud radiative feedback is set at a negative value, and these values are roughly equal to the best current estimates of what those feedback factors are. And so using those default settings gives us sort of a mid-range climate sensitivity, and you'll look at that in your problem set. So you can calculate the climate sensitivity, of course, by varying the CO2, and the CO2 can be varied with this lever here. Pre-industrial levels 280 parts per million, obviously 560 ppm is twice pre-industrial. If you like, you can even set values outside these ranges by going to the box down below. For example, I could set the CO2 level at 700 ppm, and we can see the initial temperature, surface temperature 288 k, for the standard default settings. The new surface temperature 292, that was a 4.1 degree warming of the surface. The atmosphere itself, the mid-troposphere, warmed somewhat less, 3.4 k. We can see what the long wave and the short wave forcings are. So these are estimates of the radiative forcing due to the combination of the direct influence of changing the CO2 levels, plus the various feedbacks. The water vapor feedback increasing the greenhouse gas concentration, giving us long wave forcing that adds to the long wave forcing from the increase in CO2 alone. The ice albedo feedback playing into the short wave forcing, the cloud radiative feedback can influence both the combination of short wave and long wave forcing. There's the cloud albedo effect, which tends to be a negative feedback, but there's also the greenhouse gas-like properties of clouds, the infrared-absorbing properties of clouds, which gives us a positive feedback. And as we vary this feedback factor, we can transition from where the negative cloud radiative feedbacks dominate to where the positive cloud feedbacks dominate. We can see how the albedo changes as we vary the short wave feedbacks. We can see how the atmospheric emissivity changes. For example, as we change the CO2 level, the default emissivity in this model being 0.77, the value that gives us a surface temperature of about 288K, the current best estimate of Earth's surface temperature. Finally, if we like, we can vary the solar constant. We can vary the initial albedo, Earth's planetary albedo, which will of course be modified as we change some of the feedback factors. So that's how it works. You're going to explore this model further in your problem set.