Climate Feedback:  A process that acts to amplify or reduce direct warming or cooling effects.

A positive feedback causes a direct warming effect to heat the planet more than it would without the feedback.   Similarly, a positive feedback causes a direct cooling effect to cool the planet more than would be the case without the effect.  In contrast, a negative feedback acts to mitigate direct warming and direct cooling effects.   Negative feedbacks tend to stabilize a system whereas positive feedbacks tend to destabilize it.   The Earth’s climate system has both positive and negative feedbacks.  An example of a positive climate feedback is rising temperature causing polar ice to melt.  Ice reflects more sunlight than water.  As polar ice melts, the planet absorbs more heat than it did when more of its surface was covered in ice and snow, causing it heats more rapidly, which leads to faster melting of polar ice and snow, which causes it to heat more rapidly, etc.  An example of a negative climate feedback would be increasing temperature resulting in increased evaporation of surface water leading to a greater amount of low cloud cover.   The tops of low clouds are more reflective than vegetation (and pretty much every other terrestrial surface) so increased low cloud cover has the effect of cooling the planet.  (Unfortunately, whether increasing surface temperatures will actually lead to increased low cloud cover is TBD.   The rate at which heat is being retained in the atmosphere due to increasing CO2 concentration may be so great that it effectively disables the negative feedback we get from low clouds by inhibiting their formation.  If that’s the case then we’re in deep trouble.)

With that as background, here’s a short non-technical video which explains the concept of climate feedback – emphasis is on negative feedbacks, which tend to work in our favor:

In a rational world, people would believe or not believe in predictions of human-induced climate change on the basis of how well the climate models used to make those predictions account for past observations.  The details of what climate models do and don’t do well generally doesn’t get much public discussion though.  In the interest of getting that information into wider circulation, the Executive Summary of Chapter 9 of the IPCC Working Group I Assessment Report 5 (WG1AR5), Evaluation of Climate Models, follows below.  (The full report is here.)  It’s a self-assessment by climate modelers of what they do and don’t do well.  Note that statements are phrased to address advances in capability since the IPCC’s Fourth Assessment Report (AR4) was published in 2007.  Take 10 minutes.  It’s worth the read. If you’re in a hurry or just aren’t interested in the details (no harm in that) then just read the text in bold at the start of each paragraph.  If you’re unfamiliar with climate models then RealClimate.org’s “FAQ on climate models” might be worthwhile background reading.  It covers terminology and general characteristics of climate models.  Without further ado, the Executive Summary of Chapter 9 in its entirety:

Climate models have continued to be developed and improved since the AR4, and many models have been extended into Earth System models by including the representation of biogeochemical cycles important to climate change. These models allow for policy-relevant calculations such as the carbon dioxide (CO2) emissions compatible with a specified climate stabilization target. In addition, the range of climate variables and processes that have been evaluated has greatly expanded, and differences between models and observations are increasingly quantified using ‘performance metrics’. In this chapter, model evaluation covers simulation of the mean climate, of historical climate change, of variability on multiple time scales and of regional modes of variability. This evaluation is based on recent internationally coordinated model experiments, including simulations of historic and paleo climate, specialized experiments designed to provide insight into key climate processes and feedbacks and regional climate downscaling. Figure 9.44 provides an overview of model capabilities as assessed in this chapter, including improvements, or lack thereof, relative to models assessed in the AR4. The chapter concludes with an assessment of recent work connecting model performance to the detection and attribution of climate change as well as to future projections. {9.1.2, 9.8.1, Table 9.1, Figure 9.44}

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From Ray Pierrehumbert‘s post at RealClimate several years ago, Keystone XL:  Game Over? (emphasis mine):