Putting clouds into climate models is not simple, because the more the temperature rises, the more water evaporates, creating more clouds that reflect more sunlight back out into space. Such facts are well known, but reducing them to a specific and reliable formula that will predict global temperatures is something else.

Except for the fact that it's primarily low altitude clouds that reflect more sunlight; high altitude clouds actually help trap more heat. That's actually the big challenge in cloud modeling, as I understand it; understanding which type of clouds will predominate in response to future conditions, although it seems there have been some recent advances in our understanding of how clouds work, allowing more sophisticated and accurate models of these processes. And in fact, chapter 7 of the IPCC AR5 WG1 report states:

"Based on the preceding synthesis of cloud behaviour, the net radiative feedback due to all cloud types is judged likely to be positive. This is reasoned probabilistically as follows. First, because evidence from observations and process models is mixed as to whether GCM cloud feedback is too strong or too weak overall, and because the positive feedback found in GCMs comes mostly from mechanisms now supported by other lines of evidence, the central (most likely) estimate of the total cloud feedback is taken as the mean from GCMs (+0.6 W m–2 °C–1). Second, because there is no accepted basis to discredit individual GCMs a priori, the probability distribution of the true feedback cannot be any narrower than the distribution of GCM results. Third, since feedback mechanisms are probably missing from GCMs and some CRMs suggest feedbacks outside the range in GCMs, the probable range of the feedback must be broader than its spread in GCMs. We estimate a  probability distribution  for this feedback by doubling the spread about the mean of all model values in Figure 7.10 (in effect assuming an additional uncertainty about 1.7 times as large as that encapsulated in the GCM range, added to it in quadrature). This yields a 90% (very likely) range of −0.2 to +2.0 W m–2 °C–1, with a 17% probability of a negative feedback."