warmist - someone who doesn't reject modern climate science
evolutionist - someone who doesn't reject modern biology
I've noticed that some people who wouldn't contemplate wholesale rejection of geology or biology are completely dismissive of climate science: "it's all models and simulations", "it can't be tested", "it's dependent on complex computer programs", "it's all too uncertain", and so forth. And this extends beyond the denialists, who have no interest in the science and are largely just trying to avoid having to accept its implications, to some who have been misled by their rhetoric.
This seems to be driven by some misunderstandings about how science works, so some comparisons may be useful.
First of all, climate science operates within the same institutional and social frameworks as the other sciences. It is carried out by scientists working at the same universities, publishing within the same system of peer review (in some cases in the same journals, with broad science journals such as Nature or Science), funded by the same or similar research bodies. (Obviously biology gets more medical funding, geology more mining industry funding, etc.) So there's no sociological reason to expect climate science to be more biased, less reliable, or otherwise inferior.
Every science is different, obviously, and "biology", "geology", and "climate science" are actually complexes of different disciplines. But there's nothing foundationally different about climate science. The use of complex computer programs, simulations and models extends throughout the sciences, the interpretation of data is always dependent on existing theory, there are many sciences that are historical rather than experimental, and many disciplines have to deal with large uncertainties.
Computing is now ubiquitous in the sciences. Rejection of everything dependent on complex computer analysis or simulation would mean throwing away huge slabs of high energy physics, astrophysics, chemistry, genomics, and so forth. (Even in mathematics there are proofs of results such as the Four Colour theorem which rely on computer programs and are justified by indirect arguments about the validity of those programs.) Bridges, aircraft and other engineering constructions are tested in simulations and hence have to deal with simulation errors in addition to model specification risks.
Model assumptions in science are often untested, or hard to test, and model validation is always heuristic, with models often used as theory discovery tools or predictive frameworks. Attempts to use phylogenetics to probe the early parts of the tree of life, for example, involve choices of substitution models, selection of parameters, and other assumptions for which there are only ad hoc justifications, and produce conclusions which we have limited ability to test against other lines of argument (from geochemistry, say).
Theory dependence of observation and model-data interactions are standard themes in the philosophy of science, and this extends even to the "hard" experimental sciences. Raw data from something like the Large Hadron Collider is hardly self-explanatory (my understanding is that it is pretty much incomprehensible without the aid of a bucketload of auxiliary theories and complex computer analyses). Fossils are searched for and interpreted in the context of an existing understanding of the history of life. And so forth.
There are many sciences which are, largely or in part, historical rather than experimental. The reconstruction of the history of life is one example. Geological models of plate movements rest on different physical foundations to climate models, but operate on the same spatial and temporal scale. (And also perform relatively poorly at predicting short-term phenomena such as earthquakes and volcanos.)
As far as large uncertainties go, the obvious parallel is with other environmental models. Hydrological forecasts of flood levels, for example, have large uncertainties, but that's hardly an argument for not performing them. The scientific response to uncertainty is to try to reduce it, or to understand and track it, not to throw up one's hands in despair.
What is unique about climate science? Perhaps the scale of the data collection and computation involved. Perhaps the "density" of the model-data interactions. Nothing, it seems to me, that places it on a qualitatively different epistemological footing to the rest of science.
The IPCC, much-hated by denialists, actually makes climate science stand out. Few, if any, other disciplines make such an open, international attempt to synthesise key results and present them in a format accessible to policy-makers and laypersons.
There are all kinds of unsolved problems, poorly understood areas and lacunae within climate science, just at there are in other sciences, but I see no sign that the discipline as a whole is in crisis. Perhaps the biggest problem it faces is in educating non-scientists in the face of well-resourced external attacks. (It is no coincidence, surely, that among developed nations the United States has by far the largest proportions rejecting both evolutionary biology and climate science.)
The political implications clearly explain why people attack some sciences rather than others, but don't have any direct bearing on the strength of the science itself. And political pressure is just as likely to distort science towards conservatism.