Inaccuracies in U.S. temperature records
A comment by Fred Svetz
Over the past 4 years, the National Weather Service has replaced human weather observers with an automated weather observing system called ASOS (Automated Surface Observation System). This system regularly underreports daily maximum temperatures by 1-4 degrees because of poorly designed software. How will your research results be affected by this artificial cooling of U.S. temperatures?
only time will tell . . .
A comment by Robert S. Thompson
I have heard anecdotes in the other direction as well, that is: the gradual nationwide replacement of thermometers by thermistors may be artificially inflating temperature records. On-going analyses of these data will (I hope) identify the true temperature signal (separate from instrumental and software considerations).
Warning about reliability of Global models
A comment by Rob Bracken
In understanding Global and even local "climate change", we are confronted with serious difficulties of spatial aliasing and lack of baseline data. Systems which operate on large spatial and temporal wavelengths are difficult if not impossible to quantify. The difficulty is compounded when the system is soft, having many poorly constrained variables and an incomplete understanding of the system responses; as is the case with global climate change models. A model claims to contain enough knowledge of a system that when one or more of the input parameters are changed, the model responds in parallel to the true system. A predictive model must also know how the input parameters are changing. Therefore, an accurate global change model must claim to have accounted for all dynamics of the world climatic systems either explicitly or implicitly. An explicit accounting requires current and future knowledge of all pertinent inputs and responses of the system at all locations, i.e. the spatial wavelengths extant in the Earth's system cannot be characterized without a densely spaced global network of sensors comprehensive of all appropriate variables and a complete understanding of the associated effects. An implicit accounting requires historical knowledge of all pertinent parameters over periods of time long enough to observe accurately many complete cycles of all processes within the system; i.e. geologically dependent variables having temporal wavelengths of thousands or millions of years cannot be measured. Because the prerequisites to a reliable predictive model cannot be met, we must begin interpolating across gaps in data and understanding. This process involves introduction of various tweaking factors which preclude the model from being dispassionately tied to the data and physical law. A model such as this sometimes can be useful to bootstrap our understanding of a system or to prove (after many decades of confirming evidence) that we do, in fact, understand the system; but, to produce a prediction upon which the re-organization of governments may depend (vis-a-vis UNEP & IPCC) is altogether beyond the scope of any global model that can be produced. The USGS has, in the name of true science, a moral obligation to state explicitly that we do not yet know what the global climate trends are nor the overall effect of mankind. It would be absurd to begin mitigating something that may not be a problem. However, as the scale of the system decreases, it becomes easier to observe trends and understand their causes. Therefore, it is valuable to discuss the climatic variations in a small area such as the southwestern U.S.