Climate models have long predicted that the high latitude response of nearsurface air temperatures should be greater than at lower latitudes as a result of snow/ice feedbacks. Here we show that a regression analysis of observed global surface temperatures and anthropogenic and natural forcings could misleadingly suggest that climate models fail to capture the observed zonal mean pattern of response to anthropogenic forcings. A better approach to detecting changes and to determine consistency of climate models and observations is to use multiple features of the response pattern derived from physically-based climate models, as has been done in optimal detection studies. We show that multi-variable fingerprints can more easily detect anthropogenic changes thereby offering the potential to more robustly quantify anthropogenic influence on aspects of the climate system such as the cryosphere and the hydrological cycle.

NCDC’s US Climate at a Glance webpage uses preliminary temperature anomaly data to create a monthly anomaly map:

The mauve arrow points to an oddity – a blazing hot spot around Greenwood, MS, with a peak anomaly approaching +8F. Greenwood’s Preliminary November Climate Data form (“CF6″ report available here ) hints at the cause:

For some reason Greenwood reported only the first seven days of the month, a warm spell where the temperature anomaly was +7F. The data missed the rest of the month, which was anomalously cool across the region. Despite the abbreviated and unrepresentative nature of the Greenwood data, it was apparently used in the map construction. This the hot spot.

No doubt this will be corrected later but meanwhile an oddly flawed map has been issued to, and perhaps used by, the public.

“But we’ll keep on repeating the experiment until we get the right result.”

Reminds me of an old production plant axiom:

“Purification by re-analysis.”