Modern Ancient Temperatures

By Willis Eschenbach – Re-Blogged From WUWT

OK, no need to torture me, I confess it—I’m a data junkie.

And when I see a new (to me at least) high-resolution dataset, my knees get weak. Case in point? The temperature dataset of the Colle Gnifetti ice core. It has a two-year resolution thanks to some new techniques. Better, it stretches clear back to the year 800. And best, it extends up to near the present, 2006. This lets us compare it to modern datasets. The analysis of the ice core dataset is described in Temperature and mineral dust variability recorded in two low-accumulation Alpine ice cores over the last millennium by Pascal Bohleber et al.

Let me start with where Colle Gnifetti is located. Unusual among ice core records, it’s from Europe, specifically in the Alps on the border of Switzerland and Italy.

Figure 1. Location of the ice cores in the study.

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USE OF A “CLIMATE MODEL MEAN” AND THE USE OF ANOMALIES CAN BE MISLEADING

By Bob Tisdale – Re-Blogged From WUWT

INTRODUCTION

For the purposes of examples only, I’m going to initially present comparison graphs of monthly global land-ocean surface temperature data and model outputs, all of which include (roughly) 3.5 to 4 deg C annual cycles. Why am I presenting model-data comparisons with overlapping annual cycles, you ask? There’s something very unusual about a couple of ensemble members from the CMIP5 archive (the simulations with Historic & RCP8.5 Forcings) when you compare them to the Berkeley Earth data. You’ve got to see this to believe it! I couldn’t make this up. And they provide wonderful lead-ins to a discussion of one of the climate science community’s favorite presentation devices, the multi-model mean, and they provide wonderful lead-ins to a discussion of anomalies.

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The ‘Trick’ of Anomalous Temperature Anomalies

By Kip Hansen  Re-Blogged From WUWT

It seems that every time  we turn around, we are presented with a new Science Fact that such-and-so metric — Sea Level Rise, Global Average Surface Temperature, Ocean Heat Content, Polar Bear populations, Puffin populations — has changed dramatically — “It’s unprecedented!” — and these statements are often backed by a graph illustrating the sharp rise (or, in other cases, sharp fall) as the anomaly of the metric from some baseline.  In most cases, the anomaly is actually very small and the change is magnified by cranking up the y-axis to make this very small change appear to be a steep rise (or fall).  Adding power to these statements and their graphs is the claimed precision of the anomaly — in Global Average Surface Temperature, it is often shown in tenths or even hundredths of a Centigrade degree.  Compounding the situation, the anomaly is shown with no (or very small) “error” or “uncertainty” bars, which are, even when shown,  not error bars or uncertainty bars  but actually statistical Standard Deviations (and only sometimes so marked or labelled).

GlobalTemp_420

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Sea Surface Temperatures Ahead of Hurricane Florence

By Bob Tisdale – Re-Blogged From WUWT

August 2018 Hurricane Region Sea Surface Temperatures, in Advance of the Peak Hurricane Month and Florence Making Landfall, Assuming She Does

September is upon us, and September is the peak month for hurricane activity in the North Atlantic. (See the NOAA Hurricane Climatology graph via Wikipedia.)  So, to check the temperature conditions leading up to the peak month, let’s take a look at the August 2018 sea surface temperatures anomalies and sea surface temperatures for the hurricane development regions—Main Development Region (10N-20N, 80W-20W), Caribbean (10N-20N, 86W-60W), and Gulf of Mexico (21N-31N, 98W-81W)—along with those of the waters along the east coast of the United States (24N-40N, 80W-70W).  For the geographically impaired, see the map here for the locations of those regions.

Note: This is simply a data presentation, so don’t be looking for conclusions at the end of the post.  [End note.]

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