Climate Models Are NOT Simulating Earth’s Climate – Part 1

Bob Tisdale shows the blatantly obvious and essentially total failure of CMIP5 models to simulate ocean surface temperatures, which are a primary driver of climate.

“Unfortunately for the climate science community, the spatial patterns of the modeled warming rates for the global ocean surfaces from 1982 to 2015 (the era of satellite-enhanced sea surface temperature observations) show no similarities to the spatial patterns of the observed warming and cooling…no similarities whatsoever. This is blatantly obvious in Figure 1.”

Bob Tisdale - Climate Observations

This post will serve as part 1 of the 2015 update of the model-data comparisons of satellite-era sea surface temperatures. The 2014 update is here. I’ve broken the update into two parts this year.


The locations, the timings and the magnitudes of the naturally occurring variations in the surface temperatures of our oceans are primary factors that drive weather and, in turn, climate on Earth.  In other words, where and when the surfaces of the oceans warm, or cool naturally and by how much—along with other naturally occurring factors—dictate where and when land surface air temperatures warm and cool and where precipitation increases or decreases…on annual, decadal and multidecadal timeframes.

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Let’s talk about Global Cooling

The evidence is pretty clear that the globe is cooling on most time scales, and right now we are at one of the coolest points in the history of the earth. Looking first at the last 65 million years, since T-Rex was running around:

Global Temperature estimates over the last 65 million years based on oxygen isotope thermometry of deep-ocean sediment cores from many parts of the world. Data from Zachos et al (2001). Graph by Robert A. Rohde. READ MORE…

The Medieval Warm Period in Antarctica: How two one-data-point studies missed the target

Watts Up With That?

Guest essay by Sebastian Lüning

A common claim by warmists in the climate debate is the alleged absence of the Medieval Warm Period (MWP) in the Southern Hemisphere. In a previous post we discussed the MWP in Australia, New Zealand and Oceania. In the following, we will take a look at Antarctica.

In 2012 a group led by Robert Mulvaney of the British Antarctic Survey published in Nature an ice-core record of deuterium variations from James Ross Island, off the northeastern tip of the Antarctic Peninsula, in which deuterium was used as a temperature proxy. Whilst they found indeed a slight warming centred around 1000 AD, later developments are puzzling. Unexpectedly, the highest temperatures of the past millennium occurred during the Little Ice Age (LIA) around 1750 AD (Fig. 1). And the coldest temperatures were found at 1400 AD, during the late MWP. Based on this apparent mismatch with the…

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Violating the norms and ethos of science

Judith Curry gives a brilliant and thorough critique of a recent paper…

Climate Etc.

by Judith Curry

Don’t let transparency damage science.  – Stephan Lewandowsky & Dorothy Bishop

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Undersea volcanoes may be impacting long-term climate change

reblogged from Climate Etc.
Undersea volcanoes may be impacting long-term climate change

by Alan Longhurst

I think this paper on on ocean tides, sea-floor volcanoes and Milankevitch cycles is a game changer.

Mid-ocean ridge eruptions as a climate valve

Maya Tolstoy

Abstract. Seafloor eruption rates and mantle melting fueling eruptions may be influenced by sea level and crustal loading cycles at scales from fortnightly to 100 kyr. Recent mid-ocean ridge eruptions occur primarily during neap tides and the first 6 months of the year, suggesting sensitivity to minor changes in tidal forcing and orbital eccentricity. An ~100 kyr periodicity in fast-spreading seafloor bathymetry and relatively low present-day eruption rates at a time of high sea level and decreasing orbital eccentricity suggest a longer-term sensitivity to sea level and orbital variations associated with Milankovitch cycles. Seafloor spreading is considered a small but steady contributor of CO2 to climate cycles on the 100 kyr time scale; however, this assumes a consistent short-term eruption rate. Pulsing of seafloor volcanic activity may feed back into climate cycles, possibly contributing to glacial/interglacial cycles, the abrupt end of ice ages, and dominance of the 100 kyr cycle.

M. Tolstoy, Mid-ocean ridge eruptions as a climate valve, doi:10.1002/2014GL063015, Geophys. Res. Lett. 2015 [abstract] [manuscript]

A post at WUWT includes the press release from Columbia University

The AGU also issued a press release [link]

300 Scientists Tell Chairman of the House Science Committee: ‘we want NOAA to adhere to law of the Data Quality Act’

Watts Up With That?


The following letter has been sent to Chairman of the House Science Committee, Lamar Smith, regarding NOAA’s “pause buster” data shenanigans that we highlighted back in the summer of 2015.

The issue is with bad data, as Dr. Pat Michaels Dr. Richard Lindzen, and Dr. Chip Knappenberger observed related to the switch from buckets on a rope to engine water inlets for measuring sea surface temperature:

“As has been acknowledged by numerous scientists, the engine intake data are clearly contaminated by heat conduction from the structure, and as such, never intended for scientific use,”  “Adjusting good data upward to match bad data seems questionable.”

I’ll say. As Bob Tisdale and I wrote back in June:

“If we subtract the ERSST.v3b (old) data from the new ERSST.v4 data, Figure 11, we can see that that is exactly what NOAA did.”

“It’s the same story all over again; the adjustments go…

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On the likelihood of recent record warmth

Source: On the likelihood of recent record warmth

Judith Curry’s conclusions regarding the much publicized paper by Mann et al. in Nature:

As I see it, this paper is a giant exercise in circular reasoning:

  1. Assume that the global surface temperature estimates are accurate; ignore the differences with the satellite atmospheric temperatures
  2. Assume that the CMIP5 multi-model ensemble can be used to accurately portray probabilities
  3. Assume that the CMIP5 models adequately simulate internal variability
  4. Assume that external forcing data is sufficiently certain
  5. Assume that the climate models are correct in explaining essentially 100% of the recent warming from CO2

In order for Mann et al.’s analysis to work, you have to buy each of these 5 assumptions; each of these is questionable to varying degrees.