Dr. Judith Curry writes about the Cowtan and Way paper which (according to some pundits) purports to “bust” the temperature pause of the last 17 years by claiming we just didn’t pay enough attention to the Arctic and Antarctic where there is no data. They do this by infilling data where there is none, such as NASA GISS tries to do by infilling temperatures from stations far away with their smoothing algorithm.
GISS station data with 250km smoothing:
GISS station data with 1200km smoothing:
Breathless interpreters of Cowtan & Way claim that by doing the same with satellite data instead of tortured surface data, Voilà “the pause” disappears.
Cowtan & Way are trying to address this lack of surface station data in these regions by doing infill from satellite data. At first glance, this seems an admirable and reasonable goal, but one should always be wary of trying to create data where there is none, something we learned about in Steig et al’s discredited paper on the supposed Antarctic warming. Plus, as some WUWT readers know, there’s a reason that satellite temperature data coverage doesn’t fully cover the poles. See the information on the UAH data at the bottom of this post.
A video of their methodology follows.
WUWT readers will note the before and after HadCRUT imagery from Cowtan & Way below. Take special note of the Arctic.
A discussion on that Arctic temperature infilling addition at high latitude follows Dr. Curry’s analysis.
Dr Judith Curry writes:
Let’s take a look at the 3 methods they use to fill in missing data, primarily in Africa, Arctic, and Antarctic.
- 1. Kriging
- 2. UAH satellite analyses of surface air temperature
- 3. NCAR NCEP reanalysis
The state that most of the difference in their reconstructed global average comes from the Arctic, so I focus on the Arctic (which is where I have special expertise in any event).
First, Kriging. Kriging across land/ocean/sea ice boundaries makes no physical sense. While the paper cites Rigor et al. (2000) that shows ‘some’ correlation in winter between land and sea ice temps at up to 1000 km, I would expect no correlation in other seasons.
Second, UAH satellite analyses. Not useful at high latitudes in the presence of temperature inversions and not useful over sea ice (which has a very complex spatially varying microwave emission signature). Hopefully John Christy will chime in on this.
Third, re reanalyses in the Arctic. See Fig 1 from this paper, which gives you a sense of the magnitude of grid point errors for one point over an annual cycle. Some potential utility here, but reanalyses are not useful for trends owing to temporal inhomogeneities in the datasets that are assimilated.
So I don’t think Cowtan and Wray’s [sic] analysis adds anything to our understanding of the global surface temperature field and the ‘pause.’
The bottom line remains Ed Hawkins’ figure that compares climate model simulations for regions where the surface observations exist. This is the appropriate way to compare climate models to surface observations, and the outstanding issue is that the climate models and observations disagree.
Is there anything useful from Cowtan and Wray? Well, they raise the issue that we should try to figure out some way obtain the variations of surface temperature over the Arctic Ocean. This is an active topic of research.
More from the same post at Dr. Curry’s site here
What is really funny is how Dana Nuccitelli has done an about-face since the satellite data now supports his argument. In his Guardian 97% piece [cited in Dr. Curry’s article] he’s all for this method.
But, just two years ago he was trashing the UAH satellite data on SKS as “misinformation”.
But Dana thinks UAH data is apparently OK today. What a plonker.
I will give Dr. Cowtan props though for realizing what the hypers don’t. He says this in the Guardian article:
“No difficult scientific problem is ever solved in a single paper. I don’t expect our paper to be the last word on this, but I hope we have advanced the discussion.
I give him props for having a sense of reality, something sorely lacking in climate science today.
Here’s why trying to use the satellite data to infill surface data at the poles is problematic:
Take a look at this latest image for 1000mb (near the surface) from the polar orbiting satellite NOAA-18, one of the satellites UAH now uses for temperature data:
Note how the data near the poles starts to get spotty with coverage? Note also how the plot doesn’t go to 90N or 90S?
NOAA doesn’t even try to plot data from there, for the reasons that Dr. Curry has given:
Second, UAH satellite analyses. Not useful at high latitudes in the presence of temperature inversions and not useful over sea ice (which has a very complex spatially varying microwave emission signature).
NOAA knows high latitude near-pole data will be noisy and not representative, so they don’t even try to display it. UAH is the same way. Between the look-angle problem and the noise generated by sea ice, their data analysis stops short of the pole. RSS does the same due to the same physical constraints of orbit and look angle.
As you can see, the polar orbit isn’t truly polar. Here are maps from UCAR that helps to visualize the problem:
As you can see, the orbit path never reaches 90N or 90S.
Note that the orbit is slightly tilted towards the northwest and does not actually go over the poles. While the red path follows the earth track of the satellite, the transparent overlay indicates the coverage area for the AVHRR imaging instrument carried by NOAA/POES satellites. This instrument scans a roughly 3000 km wide swath. The map projection used in this illustration, a cylindrical equidistant projection, becomes increasingly distorted near the poles, as can be seen by the seeming explosion of the viewing area as the satellite nears its northern and southern most orbital limits.
So, not only is the satellite coverage distorted at the poles due to the look angle, the look angle issue actually causes the satellite to image a wider swath of an area known to produce noisy and highly uncertain microwave data. Basically, the higher the latitude of the satellite imaging past about 60N/60S, the more uncertain the data gets.
It seems to me that all that Cowtan & Wray have done is swapped one type of highly uncertain data infilling with another. The claim that the addition of this highly uncertain data to HadCRUT4 seems to contradict ‘the pause’ most certainly isn’t proven yet, as even Dr. Cowtan admits to in his caveat.