|Forrest M. Mims III|
Forrest Mims is an interesting character. To quote from the introduction to his Science article on amateur science: "Forrest M. Mims III is a writer, teacher, and amateur scientist. He received a Rolex Award for developing a miniature instrument that measures the ozone layer and has contributed projects to “The Amateur Scientist” column in Scientific American. His scientific publications have appeared in Nature and other scholarly journals."
Anthony Watts just published a guest post by Forrest M. Mims III with the title: "Another IPCC AR5 reviewer speaks out: no trend in global water vapor". I have no special expertise in this area, but I am privileged being able to read the article that is discussed. This is sufficient to see that the article and its post are two different worlds. Update: An earlier draft is available (thanks, michael sweet).
First, note that being a "expert reviewer" does not say much. There are over a thousand reviewers, even Anthony Watts himself is an IPCC "expert reviewer". On the other hand, Mims may be an amateur, but did do valued scientific work on UV measurements.
The trend in global water vaporThe post discusses a paper by Vonder Haar et al. (2012) on the NASA Water Vapor Project (NVAP) dataset. The main piece of information missing from the post is that this dataset without trend, is only 22 years long. Almost any climatological measurement will not have a statistically significant trend over such a short period, but the story is even weirder.
Just as in the misleading post on homogenization of climate data earlier this year, Anthony Watts again proofs to have a keen eye in finding the best misinformation.
Mims added a list with all the comments of his review. In this list, Watts found this comment:
This paper concludes,
“Therefore, at this time, we can neither prove nor disprove a robust trend in the global water vapor data.”
Non-specialist readers must be made aware of this finding and that it is at odds with some earlier papers.
The complete citation from the Geophysical Research Letters article is:
"The results of Figures 1 and 4 have not been subjected to detailed global or regional trend analyses, which will be a topic for a forthcoming paper. Such analyses must account for the changes in satellite sampling discussed in the auxiliary material. Therefore, at this time, we can neither prove nor disprove a robust trend in the global water vapor data."
In other words, they cannot say anything about the trend, because they have not even tried to compute it and estimate its uncertainty. Especially estimating the error in the trend will be very difficult as the dataset uses different satellites for different periods of the dataset, which invariably creates jumps in the dataset that should not be mistaken for true climate variability or trends.
The paper is also not at odds with earlier papers. These earlier papers studied longer periods and probably datasets which were more homogenenous and consequently did find a statistically significant trend. There is thus no contradiction.
The NVAP datasetThw NASA Water Vapor Project dataset is made to study climate, but not to study trends, its strength is being able to study spatial patterns in humidity. To cite from the paper:
"Changes to input datasets and selected algorithms were made with each phase of processing, incorporating improved data and processing methodologies, but resulting in several time-dependent artifacts that degraded the dataset’s decadal uniformity. These changes, in combination with the dataset’s relatively short period of record, make the heritage NVAP dataset unsuitable for long-term trend analysis [Trenberth et al., 2005]."
The heritage NVAP dataset is the previous version with data from 1988 to 2001 (thank you RomanM for noting that this should be explicitly stated). This dataset has strong jumps (inhomogeneities), which you can even see by eye; see Figure 1 of the article. For the new dataset, they have put effort into reducing these artifacts. This is explained in the Auxilary Material, especially in Text S1; it looks like this material is not behind the pay wall. Still they only claim:
"NVAP-M Climate is designed for studies on seasonal to interannual timescales on various spatial scales."
There is no claim of usefulness to study trends. From a previous dataset you can see the beautiful global spatial patterns that can be observed by satellites. If you click on the image you go to a page where you can see a beautiful animation of the pattern for an entire year.
Further mistakesFurthermore the post claims that "Climate modelers assume that water vapor, the principle greenhouse gas, will increase with carbon dioxide". This is wrong or at least misleading: humidity is expected to follow the temperature, in as much as temperature follows carbon dioxide, humidity will indirectly follow carbon dioxide.
IN one of the comments of Mims, he complains about the line: "Thus water vapour at the surface and through the troposphere has very likely been increasing since the 1970s." in the Second Order Draft of the upcoming IPCC report. And he claims: "This conclusion is contradicted by the 2012 NVAP-M paper discussed in the rows immediately above." However, the NVAP-M dataset started in 1988 and there is thus no contradiction.
Open access publishingWater vapor is an interesting variable. It is a strong greenhouse gas and an integral part of the hydrological cycle. Getting the spatial pattern of humidity and its temporal variability is thus very important. Consequently, it is important that we understand the quality of available measurement datasets well and that climate models reproduce the humidity measurements accurately. Unfortunately, the WUWT post was no contribution to such a scientific debate, it was just a lot of misinformation. Once again.
I wish all scientific articles were open to the public. That would make this type of misinformation by climate "skeptics" more difficult.
Fortunately, more and more people seem to realize the quality of WUWT and the reach of this blog, as measured by Alexa is going down.
More posts on homogenisation
- Homogenisation of monthly and annual data from surface stations
- A short description of the causes of inhomogeneities in climate data (non-climatic variability) and how to remove it using the relative homogenisation approach.
- New article: Benchmarking homogenisation algorithms for monthly data
- Raw climate records contain changes due to non-climatic factors, such as relocations of stations or changes in instrumentation. This post introduces an article that tested how well such non-climatic factors can be removed.
- HUME: Homogenisation, Uncertainty Measures and Extreme weather
- Proposal for future research in homogenisation of climate network data.
- A short introduction to the time of observation bias and its correction
- The time of observation bias is an important cause of inhomogeneities in temperature data.