How difficult it is to be a climatologist…

Just  before COP-15 took place in Copenhagen in December 2009, unknow people broke into the computers of the Climate Research Unit (CRU) at the University of East Anglia and stole email correspondence of Prof. Jones, a major figure in the IPCC.  The issue received wide media coverage and was eventually referred to as Climategate. The story also started a flood on criticism of IPCC. To large extent, the criticism is fed by accumulated resentment about the bad manners of some leading climatologists and the quasi-religeous status confrerred to the Assessment Reports, certainly also including inputs from the anti-mitigation lobbies, the oil and and coal industry. In fact, there is some evidence that some secret services may have been behind the whole issue.

I don’t deny that some climatologists now behave as the “kings of the ring”; some of them tend to forget that their business is science – not politics (I also mentioned this in one of the introductory paragraphs in the great projects ” post). Jacques sent me a set of interesting articles from Le Monde (which I collected in a pdf that can be accessed here: controverses_diverses_IPCC_copenhagen_20091209_le-monde). If you go to the website of Le Monde you will also find an audio file with an interview of Gil Mahé, a well know hydrologist, who blames part of the problem on the fact that climate data (i.e. real unprocessed station data) are difficult to get at, for a number of reasons, mainly the fact that national meteorological services want to sell them (See footnote). It is difficult to say how the increased demand for climate data (Changnon &  Changnon, 2010) will eventually impact the trade… On one hand, Meteorological Services will use it to generate more income, but on the other hand, they may improve the quality and coverage of their networks to meet demand. This would be positive.

The result of the difficulty to access data is twofold: lack of transparency of many published climatological analyses – which does not improve the air of suspicion that surrounds some climatological analyses – , and also greater uncertainty than technically feasible in some analyses (see an example in the footnote).


Just in case someone wants to misinterpret me: I do believe that we humans contribute to modifying climate variability patterns, but I dislike climate mysticism and I don’t believe in the infallibility of the climate sacerdotes magni.

In matters of climate impacts, the rule is “the worse the prediction the better”, especially among the many “experts” who got their climatology training on CNN. In an impact assessment I was involved in, we had shown that some irrigated crops would benefit from climate change, provided sufficient water was available. One of the comments I got from a participant in the study was Are we sure this is the message we want to convey? I do not have any messages I want to convey: I carry out as honest as possible an impact assessment, and I describe the results. But the problem is that many “experts” have messages they want to convey. This is not science, this is religion (refer, again, to the post on the great projects, the section on climate manipulation). One of the articles in Le Monde recounts how the journal published by FNRS (French National Fund for Scientific Research) had been planning to include two articles on climate change in their 200912 issue, side by side, one by “mainstream” climatologists and the other by two geophysicists (Vincent Courtillot and Jean-Louis Le Mouël) who defend the “marginal” position according to which the warming is due to solar factors. Previous articles by Courtillot and Le Moël have been published in the peer-reviewed scientific literature, but the opposition of the “mainstreamers” was such that FNRS eventually gave in and… did not include any article on climate in their 200912 issue.  Again, is this the way science should work?  It is so dangerously reminiscent of the “Holy  Inquistion”…  I personally do believe that no-one has the right to tell others what to believe, what to eat, which language to use or how to dress… to name just a few. I don’t believe either that scientists have the mandate to guide the ignorant (most of them don’t care, actually, which is different from ignorance). There is much more to this subject, for instance, how deep is the knowledge of  Those-who-know? I very much like what Cedric wrote in his blog in 2007 (Lettre sur les ignorants à l’usage de ceux qui savent; Letter about the ignorant for the use of those who do know.)

The issue of non-public data does not apply only to meteorological services. Several times I have come across graphs published by insurance companies about climatic risk, but I was denied access to the original data by the authors. This applies, in particular, to much work done by insurance companies. The justification is always either “confidentiality” or the risk of giving away info to competitors.

The problem is not new either! In 20031203, I wrote the following note on the website of  the international society of agrometeorology:

On 13 Nov. 2003 the FAO agrometeorology Group sent requests to the FAO/WMO AGROMET-L and to CLIMLIST ask for help to locate average monthly station (point) Penman-Monteith data to be included in the new version of LocClim All replies we received except one offered gridded data. Each of them got an answer repeating what we said in the announcement, i.e. “we specifically exclude any data from global or local grids (Interpolated data and area-wide ones). We need real station data, with geographic coordinates and altitude”. Another example: earlier this year, I requested a friend in an African Meteorological Service to provide me actual rainfall data for some stations. He sent me data extracted from a popular 10-daily African rainfall grid produced in the US based on GTS data. This is not the place to discuss the complex differences between point data and pixel values, but I find it amazing that even national agrometeorological services use “highly imaginative” data rather than their own station information. I think this raises a very serious issue: many people no longer work with real data. Instead, they use a number of gridded average and “real-time” datasets around, often interpolated with unspecified methods and very large cell sizes. Maybe part of the problem is that meteorological services want money for their data, which leads many users, even at the national level (e.g. agronomic research) to resort to easily accessible grids, avoiding costs and administrative work. 10 years ago, the operational agrometeorologist had a real technical problem because there were no good tools available to spatially interpolate data. This issue was addressed from many sides; today gridding is no longer a serious problem in operational agrometeorology for most variables. Unfortunately, the result is that the perceived need for good data has decreased, as everything is somehow available as grids. We have replaced a real problem associated with the lack of ground data with a data processing problem, which is much easier to solve. We have somehow traded data for colour pictures. There is just no way to make proper weather impact assessments (and this is actually what agrometeorology is about) without adequate data. We have to do something about it.

I concluded by saying : Any suggestions?

There were none!

Related post: Climate change: vehemence Vs competence


D. Changnon & S.A Changnon, 2010. Major Growth in Some Business-Related Uses of Climate Information. J. Appl. Meteorol. Climatol., 49: 325-331


Selling climatic data is a wrong approach, as (1) there is very little demand for (and money in) individual data items, say, 21st December rainfall in Ferkessedougou and (2) there is more money in value-adding (analyses) that in raw data. Unfortunately, many meteorological services are far better at collecting data than using them! Finally (3) meteorological services tend to charge completely unrealistic amounts for data. For instance, while we were involved in a climate change impact study in Morocco (downloadable from here), I tried to add some Algerian data to improve impact assessments in eastern Morocco. For one station with 30 years of daily data (rainfall, maximum and minimum temperatures), we were asked 20,000 US$… which we could not afford.

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