At the Deplorable Climate Science Blog, he claims that this map was published: enter image description here

When this is the reality enter image description here

The map above (the first map) is fake. NOAA has almost no temperature data from Africa, and none from central Africa. They simply made up the record temperatures

Is it true? Did NOAA publish a fake map based on information it doesn't have?


3 Answers 3


tl;dr: The supposedly fake map is composed of multiple sources of data, averaged over larger areas of the Earth and a longer period of its history. The map labelled as "the reality" shows just one of these sources of data, plotted at relatively high resolution, and only where directly comparable data is available from a specific 30-year period.

Both of the maps shown in the article can be downloaded from the NOAA's website on a page of Global Temperature and Precipitation Maps. I have selected from the form December 2016, and four "products":

  1. the "Global Land Mean Temp Anomaly Map" (labelled on the graph as "Land-Only") is the one being labelled as "the reality"
  2. the "Global Land & Ocean Temp Percentile Map" matches the "real" graph, but fills in the oceans, and also broad smudges of land
  3. the "Global Land Temp Percentile Map" (labelled on the graph as "Land & Ocean") is the one being labelled as "fake"
  4. finally, there is the "Global Z-Score Map"; this has the same coverage as the "fake" map

Maps 2 and 3 are also featured in this report analysing the Dec 2016 data.

On each of these maps, the legend includes two pieces of information which are key to understanding their different coverage.

Firstly, they list their source data:

Secondly, they list the time frame of their comparison: maps 1 and 2 state that they are "with respect to a 1981-2010 base period", while maps 3 and 4 do not. The reason for this, and the base period of the other maps, is explained in this FAQ:

Why do some of the products use different reference periods?
The national maps show temperature anomalies relative to the 1981–2010 base period. This period is used in order to comply with a recommended World Meteorological Organization (WMO) Policy, which suggests using the latest decade for the 30-year average. For the global-scale averages (global land and ocean, land-only, ocean-only, and hemispheric time series), the reference period is adjusted to the 20th Century average for conceptual simplicity (the period is more familiar to more people, and establishes a longer-term average). The adjustment does not change the shape of the time series or affect the trends within it.

So we have two very different types of graph:

  • a graph comparing a single data set in Dec 2016 against available averages within that dataset for the reference period 1981-2010
  • several graphs comparing a combined analysis of two data sets against averages for the period 1901-2000

It would seem an obvious question to ask how an ocean data set can be used to fill in land temperatures. However, the combined data set does more than just overlay the two sets of observations; details of exactly how it is computed are available in these references:

  • Smith, T.M., R.W. Reynolds, T.C. Peterson, and J. Lawrimore, 2008: Improvements to NOAA's historical merged land–ocean surface temperatures analysis (1880–2006); Journal of Climate, 21, 2283–2296, doi:10.1175/2007JCLI2100.1
  • Vose, R.S., D. Arndt, V.F. Banzon, D.R. Easterling, B. Gleason, B. Huang, E. Kearns, J.H. Lawrimore, M.J. Menne, T.C. Peterson, R.W. Reynolds, T.M. Smith, C.N. Williams, Jr., and D.L. Wuertz, 2012: NOAA's merged land-ocean surface temperature analysis. Bulletin of the American Meteorological Society, 93, 1677–1685, doi:10.1175/BAMS-D-11-00241.1

I have not read the full papers, but I think the key is that the combined data set measures relative rather than absolute temperatures, and is therefore able to combine them across much larger regions. (See also question 7 in the FAQ.) This accounts for the low resolution evident in the graphs which have full coverage. The GHCN-M data has not benefited from this "smoothing", so instead shows smaller patches of data; and it contains absolute temperatures, not deviations from average, so can only be plotted where there is enough to form a meaningful comparison.

Similarly, you might question why a dataset would contain enough data for an average across 1901-2000, but not for 1981-2010. The GHCN-M overview page explains that the dataset was first produced in the 1990s, but composed out of existing historical records. So at the relatively high resolution of the data set, a particular grid point might have values for 1900 to 1980, but none since, while a neighbouring grid point has only recent data. The map of station ages on this page shows very few long-established points in Africa, which would be consistent with the theory that map 1 is missing Africa data because of a lack of consistently placed observations to compare.

To be clear, the "missing data" on map 1 does not mean that there are currently no measuring stations in Central Africa (the location map above shows plenty); it also probably does not mean there weren't any in the period 1981-2010 (I would be very surprised if there weren't). What it probably means is that the measuring stations currently in place are different from those that were in place between 1981 and 2010, meaning that comparisons must be made based on larger analysed areas.

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    +1 for actually explaining something about the data instead of ranting about the article.
    – jpmc26
    Commented Feb 7, 2017 at 0:37
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    @KDog Not really. The difference between "making data up", and "combining data from nearby locations over a large time frame in a statistically rigorous way" is not just "overstating it some". The data is all "real", and the methods for interpreting it are openly published and regularly refined to eliminate confounding factors. If anything, the processed data is higher quality than the raw data, because the processing is designed to eliminate noise. The fact that you don't understand some analysis doesn't make that analysis equivalent to fraud.
    – IMSoP
    Commented Feb 7, 2017 at 17:08
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    @Konstantine The linked article is accusing the NOAA of fraud; not just implying it, explicitly stating it. The author refers to the data as "fake", "simply made up", "imaginary", and "obviously bogus". A couple of hours of my non-expert time was all it took to find the source of the data, including comprehensive details of how and why it is analyzed. This guy writes a blog dedicated to climate science, and yet somehow never looked for (or deliberately ignored) any background to the two out-of-context images. So no, "the guy who wrote the article" most emphatically does not "have a point".
    – IMSoP
    Commented Feb 7, 2017 at 18:25
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    @Konstantine What "underlying data issue"? That we don't have thermometers on every square inch of the planet's surface which have been recording accurate measurements at hourly intervals for the last 150 years? What would you trust exactly? As for "not based upon terrestrial thermometer measurement observations", it's certainly not true that there are no measuring stations in central Africa, as the map I link at the end shows. The interpolation is only necessary because those measuring stations have not always been in the same place, and we need some way of comparing across time.
    – IMSoP
    Commented Feb 7, 2017 at 22:05
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    Frustrating, ain't it, when you take the time to write a thorough, detailed rebuttal to a baseless accusation, and people still hear what they want to hear? Nice answer. You have my upvote, and my sympathy.
    – ArtOfCode
    Commented Feb 8, 2017 at 4:20

This claim is complete and utter bollocks.

Let's start with the obvious. If map A has some data on it, and map B doesn't, that in no way indicates that map A is fake - even if data is marked as 'missing. There might be many reasons the data is not on map B. They might have been compiled from different sources, or have different criteria for inclusion, or require different amounts of data for accuracy. The same is true of datasets in general.

Here is a link to the page where the supposedly fake map is published. On the same page you will see another map, identical to the one that is claimed as evidence of fakery, but with all the supposedly missing data (and also ocean temperatures). There is no missing data.

We can also show clearly that NOAA and the CHCNM dataset DOES have data for central Africa, in the places where the cited map has grey areas. As an example here is the link to the NOAA data for Kigali, Rwanda. You can actually go and look up the temperatures for yourself, and do the analysis yourself. Even if it were not in this dataset it would be easily available. This link will tell you that the temperature in Kigali, Rwanda is 19 degrees C as I write it. (YMMV)

The only evidence that 'Deplorable Climate Science Blog' presents is that "the data in the first map doesn't show up on the second, so it must not exist". That's equivalent to saying "Because data for Washington DC doesn't show up on this map of Alaska, the data on the East Coast map must be fake". We can't give a definite reason why African data is not shown, but there are plenty of potential reasons that don't involve fraud.

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    When an argument starts off with "obviously wrong" it's immediately worrisome and all statements thereafter are subject to severe skepticism...
    – ylluminate
    Commented Feb 6, 2017 at 0:43
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    While I am very confident that this answer is correct, I don't think it really addresses the question as asked. It took me awhile to figure out what the issue was because the article linked in the question is so poorly written and poorly supported. But after some study, I recognized that the second figure in this question indicates that NOAA has no data from most of Africa for December 2016. The first figure indicates that there is a region in south-central Africa which set temperature records in December 2016. So the question is how they came to that conclusion without data.
    – Mark
    Commented Feb 6, 2017 at 1:46
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    @yluminate With an obvious exception, which is when the original claim is obviously wrong. Commented Feb 6, 2017 at 2:50
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    @Mark The second map compares the Dec 2016 data to the 1981-2010 data, so "no data" can mean "no Dec 2016 data" and/or "no (or incomplete) 1981-2010 data". The original claim was that it is "no Dec 2016 data" and this answer shows that it is not "no Dec 2016 data". Commented Feb 6, 2017 at 4:31
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    @Mark One thing I would note here is that the map is not the data; the maps represent two different products produced using data from one or both of the two time series involved, both of which are published and downloadable. There's an extensive discussion about temperature monitoring and links to additional resources at ncdc.noaa.gov/monitoring-references/faq/… Commented Feb 6, 2017 at 4:35

DJ's answer is correct. I spent some time doing some research, to back it up. The GHCN has two datasets, QCU and QCA.

This is the description of the two data files from the readme.

"QCU" files represent the quality controlled unadjusted data, and "QCA" files represent the quality controlled adjusted data.

Looking at this map "NOAA GIS Site (Global Summary)", You can see there are stations in that area and the only hole from the first map corresponds to the lack of stations in the DR of Congo.

It took some work to verify one of the sites in that area. The Lichinga site was very close to the area of no data. Neither file contained it. There were two things that stuck out, when going through the file. First was sites being categorized under the USSR. The second was there were many more entries in the QCU file. The USSR anachronism provided evidence, that they don't update the site names. By looking at the Lat/Long, there was an entry for VILA CABRAL (Only in the QCU file). A quick search confirmed that Lichinga was founded as Vila Cabral.

This all leads me to the conclusion that the "fake" map is using the QCU data and the second map only includes the QCA data, because they can't verify if there were adjustments made to some sites, they don't include that data in the QCA file, in which they do adjustments.

The data to back this up was obtained at ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v3/

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