This started out as a discussion point following E.M. Smith’s blog post Mysterious Madagascar Muse. The jist of the original article centred around the availability of data after 1990 in the GHCN dataset and the NASA/GISS treatment of temperature on the island. Well Madagascar has a bit of a further story to tell. I had offered to plot a ‘spaghetti’ graph of the temperatures from the ten stations used on Madagascar, and this has proven interesting as an example of how data is adjusted and filled in by GISS.

To start, the annual mean temperatures plotted on a graph (Figure 1) show clearly the differences between the stations – Antananarivo is high altitude and relatively cool, with a cooling trend; of the other stations, some have cooling trends, most are warming. Also noticeable is the very sparse data after 1990. Note the darker blue data for Maintirano, of which more later.

With such temperature differences between sites, obviously you cannot just average the temperatures. This is what it looks like if you do (Figure 2), and it clearly does not work as an average temperature for the island.

Figure 2. Averaged Annual Mean Temperatures (Clearly Wrong!)

Normalizing each of the temperature series by calculating the mean temperature for that station for the baseline period of 1951-1980 allows plotting of an anomaly-based ‘spaghetti’ graph (Figure 3). This shows what looks like warming-cooling-warming climate cycles very clearly and it is possible to fit a third order polynomial trendline though the averaged data. I’ve seen this again and again for data I’ve plotted around the world (incidentally these were for WUWT regular TonyB).

Now for the interesting bit – how GIStemp adjusts the data. GIStemp takes rural datasets and uses them to correct for urban warming. In this set of ten unadjusted stations there were three rural ones: Maintirano and two overlapping but separate ones for Antalalava (why kept separate?). In the homogenized set, only Maintirano, which has a large warming trend of 1.16 deg. C/century, remains unadjusted and all the other stations (Figure 4) have the trend increased – it seems to match Maintirano.

E.M.Smith finds seven other rural stations within 1000km that may contribute to homogenization. They also show cooling to about 1965-1975, then a warming trend. This is lost from the homogenized data.

So overall what effect does homogenization have? – well a big one. Having started into a better understanding of calculation of anomalies, I decided it was better to leave that for the present, but a straight average of the normalized unadjusted and homogenized overlaid with a 10 year moving average for each (Figure 5) shows just what homogenisation does for the ‘anomaly’ value for Madagascar calculated this way – it stabilises the base period and significantly warms the subsequent years.

Given that several of the stations show a cooling trend prior to homogenization, and that UHI correction should NEVER be in the wrong direction, this is nothing short of scandalous.

I originally looked at the temperature trends using a database that has been developed over the last two months, but when I checked for any up-dated data on the GISS site, I found the trends were different (Table 1). We’ve now found the reason for that and that is worth investigating in its own right. The answer is simple – bad data. The database QC system throws out any year with missing months of data, and after 1990 the data in most of the Madagascar stations is patchy at best, so the database ignored the data in plotting the temperature trends. It is amazing how much warmer Madagascar is with that patchy data included.

>Table 1. Temperature Trends for Data Madagascar Stations: Comparison of Sources with/without QC Control (see text).

One final thing. Even the patchy data stops in 2005, so after this date Madagascar too gets ‘filled in’ data from elsewhere – it seems from the rural stations up to 1000km away – again. And even the stations used to ‘fill in’ have patchy data – many have a gap then ONE DATA POINT in 2009. This is unbelievable. Rather than give an example, check the station hyperlinks below for yourself:

 Ile Juan De N 17.1 S 42.7 E 111619700000 rural area 1973 – 2009 Dzaoudzi/Pama 12.8 S 45.3 E 163670050000 rural area 1951 – 2009 Iles Glorieus 11.6 S 47.3 E 111619680000 rural area 1956 – 2009 Ouani (Anjoua 12.1 S 44.4 E 111670040000 rural area 1963 – 1984 Serge-Frolow 15.9 S 54.5 E 168619760000 rural area 1954 – 2009 Ile Europa 22.3 S 40.3 E 111619720000 rural area 1951 – 2009 Porto Amelia 13.0 S 40.5 E 131672150004 rural area 1987 – 200

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1. tonyb says:

Nice post VJ.

I think the clear warm /cool trends are very interesting, but the more figures are ‘adjusted’ the more they get smoothed out. This probably explains why the Met office (and Michael Mann) are so convinced that temperatures in the past were not very variable until we started adding Co2.

I think it would do everyone good to go back to basic raw data then start again with the adjustments -asking themselves why they are doing it- AND at the same time compare the end results with real world data and observations recorded by people living in an area at the time.

Looking at adjusted data or computer models all the time does I believe get in the way of scientists taking a more rational view of climate-observations seem to be very secondary to a model.

As an example, the Met office in near by Exeter have been telling us all day to expect a gloomy overcast today. However, if they had bothered to actually look out of the windows of their computer suite they would have seen we have been bathed in glorious suinshine all day.

Yes yes I do know the difference between weather and climate but just wanted to point out that observations seem to take second place to modelling and we see this in all spheres of climate science.

Tonyb

2. drj11 says:

Looking at your figure 1, I see that Diego-Suarez (Antsiranana really, according to Wikipedia) has a marked cooling trend. But it kind of looks like there might be a station move (uphill) that hasn’t been adjusted for. Maybe in the late 1950’s? What do you reckon?

• Verity Jones says:

David, a station move is certainly likely and there is a gap in the data, however it wouldn’t be uphill (given altitude is 105m) or at least that does not account for it – there isn’t sufficient elevation in the area and even from the coast it is not enough – the adiabatic laspe rate would suggest requirement for a much greater change. I agree that some change is likely – perhaps uphill and away from the coast (warmer sea at night in this region while inland temperatures fall?).

The figure uses unadjusted data obviously. In the adjusted data (downloaded in Jan/Feb), that for Diego-Suarez begins in 1960. But then the adjusted data for Antananarivo only begins in 1941 (rural ref stations rule). This was before any ‘nightlights’ adjustment changes which leaves both intact after adjustment.

• drj11 says:

I did a little digging using the online version of MCDW: http://www7.ncdc.noaa.gov/IPS/mcdw/mcdw.html

The Diego Suarez station moved from 12 17’S 49 18’E 29 metres in 1957 October to 12 21’S 49 18’E 105 metres in 1957 November.

So yes, a move uphill and inland away from the coast. For any regional station analysis, it’s probably best to treat it as two separate records.