Irrigation and paint as reasons for a cooling bias

In previous posts on reasons why raw temperature data may show too little global warming I have examined improvements in the siting of stations, improvements in the protection of thermometers against the sun, and moves of urban stations to better locations, in particular to airports. This post will be about the influence of irrigation and watering, as well as improvements in the paints used for thermometer screens.

Irrigation and watering

Irrigation can decrease air temperature by up to 5 degrees and typically decreases the temperature by about 1°C (Cook et al., 2014). Because of irrigation more solar energy is used for evaporation and for transpiration by the plants, rather than for warming of the soil and air.

Over the last century we have seen a large 5 to 6 fold global increase in irrigation; see graph below.



The warming by the Urban Heat Island (UHI) is real. The reason we speak of a possible trend bias due to increases in the UHI is that an urban area has a higher probability of siting a weather station than rural areas. If only for the simple reason that that is where people live and want information on the weather.

The cooling due to increases in irrigation are also real. It seems to be a reasonable assumption that an irrigated area again has a higher probability of siting a weather station. People are more likely to live in irrigated areas and many weather stations are deployed to serve agriculture. While urbanization is a reason for stations to move to better locations, irrigation is no reason for a station to move away. On the contrary maybe even.

The author of the above dataset showing increases in irrigation, Stefan Siebert, writes: "Small irrigation areas are spread across almost all populated areas of the world." You can see this strong relation between irrigation and population on a large scale in the map below. It seems likely that this is also true on local scales.



Many stations are also in suburbs and these are likely watered more than they were in the past when water (energy) was more expensive or people even had to use hand pumps. In the same way as irrigation, watering could produce a cool bias due to more evaporation. Suburbs may thus be even cooler than the surrounding rural areas if there is no irrigation. Does anyone know of any literature about this?

I know of one station in Spain where the ground is watered to comply with WMO guidelines that weather stations should be installed on grass. The surrounding is dry and bare, but the station is lush and green. This could also cause a temperature trend bias under the reasonable assumption that this is a new idea. If anyone knows more about such stations, please let me know.

From whitewash to latex paint

Also the maintenance of the weather station can be important. Over the years better materials and paints may have been used for thermometer screens. If this makes the screens more white, they heat up less and they heat up the air flowing through the Louvres less. More regular cleaning and painting would have the same effect. It is possible that this has improved when climate change made weather services aware that high measurement accuracies are important. Unfortunately, it is also possible that good maintenance is nowadays seen as inefficient.

The mitigation skeptics somehow thought that the effect would go into the other direction. That the bad paints used in the past would be a cooling bias, rather than a warming bias. Something with infra-red albedo. Although most materials used have about the same infra-red albedo and the infra-red radiation fluxes are much smaller than the solar fluxes.

Anthony Watts started a paint experiment in his back garden in July 2007. The first picture below shows three Stevenson screens, a bare one, a screen with modern latex paint and one with whitewash, a chalk paint that quickly fades.



Already 5 months later in December 2007, the whitewash had deteriorated considerably; see below. This should lead to a warm bias for the whitewash screen, especially in summer.

Anthony Watts:

Compare the photo of the whitewash paint screen on 7/13/07 when it was new with one taken today on 12/27/07. No wonder the NWS dumped whitewash as the spec in the 70’s in favor of latex paint. Notice that the Latex painted shelter still looks good today while the Whitewashed shelter is already deteriorating.

In any event the statement of Patrick Michaels “Weather equipment is very high-maintenance. The standard temperature shelter is painted white. If the paint wears or discolors, the shelter absorbs more of the sun’s heat and the thermometer inside will read artificially high.” seems like a realistic statement in light of the photos above.

I have not seen any data from this experiment beyond a plot with one day of temperatures, which was a day one month after the start, showing no clear differences between the Stevenson screens. They were all up to 1°C warmer than the modern ventilated automatic weather station when the sun was shining. (That the most modern ventilated measurement had a cool bias was not emphasized in the article, as you can imagine.) Given that Anthony Watts maintains a stealth political blog against mitigation of climate change, I guess we can conclude that he probably did not like the results, that the old white wash screen was warmer and he did not want to publish that.

We may be able to make a rough estimate the size of the effect by looking at another experiment with a bad screen. In sunny Italy Giuseppina Lopardo and colleagues compared two old aged, yellowed and cracked screens of unventilated automatic weather stations that should have been replaced long ago with a good new screen. The picture to the right shows the screen after 3 years. They found a difference of 0.25°C after 3 years and 0.32°C after 5 years.

The main caveat is that the information on the whitewash comes from Anthony Watts. It may thus well misinformation that the American Weather Bureau used whitewash in the past. Lacquer paints are probably as old as 8000 years and I see no reason to use whitewash for a small and important weather screen. If anyone has a reliable source about paints used in the past, either inside or outside the USA, I would be very grateful.

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Related posts

Changes in screen design leading to temperature trend biases

Temperature bias from the village heat island

Temperature trend biases due to urbanization and siting quality changes

Climatologists have manipulated data to REDUCE global warming

Homogenisation of monthly and annual data from surface stations

References

Cook, B.I., S.P. Shukla, M.J. Puma, L.S. Nazarenko, 2014: Irrigation as an historical climate forcing. Climate Dynamics, 10.1007/s00382-014-2204-7.

Siebert, Stefan, Jippe Hoogeveen, Petra Döll, Jean-Marc Faurès, Sebastian Feick and Karen Frenken, 2006: The Digital Global Map of Irrigation Areas – Development and Validation of Map Version 4. Conference on International Agricultural Research for Development. Tropentag 2006, University of Bonn, October 11-13, 2006.

Siebert, S., Kummu, M., Porkka, M., Döll, P., Ramankutty, N., and Scanlon, B.R., 2015: A global data set of the extent of irrigated land from 1900 to 2005. Hydrology and Earth System Sciences, 19, pp. 1521-1545, doi: 10.5194/hess-19-1521-2015.

See also: Zhou, D., D. Li, G. Sun, L. Zhang, Y. Liu, and L. Hao (2016), Contrasting effects of urbanization and agriculture on surface temperature in eastern China, J. Geophys. Res. Atmos., 121, doi: 10.1002/2016JD025359.

Temperature bias from the village heat island

The most direct way to study how alterations in the way we measure temperature affect the registered temperatures is to make simultaneous measurements the old way and the current way. New technological developments have now made it much easier to study the influence of location. Modern batteries have made it possible to just install an automatically recording weather station anywhere and obtain several years of data. It used to be necessary to have nearby electricity access, permissions to use it and dig cables in most cases.

Jenny Linden used this technology to study the influence of the siting of weather stations on the measured temperature for two villages. One village was in North Sweden, one in the West of Germany. In both cases the center of the village was about half a degree Centigrade (one degree Fahrenheit) warmer than the current location of the weather station on grassland just outside the villages. This is small compared to the urban heat island found in large cities, but it is comparable in size to the warming we have seen since 1900 and thus important for the understanding of global warming. In urban areas, the heat island can be multiple degrees and is studied much because of the additional heat stress it produces. This new study may be the first for villages.

Her presentation (together with Jan Esper and Sue Grimmond) at EMS2014 (abstract) was my biggest discovery in the field of data quality in 2014. Two locations is naturally not not enough for strong conclusions, but I hope that this study will be the start of many more, now that the technology has been shown to work and the effects to be significant for climate change studies.

The experiments

A small map of Haparanda, Sweden, with all measurement locations indicated by a pin. Mentioned in the text are Center and SMHI current met-station.

The Swedish case is easiest to interpret. The village [[Haparanda]] with 5 thousand inhabitants is in the North of Sweden, on the border with Finland. It has a beautiful long record, measurements started in 1859. Observations started on a North wall in the center of the village and were continued there until 1942. Currently the station is on the edge of the village. It is thought that the center did not change much any more since 1942. Thus the difference could be interpreted as the cooling bias due to the relocation from the center to its current location in the historical observations. The modern measurement was not at the original North wall, but free standing. Thus only the difference of the location can be studied.

As so often, the minimum temperature at night is affected most. It has a difference of 0.7°C between the center and the current location. The maximum temperature only shows a difference of 0.1°C. The average temperature has a difference of 0.4°C.

The village [[Geisenheim]] is close to Mainz, Germany, and was the first testing location for the equipment. It has 11.5 thousand inhabitants and is on the right bank of the Rhine. Also this station has a quite long history and started in 1884 in a park and stayed there until 1915. Now it is well-sited outside of the village in the meadows. A lot has changed in Geisenheim between 1915 and now. So we cannot make any historical interpretation of the changes, but it is interesting to compare the measurements in the center with the current ones to compare with Haparanda and to get an idea how large the maximum effect would theoretically be.

A small map of Geisenheim, Germany. Compared in the text are Center and DWD current met-station. The station started in Park.

The difference in the minimum temperature between the center and the current location is 0.8°C. In this case also the maximum temperature has a clear difference of 0.4°C. The average temperature has a difference of 0.6°C.

The next village on the list is [[Cazorla]] in Spain. I hope the list will become much longer. If you have any good suggestions please comment below or write Jenny Linden. Especially locations where the center is still mostly like it used to be are of interest. And as much different climate regions should be sampled as possible.

The temperature record

Naturally not all stations started in villages and even less exactly in the center. But this is still a quite common scenario, especially for long series. In the 19th century thermometers were expensive scientific instruments. The people making the measurements were often the few well-educated people in the village or town, priests, apothecaries, teachers and so on.

Erik Engström, climate communicator of the Swedish weather service (SMHI) wrote:

In Sweden we have many stations that have moved from a central location out to a location outside the village. ... We have several stations located in small towns and villages that have been relocated from the centre to a more rural location, such as Haparanda. In many cases the station was also relocated from the city centre to the airport outside the city. But we also have many stations that have been rural and are still rural today.

Improvements in siting may be even more interesting for urban stations. Stations in cities have often been relocated (multiple times) to better sited locations, if only because meteorological offices cannot afford the rents in the center. Because the Urban Heat Island is stronger, this could lead to even larger cooling biases. What counts is not how much the city is warming due to its growth, but the siting of the first station location versus its current one.

More specifically, it would be interesting to study how much improvements in siting have contributed to a possible temperature trend bias in the recent decades. The move to the current locations took place in 2010 in Haparanda and in 2006 in Geisenheim. Where it should be noted that the cooling bias did not take place in one jump: decent measurements are likely to have been recorded since 1977 in Haparanda, and since 1946 in Geisenheim; For Geisenheim the information is not very reliable).

It would make sense to me that the more people started thinking about climate change, the more the weather services realized that even small biases due to imperfect siting are important and should be avoided. Also modern technology, automatic weather stations, batteries and solar panels, have made it easier to install stations in remote locations.

An exception here is likely the United States of America. The Surface Stations project has shown many badly sited stations in the USA and the transition to automatic weather stations is thought to have contributed to this. Explanations could be that America started early with automation, the cables were short and the technician had only one day to install the instruments.

When also villages have a small urban effect, it is also possible that this gradually increases while the village is growing. Such a gradual increase can also be removed by statistical homogenization by comparison with its neighboring stations. However, if too many stations have a such a gradual inhomogeneity, the homogenization methods will no longer be able to remove this non-climatic increase (well). Thus this finding makes it more important to make sure that sufficient really rural stations are used for comparison.

On the other hand, because a village is smaller, one may expect that the "gradual" increases are actually somewhat jumpy. Rather than being due to many changes in a large area around the station, in case of a village the changes may be expected to be more often nearer to the station and produce a small jump. Jumps are easier to remove by statistical homogenization than smooth gradual inhomogeneities, because the probability of something happening simultaneously in the neighboring station is smaller.

A parallel measurement in Basel, Switzerland. A historical Wild screen, which is open to the bottom and to the North and has single Louvres to reduce radiation errors, measures in parallel with a Stevenson screen (Cotton Region Shelter), which is close to all sides and has double Louvres.

Parallel measurements

These measurements at multiple locations are an example of parallel measurements. The standard case is that an old instrument is compared to a new one while measuring side by side. This helps us to understand the reasons for biases in the climate record.

From parallel measurements we, for example, also know that the way temperature was measured before the introduction of Stevenson Screens has caused a bias in the old measurements of up to a few tenth of a degree. With differences of 0.5°C being found for two locations Spain and two tropical countries, while the differences in North West Europe are typically small.

To be able to study these historical changes and their influence on the global datasets, we have started an initiative to build a database with parallel measurements under the umbrella of the International Surface Temperature Initiative (ISTI), the Parallel Observations Science Team (POST). We have just started and are looking for members and parallel datasets. Please contact us if you are interested.

[UPDATE. The above study is now published as. Lindén, J., C.S.B. Grimmond, and J. Esper: Urban warming in villages, Advances in Science and Research, 12, pp. 157-162, doi: 10.5194/asr-12-157-2015, 2015.]

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