A wall measurement at the Mathematical Tower in Kremsmünster. You mainly see the bright board to protect the instruments against rain, which is on the first floor, at the base of the window, a little right of the entrance.
HistoryThe history of changes in exposure is different in every country, but in broad lines follows this pattern. In the beginning thermometers were installed in unheated rooms or in front of a window of an unheated room on the North (poleward) side of a building.
When this was found to lead to too high temperatures a period of innovation and diversity started. For example, small metal cages were added to the North wall measurements. More importantly free standing structures were designed: stands, shelters, houses and screens. In the Common Wealth the Glaisher (Greenwich) stand was prevalent. It has a vertical wooden board, a small roof and sides, but it is fully open in the front and in summer you have to rotate it to ensure that no direct sun gets onto the thermometer.
Shelters were build with larger roofs and sides, but still open to the front and the bottom, for example the Mountsouris and Wild screens. Sometimes even small houses or garden sheds were build, in the tropics with a thick thatched roof.
In the end, the [[Stevenson screen]] (Cotton Region Shelter) won the day. This screen is closed to all sides. It has double Louvre walls, double boards as roof and a board as bottom. (Early designs sometimes did not have a bottom.)
In the recent decades there is a move to Automatic Weather Stations (AWS), which do not have a normal (liquid in glass) thermometer, but an electrical resistance temperature sensor and is typically screened by multiple round plastic cones. These instruments are sometimes mechanically ventilated, reducing radiation errors during calm weather. Some countries have installed their automatic sensors in Stevenson screens to reduce the non-climatic change.
Radiation errorsTo understand when and where the temperature measurements have most bias, we need to understand how solar and heat radiation leads to measurement errors.
The temperature sensor should have the temperature of the air and should thus not be warmed or cooled by solar or heat radiation. The energy exchange between sensor and air due to ventilation should thus be large relative to the radiative exchanges. One of the reasons why temperature measurements outside are so difficult is that these are conflicting requirements: closing the screen for radiation will also limit the air flow. However, with a smart design, mechanical ventilation and small sensors this conflict can be partially resolved.
For North-wall observations direct solar radiation on the sensor was sometimes a problem during sunrise and sunset. In addition the sun may heat the wall below the thermometer and warm the rising air. Even for Stevenson screens some solar radiation still gets into the screen. Furthermore, the sun shining on the screen warms it, which can then warm the air flowing through the screen. For this reason it is important that the screen is regularly painted white and cleaned.
Scattered solar radiation (clouds, vegetation, surface) is important for older screens being open to the front. The open front also leads to a direct cooling of the sensor as it emits heat radiation. The net heat radiation flux is especially large when the back radiation of the atmosphere is low, thus when there are no clouds and the air is dry. Warm air can contain more humidity, thus these effects are generally also largest when it is cold.
Because older screens did not have a bottom, a hot surface below the screen could be a problem during the day and a cold surface during the night. This especially happens when the soil is dry and bare.
All these effects are most clearly seen when the wind is calm.
Concluding, we expect the cooling bias at night to be largest when the weather is calm, cloud free and the air is dry (cold). We also expect a warming bias during the day to be largest when the weather is calm and cloud free. In addition we can get a warm bias when the soil is dry and bare and in summer during sunrise and sunset.
Thus all things being equal, the radiation error is expected to be largest in sub-tropic, tropical and continental climates and small in maritime, moderate and cold climates.
Schematic drawing of the various factors that can lead to radiation errors.
Parallel measurementsWe know how large these effects are from parallel measurements, where an old and new measurement set-up are compared side by side. Unfortunately, there are not that many of parallel measurements for the transition to Stevenson screens. Many parallel measurements in North-West Europe, a maritime, moderate or cold climate, where the effects are expected to be small of those are described in a wonderful review article by David Parker (1994) and he concludes that in the mid-latitudes the past warm bias will be smaller than 0.2°C. In the following, I will have a look at the parallel measurements outside of this region.
In the topics, the bias can be larger. Parker also describes two parallel measurements of a tropical thatched house with a Stevenson screen. One in India and one in Ceylon (Sri Lanka). They both have a bias of about 0.4°C. The bias naturally depends on the design, a comparison of a normal Stevenson screen with one with a thatched roof in Samoa shows almost no differences.
Recently two beautiful studies were made with modern automatic equipment to study the influence of the screens. With automatic sensors you can make measurements every 10 minutes, which helps in understanding the reasons for the differences. In Spain they have build two replicas of the French screen used around 1900. One was installed in [[La Coruna]] (more Atlantic) and one in [[Murcia]] (more Mediterranean). They showed that the old measurements had a temperature bias of about 0.3°C; the Mediterranean location had, as expected, a somewhat larger bias than the Atlantic one.
The second modern study was in Austria, at the Mathematical Tower in Kremsmünster (depicted at the top of this post). This North-wall measurement was compared to a Stevenson screen (Böhm et al., 2010). It showed a temperature bias of about 0.2°C. The wall was oriented North-North-East and during sunrise in summer the sun could shine on the instrument.
For both the Spanish and the Austrian examples it should be noted that small modern sensors were used. It is possible that the radiation errors would have been larger had the original thermometers been used.
Comparing a Wild screen with a Stevenson screen at the astronomical observatory in [[Basel]], Switzerland, Renate Auchmann and Stefan Brönnimann (2012) found clear signs of radiation errors, but the annual mean temperature was somehow not biased.
Adelaide]], Australia, we have a beautiful long parallel measurement of the Glaisher (Greenwich) stand with a Stevenson screen (Cotton Region Shelter). It runs 61 complete years (1887-1947) and shows that the historical Glaisher stand recorded on average 0.2°C higher temperatures; see figure with annual cycle below. The negative bias in the minimum temperature at night is almost constant throughout the year, the positive bias is larger and strongest in summer. Radiation errors thus not only affect the mean, but also the size of the annual cycles. They will also affect the daily cycle, as well as the weather variability and extremes in the temperature record.
The exact size of the bias of this parallel measurement has a large uncertainty, it varies considerably from year to year and the data also shows clear inhomogeneities itself. For such old measurements, the exact measurement conditions are hard to ascertain.
The annual cycle of the temperature difference between a Glaisher stand and a Stevenson screen. For both the daily maximum and the daily minimum temperature. (Figure 1 from Nicholls et al. (1996)
ConclusionsOur understanding of the measurements and limited evidence from parallel measurements suggest that there is a bias of a few tenth of a Centigrade in observations made before the introduction of Stevenson screens. The [[Stevenson screen]]
was designed in 1864, most countries switched in the decades around 1900, but some countries did not switch until the 1960ies.
The last few decades there was a new transition to automatic weather stations (AWS). Some countries have installed the automatic probes in Stevenson screens, but most have installed single unit AWS with multiple plastic cones as screen. The smaller probe and mechanical ventilation could make the radiation errors smaller, but depending on the design possibly also more radiation gets into the screen and the maintenance may also be worse now that the instrument is no longer visited daily. An review article on this topic is still dearly missing.
Last month we have founded the Parallel Observations Science Team (POST) as part of the International Surface Temperature Initiative (ISTI) to gather and analyze parallel measurements and see how they affect the climate record. (Not only with respect to the mean, but also for changes in day and annual cycles, weather variability and weather extremes.) Theo Brandsma will lead our study on the transition to Stevenson screens and Enric Aguilar the transition from conventional observations to automatic weather stations. If you know of any dataset and/or want to collaborate please contact us.
AcknowledgementWith some colleagues I am working on a review paper on inhomogeneities in the distribution of daily data. This work, especially with Renate Auchmann, has greatly helped me understand radiation errors. Mistakes in this post are naturally my own. More on non-climatic changes in daily data later.
Further readingA beautiful "must-read" article on temperature screens by Stephen Burt: What do we mean by ‘air temperature’? Measuring temperature is not as easy as you may think.
Just the facts, homogenization adjustments reduce global warming: The adjustments to the land surface temperature increase the trend, but the adjustments to the sea surface temperature decrease the trend.
Temperature bias from the village heat island
A database with parallel climate measurements describes the database we want to build with parallel measurements
A database with daily climate data for more reliable studies of changes in extreme weather gives somewhat more background
Statistical homogenisation for dummies
New article: Benchmarking homogenisation algorithms for monthly data
ReferencesAuchmann, R., and S. Brönnimann, 2012: A physics-based correction model for homogenizing sub-daily temperature series. Journal Geophysical Research, 117, D17119, doi: 10.1029/2012JD018067.
Böhm, R., P.D. Jones, J. Hiebl, D. Frank, M. Brunetti, M.Maugeri, 2010: The early instrumental warm-bias: a solution for long central European temperature series 1760–2007. Climatic Change, 101, no. 1-2, pp 41-67, doi: 10.1007/s10584-009-9649-4.
Brunet, M., Asin, J., Sigró, J., Bañón, M., García, F., Aguilar, E., Palenzuela, J. E., Peterson, T. C. and Jones, P., 2011: The minimization of the screen bias from ancient Western Mediterranean air temperature records: an exploratory statistical analysis. International Journal Climatology, 31, pp, 1879–1895, doi:
Nicholls, N., R. Tapp, K. Burrows, D. Richards. Historical thermometer exposures in Australia. International Journal of Climatology, 16, pp. 705-710, doi: 10.1002/(SICI)1097-0088(199606)16:6<705::AID-JOC30>3.0.CO;2-S, 1996.
Parker, D. E., 1994: Effects of changing exposure of thermometers at land stations. International Journal of Climatology, 14, pp. 1–31, doi: 10.1002/joc.3370140102.