Tomato Sauce Throws Off Rain Gauge, Causing Rainfall to Be Underestimated by More Than 10%

A small smear of tomato sauce can make a rain gauge report substantially less rain than actually falls. Taiwan’s Central Weather Administration used the condiment in an experiment designed to show how contamination affects the instruments behind daily weather figures.

Lin Yu-jen, section chief of the agency’s Atmospheric Observation Division, described the testing during a meteorological training course. A tipping-bucket rain gauge collects water through a funnel. Once a bucket accumulates a fixed amount, it tips, and the system converts the number of turns into a rainfall measurement.

The mechanism has a limitation during intense rain. Water can continue flowing into the gauge while the bucket is still tipping, meaning stronger rainfall can lead to an underestimated total. The agency’s experiments found that several gauges produced increasingly low readings as rainfall intensity rose.

The tests also examined contamination at the bucket’s contact point. After tomato sauce remained in place for 15.5 hours, the average instrument error reached minus 10.46%. The comparable figures were minus 2.35% in dry conditions, minus 3.89% with pure water and minus 3.81% with silicone oil. The results indicated that more viscous contamination had a stronger effect on the instrument.

Rainfall gauges in remote automatic weather stations can also become blocked by fallen leaves. Their sheltered, warm interiors may attract insects or small animals, which can jam the mechanism and leave the system showing no rainfall despite wet conditions. Lin said regular maintenance is therefore essential.

The location of an instrument matters as well. Parking lots, concrete buildings, trees, vegetation and terrain can distort temperature readings. Newer observation systems use multiple safeguards, including three thermometers that cross-check one another. The agency describes the newer systems as digital, redundant, less exposed to interference and more accurate.

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Weather data may look like just a string of numbers on a screen, but behind it are instrument calibration, the station environment and daily maintenance. A problem at any small link can make weather observations differ by a hair.