Accessibility navigation


Quantifying uncertainties in climate data: measurement limitations of naturally ventilated thermometer screens

Harrison, R. G. and Burt, S. D. ORCID: https://orcid.org/0000-0002-5125-6546 (2021) Quantifying uncertainties in climate data: measurement limitations of naturally ventilated thermometer screens. Environmental Research Communications, 3 (6). 061005. ISSN 2515-7620

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

1MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1088/2515-7620/ac0d0b

Abstract/Summary

Climate science depends on accurate air temperature measurements. To achieve this, well ventilated thermometers protected from direct sunlight and precipitation are needed, commonly through using louvred enclosures known as screens or shields. Maintaining good natural ventilation is critical for accurate measurements. Ventilation effects on air temperature uncertainties are quantified here using an aspirated thermometer as a reference, for air temperatures spanning -2.8°C to 35.5°C. Of 81462 5 min mean temperature values obtained, 50% were within ±0.07°C of the reference and only 2% lay beyond -0.66°C to 0.47°C, where negative values represent the naturally ventilated screen thermometer underestimating air temperature. Larger absolute differences arose from a combination of radiation exchange and time response effects, which are separated here. Firstly, using 20s data, the exponential time response of the naturally ventilated thermometer is shown to vary with wind speed u as u-0.5, and exceeds the conventional 1 min averaging time for wind speeds up to 5 ms-1 (at 2 m height), increasing to at least 15 mins when calm. Secondly, radiation exchange effects (both by day and by night) dominated at low wind speeds (<1 ms-1 at 2 m height). Insufficient time response damps recording of temperature extremes, potentially also influencing climatological means. A new method to reduce the uncertainties is presented. This reduces negative skew in the temperature bias from -1.05 to -0.26, and, for almost 90% of the data, also reduces the spread.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:99129
Publisher:IOP Science

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation