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Response times of meteorological air temperature sensors
Guidelines in the Guide to Meteorological Instruments and Methods of Observation (the CIMO guide) of the World Meteorological Organization (WMO, 2014, updated 2017, section 2.1.3.3, Response times of thermometers) recommend that the 63% response time τ for an air temperature sensor be 20 s, although—as airflow speed influences response time—the minimum airflow speed at which this applies should also be specified in the document. A 63 % response time τ63 = 20 s implies that 95% of a step change be registered within 3τ63 or 60 s, the WMO recommended averaging interval for air temperature: rapid air temperature changes on this timescale are not uncommon, often associated with convective squalls, frontal systems or sea breeze circulations. An alternative way of expressing the effect of the time constant is that in air whose temperature is changing at 0.1 K/minute the thermometer would lag by approximately 0.03 K.
To assess whether this response time specification was realistic, we have undertaken an experimental and theoretical study of the time constants of meteorological thermometers. Laboratory wind tunnel tests were undertaken to quantify 63% and 95% response times of 25 commercial 100 Ω platinum resistance thermometers (PRTs) of various sizes (length and sheath diameter) from five manufacturers. The test results revealed a fourfold difference in response times between different sensors: none of the PRTs tested met the CIMO response time guideline at a ventilation speed of 1 m s-1 typical of passively-ventilated thermometer shields such as Stevenson-type thermometer screens. A theoretical model of the sensors was devised which matched the experimental behaviour with regard to the most important contributing factors, namely ventilation rate and sensor diameter. Finally, suggestions and recommendations for operational air temperature sensor adoption and future sensor development are included
A Framework for Incorporating the Impact of Water Quality on Water Supply Stress: An Example from Louisiana
Water of poor quality can directly impact the budget of water available for key user groups. Despite this importance, methods for quantifying the impact of water quality on water availability remain elusive. Here, we develop a new framework for incorporating the impact of water quality on water supply by modifying the Water Supply Stress Index (WaSSI). We demonstrate the usefulness of the framework by investigating the impact of high salinity waters on the availability of irrigation water for agriculture in Louisiana. The WaSSI was deconstructed into sectoral components such that the total available water supply could be reduced for a particular demand sector (agricultural irrigation in this example) based on available water quality information. The results for Louisiana highlight substantial impacts on water supply stress for farmers attributable to the landward encroachment of saline surface water and groundwater near the coast. Areas of high salinity near the coast also increased the competition for freshwater resources among the industrial, municipal, and agricultural demand sectors in the vicinities of the municipal areas of Lake Charles, Lafayette, and Baton Rouge, Louisiana. The framework developed here is easily adaptable for other water quality concerns and for other demand sectors, and as such can serve as a useful tool for water managers