Abstract
Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.
Highlights
Meteorology monitoring is highly required in many domains, e.g., weather forecasting, agricultural, traffic [1], etc
We found the relevance among NodeAT, AwsAT and AwsSR and proposed an original approach to reduce the error of NodeAT based on the value of solar radiation (SR)
More than 60% of the error of NodeAT can be corrected by using this approach, and it can be applied to the real-time air temperature (AT) monitoring system in a practical scenario
Summary
Meteorology monitoring is highly required in many domains, e.g., weather forecasting, agricultural, traffic [1], etc. The high flexibility of WSNs makes it possible to deploy nodes swiftly in a disaster spot, and the low cost of the sensing node provides the possibility to control the cost of AT monitoring at an acceptable level Due to these advantages of WSNs, we established a meteorological WSN using our own sensing nodes to collect data of AT and other meteorological factors in a practical environment, involving our campus and other weather stations of meteorological departments. The standard data of air temperature and solar radiation used in this study are all collected by the AWS at Nanjing University of Information Science and Technology (NUIST). This AWS was founded according to the AWS construction technical standard and has a national base station Number.
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