Presentation on theme: "Field experiment on the effects of a nearby asphalt road on temperature measurement Mariko Kumamoto 1, Michiko Otsuka 2, Takeshi Sakai 1 and Toshinori."— Presentation transcript:
Field experiment on the effects of a nearby asphalt road on temperature measurement Mariko Kumamoto 1, Michiko Otsuka 2, Takeshi Sakai 1 and Toshinori Aoyagi 2 1 Meteorological Instruments Center, JMA, Tsukuba, Japan 2 Meteorological Research Institute (MRI), Tsukuba, Japan TECO-2012 (Brussels,Belgium,17 Oct. 2012) 3（5）3（5） S N wind Summer Meteorological Instruments Center, Japan Meteorological Agency (JMA) 1 http://www.jma.go.jp/jma/indexe.html http://www.jma.go.jp/jma/jma-eng/jma-center/ric/RIC_HP.html
However, interpretation of such metadata is unclear without any theory or guidelines based on related experiment or research. Metadata describing site environment would be helpful. e.g. the WMO siting classification (CIMO Guide) Needs for observing temperature data of high quality from data users Many JMA stations are located in urbanized areas and surrounded by artificial heat source (buildings, car roads, car parks, artificial surfaces … ).. 0．Background 2
1. Purpose of Study 3 Focus on the effects from asphalt surface on temperature measurement Clarify the characteristics of temperature distribution near an asphalt car road – With relation to the distance from the road, wind condition and mounting height of sensors Better interpretation of siting metadata to estimate temperature measurement uncertainty Glass Asphalt road T ref T 1 Ｔ 2 Ｔ 3 Ｔ 4 Heated Air WIND
Sample points T4 T3 T2 T1 Reference point T0 10.0m 6.9m 3.2m 10.0m 0.8m Distances from the road (m) 2m Prevailing wind direction Summer: S (SSW-ESE) □ : Experiment Site (square 100m) as area below indicates ● : Thermometers with radiation shield ： Asphalt Road 2．Data and method 2-1. Field layout and sensor installations Summer : 30 th June - 1 st Oct. 2010, Winter :29 th Nov. 2010 - 6 th Jan. 2011 4 Difference( ℃ ) δT = TN – T0 (compared at the same height) The height of temperature measurement is 1.5m on JMA operational observation. T0 TN (N=1,2,3,4) 0.5m 1.5m 2.5m (Image:Google Maps) height In winter, the prevailing wind direction was NW (WNW-NE), so the sensors were installed on the opposite side. Screen with artificial ventilation ( Thermometer ) Ultrasonic anemometer Surface temperature (Asphalt road, glass)
Class 3, 4, and 5 are determined by the environment within 10m in radius. 2-2. WMO siting classification and sampling points 5 ● Temperature by the WMO siting classification (2010) （ surface of heat sources ［％］） ・ not meeting the requirement of Class4 ・ less than 50 % circular area of 10m ・ less than 30 % circular area of 3m class3 class2class1 class3 class2 class1 10m circle 30m circle 100m circle class5 class4 class5 class4 circle 10m in radius S ［％］ 45 ％ 30 ％ 10 ％ 0 ％ class5 class4class3 class3 class5 class4 class3 class3 10m 0.8m 3.2m 6.9m 10.0m T1 T2 T3 T4 up to 1 ℃ up to 2 ℃ Uncertainty up to 5 ℃ ● The distances from the road and S ［％］ at each sampling point （ the ratio of the area occupied by the road within 10m in radius) The distance from the road for each sampling point was determined to represent the conditions of Class 3, 4 and 5 in the WMO siting classification.
Frequency ×10 3 Summer 3. Results 3 - 1. Wind direction frequency and δT distribution （ 30 th June - 1 st Oct. 2010） 1.5m 0.5m 2.5m T1 0.8 m T2 3.2 m T3 6.9m T4 10.0m δT( ℃ ) (℃)(℃) (℃)(℃) (℃)(℃) heights distances Frequency ×10 3 class5 class4class3 class3 class5 class4 class3 class3 at different distances / heights At 0.5m height in case of southerly wind, the highest frequency of biases were up to +0.2 to +0.4 ℃ At 1.5m height, only small biases were seen near the road. No significant biases at T2, T3 and T4. 6
Frequency ratio ×0.01 ［％］ 3－2. By wind speed δT frequency distributions (Surface temperature difference ≧ 10 °C) +0.2 ℃ +0.1 ℃ +0.5 ℃ +0.3 ℃ 1.5m 0.5m 2.5m Wind speed ［ m/s ］ 7 T1 0.8 m T2 3.2 m T3 6.9m T4 10.0m Summer (30 th June - 1 st Oct. 2010) Southerly δT( ℃ ) (℃)(℃) ［ m/s ］ (℃)(℃) (℃)(℃) heights distances class5 class4class3 class3 class5 class4 class3 class3 In all cases, the stronger the wind, the fewer large biases At 0.5m height, the highest frequency of δTs and the range of δTs variation were larger when the wind was less than 2m/s. At 1.5m height, even when the wind speed was relatively weak, the highest frequency of δTs appeared around 0.0 ℃ to +0.2 ℃ regardless of the distance from the road.
4．Summary 8 The extent of effects of the asphalt road (10m in width) A t the height of 1.5 m, t he high frequency of δTs for the total period was around +0.1 – +0.2 ℃ and 0.0 ℃, for summer and for winter respectively. At the height of 0.5 m, t he effect depends significantly on the distance from the road. Not much difference at the height of 1.5 m. When the wind speed is over 2 m/s in summer or over 1 m/s in winter, t he effect is reduced. We presented only summer cases. If you would like to know winter cases or much more in details, please read papers.
よとｈ 5. Conclusion 9 The effects of the road depend much on prevailing wind directions. were reduced when the wind was relatively strong. In the implementation of the WMO siting classification, we also need to take wind conditions into account. From the results of the field experiment, As a next step, we study the effects of nearby trees on the wind speed and temperature measurement by field experiment. Surrounding objects such as buildings or trees may reduce the wind speed and affect temperature measurement. How effect by the windward side? 0 40m (Image:Google Maps)
To support reliable high-quality climate monitoring, it is necessary to consider how environmental changes around the site influence observation data. The examination is performed to allow quantitative evaluation for the effects of trees located at one side of the field on temperature and wind measurement data. Fig. Layout of instrumentation 10 ● Another Experiment ( currently in progress ) －Influences by the trees around the observation field－