Addressing the Challenge of Interpreting Microclimatic Weather Data Collected from Urban Sites

Abstract

This paper presents some installation and data analysis issues from an ongoing urban air temperature and humidity measurement campaign in Hangzhou and Ningbo, China. The location of the measurement sites, the positioning of the sensors and the harsh conditions in an urban environment can result in missing values and observations that are unrepresentative of the local urban microclimate. Missing data and erroneous values in micro-scale weather time series can produce bias in the data analysis, false correlations and wrong conclusions when deriving the specific local weather patterns. A methodology is presented for the identification of values that could be false and for determining whether these are “noise”. Seven statistical methods were evaluated in their performance for replacing missing and erroneous values in urban weather time series. The two methods that proposed replacement with the mean values from sensors in locations with a Sky View Factor similar to that of the target sensor and the sensors closest to the target’s location performed well for all Day-Night and Cold-Warm days scenarios. However, during night time in warm weather the replacement with the mean values for air temperature of the nearest locations outperformed all other methods. The results give some initial evidence of the distinctive urban microclimate development in time and space under different regional weather forcings.

Share and Cite:

Bourikas, L. , Shen, T. , James, P. , Chow, D. , Jentsch, M. , Darkwa, J. and Bahaj, A. (2013) Addressing the Challenge of Interpreting Microclimatic Weather Data Collected from Urban Sites. Journal of Power and Energy Engineering, 1, 7-15. doi: 10.4236/jpee.2013.15002.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, “World Population Prospects: The 2010 Revision and World Urbanization Prospects: The 2011 Revision,” 2012, UN ESA.
[2] R. A. Memon, D. Y. C. Leung and L. Chunho, “A Review on the Generation, Determination and Mitigation of Urban Heat Island,” Journal of Environmental Sciences, Vol. 20, No. 1, 2008, pp. 120-128. http://dx.doi.org/10.1016/S1001-0742(08)60019-4
[3] A. Mylona, “The Use of UKCP09 to Produce Weather Files for Building Simulation,” Building Services Engineering Research and Technology, Vol. 33, No. 1, 2012, pp. 51-62. http://dx.doi.org/10.1177/0143624411428951
[4] F. Chen, et al., “The Integrated WRF/Urban Modelling System: Development, Evaluation, and Applications to Urban Environmental Problems,” International Journal of Climatology, Vol. 31, No. 2, 2011, pp. 273-288. http://dx.doi.org/10.1002/joc.2158
[5] A. Baklanov, et al., “Hierarchy of Urban Canopy Parameterisations for Different Scale Models,” In: A. Mahura and A. Baklanov, Eds, MEGAPOLI Project Scientific Report 10-04, Danish Meteorological Institute, DMI: Copenhagen, 2010.
[6] V. Masson, C. S. B. Grimmond and T. R. Oke, “Evaluation of the Town Energy Balance (TEB) Scheme with Direct Measurements from Dry Districts in Two Cities,” Journal of Applied Meteorology, Vol. 41, No. 10, 2002, pp. 1011-1026.
[7] C. S. B. Grimmond and T. R. Oke, “Turbulent Heat Fluxes in Urban Areas: Observations and a Local-Scale Urban Meteorological Parameterization Scheme (LUMPS),” Journal of Applied Meteorology, Vol. 41, No. 7, 2002, pp. 792-810. http://dx.doi.org/10.1175/1520-0450(2002)041<0792:THFIUA>2.0.CO;2
[8] A. J. Arnfield, “Two Decades of Urban Climate Research: A Review of Turbulence, Exchanges of Energy and Water, and the Urban Heat Island,” International Journal of Climatology, Vol. 23, No. 1, 2003, pp. 1-26. http://dx.doi.org/10.1002/joc.859
[9] J. Bouyer, C. Inard and M. Musy, “Microclimatic Coupling as a Solution to Improve Building Energy Simulation in an Urban Context,” Energy and Buildings, Vol. 43, No. 7, 2011, pp. 1549-1559. http://dx.doi.org/10.1016/j.enbuild.2011.02.010
[10] F. Rubel and M. Kottek, “Observed and Projected Climate Shifts 1901-2100 Depicted by World Maps of the KöppenGeiger Climate Classification,” Meteorologische Zeitschrift, Vol. 19, No. 2, 2010, pp. 135-141. http://dx.doi.org/10.1127/0941-2948/2010/0430
[11] Esri, “ArcGIS 10. GIS Software Suite,” 2012. http://www.esri.com/software/arcgis
[12] Hangzhou Statistical Bureau, “Statistical YearBook of Hangzhou 2012,” China Statistical Press, Beijing, 2012.
[13] Ningbo Municipal Statistics Bureau, “Ningbo Statistical YearBook 2012,” China Statistical Press, Beijing, 2012.
[14] Information Office of the State Council of the People’s Republic of China, “China’s Policies and Actions for Addressing Climate Change,” 2008. http://www.gov.cn/english/2008-10/29/content_1134544.htm
[15] China Daily, “Summer Heat Leaves Cities Gasping as Mercury Rises,” 2013. http://www.chinadaily.com.cn/cndy/2013-07/17/content_16786059.htm
[16] Best News, “Hangzhou Ranked New ‘Four Fournaces’ Third Old Foundation Hangzhou Sign,” 2013. http://www.best--news.us/news-4918452-Hangzhou-ranked-new-four-furnaces-third-old-foundation-Hangzhou-sigh.html
[17] Maxim Integrated, “iButton Temperature/Humidity Logger with 8 kb Data Logger Memory”. http://www.maximintegrated.com/products/ibutton/data-logging/
[18] T. R. Oke, “Initial Guidance to Obtain Representative Meteorological Observations at Urban Sites,” Instruments and Observing Methods (WMO/TD-No. 1250):47, 2006. http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-81/IOM-81-UrbanMetObs.pdf
[19] World Meteorological Organisation, “Guide to Meteorological Instruments and Methods of Observation. Sixth Edition,” WMO-No. 8, Geneva, 1996.
[20] Hangzhou Academy of Urban Planning & Design, “Hangzhou General Planning Map,” Hangzhou, China, 2006.
[21] Ningbo Urban Planning Bureau, “Ningbo General Planning Map (2004-2020),” Ningbo, China, 2003.
[22] Google Earth, “Satellite Images and Maps of Hangzhou and Ningbo, China,” 2013.
[23] H. K. W. Cheung, G. J. Levermore and R. Watkins, “A Low Cost, Easily Fabricated Radiation Shield for Temperature Measurements to Monitor Dry Bulb Air Temperature in Built Up Urban Areas,” Building Services Engineering Research and Technology, Vol. 4, No. 31, 2010, pp. 371-380. http://dx.doi.org/10.1177/0143624410376565
[24] IBM Corp., “IBM SPSS Statistics for Windows,” Version 19.0. Released 2010, Armonk, NY: IBM Corp.
[25] The Weather Underground, “Hangzhou Weather Data from from Mantou Mountain’s National Principle WMOListed Weather Station”. http://www.wunderground.com/
[26] NIST/SEMATECH, “e-Handbook of Statistical Methods,” 2013. http://www.itl.nist.gov/div898/handbook/

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.