Quantification of Local Warming Trend: A Remote Sensing-Based Approach

PLoS One. 2017 Jan 10;12(1):e0169423. doi: 10.1371/journal.pone.0169423. eCollection 2017.

Abstract

Understanding the warming trends at local level is critical; and, the development of relevant adaptation and mitigation policies at those levels are quite challenging. Here, our overall goal was to generate local warming trend map at 1 km spatial resolution by using: (i) Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composite surface temperature data; (ii) weather station-based yearly average air temperature data; and (iii) air temperature normal (i.e., 30 year average) data over the Canadian province of Alberta during the period 1961-2010. Thus, we analysed the station-based air temperature data in generating relationships between air temperature normal and yearly average air temperature in order to facilitate the selection of year-specific MODIS-based surface temperature data. These MODIS data in conjunction with weather station-based air temperature normal data were then used to model local warming trends. We observed that almost 88% areas of the province experienced warming trends (i.e., up to 1.5°C). The study concluded that remote sensing technology could be useful for delineating generic trends associated with local warming.

MeSH terms

  • Alberta
  • Algorithms
  • Climate Change*
  • Environmental Monitoring
  • Models, Theoretical
  • Remote Sensing Technology*
  • Seasons
  • Temperature*

Grants and funding

The authors would like to acknowledge the following funding sources: (i) Alberta Innovates Technology Future (AITF) Fellowship to K. Rahaman, (ii) University Research Grants Committee (URGC) of the University of Calgary to Q. Hassan, and (iii) NSERC Discovery Grant to Q. Hassan.