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Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University.

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Presentation on theme: "Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University."— Presentation transcript:

1 Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University Jennifer Vanos, PhD Assistant Professor of Atmospheric Science Texas Tech University November 6, 2014. Urbanization and Global Environmental Change

2 Objectives Study the spatiotemporal differences in the surface UHI development and intensity, while different synoptic weather types are present, using meso-scale UrbaNet stations. Examine spatiotemporal differences between different stations to learn where the hottest regions in each city are. Determine what potential associations exist between differential urban heating & air pollution, + health effects.

3 UrbaNet Data Observational surface research network run by NOAA and Earth Networks, Inc. in 17 different cities in the U.S. Data from 2006 through 2013 5min or 60min averages of 19 different variables Very high spatial and temporal resolution. Instruments used: propeller and vane anemometer, temp/RH probe, and tipping bucket rain gauge. Temp, RH, Pressure Wind Velocity Source: http://madis.noaa.gov/urbanet.html

4 Baltimore, 125 stations UHI = T avg. urban – T avg. Rural

5 Daytime/Nighttime UHI

6 Nighttime UHI Baltimore/Boston 2006-2013

7 Variation in Heating

8

9 Application of Results

10 Air Pollution Variations by Site: Summer 2007 1 2 3

11 July 2007 Variations 1 2 3

12 Conclusions/Future Work Largest heat islands occur when dry weather type present. Most intense heat islands occur at night, moisture plays a role in weather type with largest UHI at night. DT hottest in urban area, MT+ hottest over entire area. Ability to see spatial variability of urban heating in very high detail. Potential to consider other meteorological variables (e.g. wind and humidity) in analysis. UrbaNet combined with air pollution sensors can support operational meteorologists for more localized forecasts.

13 Thanks! Questions? Email: Aaron.Hardin@ttu.edu

14 Average DT Day Boston

15 Human Energy Budget Modeling Absorbed Radiation (R RT ) Metabolism (M) ( M net = M − W) Evaporation (E) Emitted LW Radiation (L emit ) Convective Heat (C) R RT BUDGET (W m -2 ) = M net + R RT – C – E – L emit Fiala et al., (1999)


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