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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 Jennifer Vanos, PhD Assistant Professor of Atmospheric Science Texas Tech University November 6, 2014. Urbanization and Global Environmental Change

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Page 1: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Assessment of Localized Urban Climates

and Associations with Air Pollution and

Synoptic Weather Patterns

Aaron Hardin, MS Candidate, Texas Tech University

Jennifer Vanos, PhDAssistant Professor of Atmospheric ScienceTexas Tech University

November 6, 2014. Urbanization and Global Environmental Change

Page 2: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

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.

Page 3: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

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

Page 4: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Baltimore, 125 stations

Page 5: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Daytime/Nighttime UHI

Page 6: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Nighttime UHI Baltimore/Boston 2006-2013

Page 7: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Variation in Heating

Page 8: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University
Page 9: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Application of Results

Page 10: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Air Pollution Variations by Site: Summer 2007

1

2

3

Page 11: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

July 2007 Variations 1

2

3

Page 12: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

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.

Page 13: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Thanks! Questions?Email: [email protected]

Page 14: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Average DT Day Boston

Page 15: Assessment of Localized Urban Climates and Associations with Air Pollution and Synoptic Weather Patterns Aaron Hardin, MS Candidate, Texas Tech University

Human Energy Budget Modeling

Absorbed Radiation (RRT)

Metabolism (M)(Mnet = M − W)

Evaporation (E)

Emitted LW Radiation (Lemit)

Convective Heat (C)

RRT

BUDGET (W m-2) = Mnet + RRT – C – E – LemitBUDGET (W m-2) = Mnet + RRT – C – E – Lemit

Fiala et al., (1999)