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Modeling the Impact of Anthropogenic Heating on the Urban Climate of Houston David J. Sailor 1 and Hongli Fan 2 1. Portland State University.

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Presentation on theme: "Modeling the Impact of Anthropogenic Heating on the Urban Climate of Houston David J. Sailor 1 and Hongli Fan 2 1. Portland State University."— Presentation transcript:

1 Modeling the Impact of Anthropogenic Heating on the Urban Climate of Houston David J. Sailor 1 and Hongli Fan 2 sailor@cecs.pdx.edu 1. Portland State University 2. Tulane University August 2004

2 Motivation On average anthropogenic heating (Q f ) is small –peak solar flux is ~1000 W m -2 in summer –city-scale, daily average Q f is ~ 30 to 50 Wm -2 Local peaks in anthropogenic heating can be a factor of 10-20 higher than the city-scale average value *. In morning/evening Q f may affect boundary-layer transitions and mixing processes with important AQ implications * Sailor, D.J., and L. Lu, (2004) “A Top-Down Methodology for Developing Diurnal and Seasonal Anthropogenic Heating Profiles for Urban Areas,” Atmospheric Environment, 38 (17), 2737-2748. time Q Q sw QfQf

3 A top-down methodology for Q f (vehicles) (building sector) (metabolism) non-dimensional traffic profile [-] vehicle energy used per unit distance [W km -1 ] distance traveled per person [km] metabolic heat per person [W] electricity profile [-] heating fuel consumption [W] electricity consumption [W] heating fuel profile [-] population density [person/km 2 ] Determine consumption rates separately for residential, commercial, and industrial sectors. For further details see poster P3.6

4 Estimating population density Census Transportation Planning Package (CTPP*) –Need: population data from the basic census database underestimate daytime populations by ~ a factor of 2 at the city scale… –CTPP data available at range of scales (city, census tract, TAZ) –Residents, non-working residents, workers, time-of-arrival data… –Estimate nighttime and daytime (workday) populations –Neglect other visitors to city (hotel/conference/shoppers/etc) * www.bts.dot.gov

5 Anthropogenic Heating in Houston at Various Scales Workday population density (centered on CBD) –1,538 persons/km 2 at city scale –20,844 persons/km 2 at census tract scale –up to 184,500 persons/km 2 at TAZ scale Since Q f scales with population density it can vary dramatically depending upon the scale of analysis

6 Anthropogenic Heating in Houston at TAZ Scales Day (summer)Night (summer)

7 City-average (low spatial resolution case: Q2) Houston Summer In this study… we define 3 categories of urban land use and implement one distinct Q f profile for each category. High spatial resolution case: Q1

8 Simulation Overview MM5 implementation: Modified USGS land use with 3 new urban subcategories No urban canopy parameterization Diurnal land-use-dependent profile for Q f Q f input into near-surface air layer as  T Modified Blackadar PBL scheme 4 two-way nests, 1km grid cells in inner domain Simulation Episodes: Aug. 30, 2000 Sept. 27, 2002 Q0 – No anthropogenic heating Q1 – Land-use specific profiles Q2 – Single city-scale avg. profile.

9 Night (8pm) Morning (6am) Day (noon) 092702083000 Temperature Perturbation (avg. over city) Q 1 – Q 0 : Near-surface air temperature difference between base case (no Q f ) and spatially- detailed Q f case (~ 2-2.5 0 C during night/morning, ~ 0.25-0.5 0 C during day)

10 092702 10 45 Q 1 – Q 0 : Near-surface air temperature difference between base case (no Q f ) and spatially- detailed Q f case (~ 2-2.5 0 C during night/morning, ~ 0.25-0.5 0 C during day)

11 7pm 5pm Sept. 27, 2002 simulation Q 1 – Q 2 : Temp. difference between spatially-detailed Q f case and city-average Q f case: (  T ~ 0.5-2.0 o C during transitions; 0.2-0.4 o C during day ) 9am 11am Vertical cross section (0-2.5km)

12 Conclusions and Future Work Q f in Houston is 30-50 W/m 2 at the city scale, but may be a factor of 10 to 20 larger in isolated regions within the core of the city. CTPP data are useful for population-based analyses of anthropogenic heating (and moisture), but refinements & extensions are possible. Addition of Q f in MM5 creates a summer heat island signature in morning and night (~ 2.0 o C ), with less impact during day ( ~ 0.25-0.5 o C ). Including Q f at high spatial resolution can generate local temperature perturbations of up to several degrees C compared with use of city-average profiles. Effect is largely limited to morning/evening transition hours. Next steps include: –use improved landuse database and refined surface characteristic definitions –better vertical representation of Q f in MM5 –workday vs. non-workday profiles –integration with an urban canopy parameterization –investigate winter episodes sailor@cecs.pdx.edu www.cecs.pdx.edu/~sailor


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