Presentation on theme: "David J. Sailor1 and Hongli Fan2 1. Portland State University"— Presentation transcript:
1David J. Sailor1 and Hongli Fan2 1. Portland State University Modeling the Impact of Anthropogenic Heating on the Urban Climate of HoustonDavid J. Sailor1 and Hongli Fan21. Portland State University2. Tulane UniversityAugust 2004Introduction…In prior research we have (1) established a methodology for generating Qf profiles for cities; (2) evaluated the impact of Qf on mesoscale model simulations of Philadelphia.In this work we (1) apply the methodology at very fine spatial scales; (2) evaluate impact of various spatial and temporal scales of Qf profiles in mesoscale model simulaitons of Houston.
2Motivation On average anthropogenic heating (Qf) is small timeQQswQfMotivationOn average anthropogenic heating (Qf) is smallpeak solar flux is ~1000 W m-2 in summercity-scale, daily average Qf is ~ 30 to 50 Wm-2Local peaks in anthropogenic heating can be a factor of higher than the city-scale average value*.In morning/evening Qf 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 SeasonalAnthropogenic Heating Profiles for Urban Areas,” Atmospheric Environment, 38 (17),
3A top-down methodology for Qf (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/km2]Determine consumption rates separately for residential, commercial, and industrial sectors.For further details see poster P3.6
4Estimating 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) populationsNeglect other visitors to city (hotel/conference/shoppers/etc)*
5Anthropogenic Heating in Houston at Various Scales Workday population density (centered on CBD)1,538 persons/km2 at city scale20,844 persons/km2 at census tract scaleup to 184,500 persons/km2 at TAZ scaleSince Qf scales with population density it can vary dramatically depending upon the scale of analysis
6Anthropogenic Heating in Houston at TAZ Scales Day (summer)Night (summer)
7In this study… we define 3 categories of urban land use and implement one distinct Qf profile for each category.High spatial resolution case: Q1Houston SummerCity-average (low spatial resolution case: Q2)
8Simulation Overview MM5 implementation: Simulation Episodes: Modified USGS land use with 3 new urban subcategoriesNo urban canopy parameterizationDiurnal land-use-dependent profile for QfQf input into near-surface air layer as DTModified Blackadar PBL scheme4 two-way nests, 1km grid cells in inner domainSimulation Episodes:Aug. 30, 2000Sept. 27, 2002Q0 – No anthropogenic heatingQ1 – Land-use specific profilesQ2 – Single city-scale avg. profile.
9Q1 – Q0:Near-surface air temperature difference between base case (no Qf) and spatially-detailed Qf case (~ C during night/morning, ~ C during day)Night (8pm)Morning (6am)Day (noon)092702083000Temperature Perturbation (avg. over city)
10Q1 – Q0:Near-surface air temperature difference between base case (no Qf) and spatially-detailed Qf case (~ C during night/morning, ~ C during day)45101009270245
11(DT ~ 0.5-2.0 oC during transitions; 0.2-0.4 oC during day ) Q1 – Q 2:Temp. difference between spatially-detailed Qf case and city-average Qf case:(DT ~ oC during transitions; oC during day )Vertical cross section (0-2.5km)9am11am7pm5pmSept. 27, 2002 simulation
12Conclusions and Future Work Qf in Houston is W/m2 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 Qf in MM5 creates a summer heat island signature in morning and night (~ 2.0 oC ) , with less impact during day ( ~ oC ).Including Qf 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 definitionsbetter vertical representation of Qf in MM5workday vs. non-workday profilesintegration with an urban canopy parameterizationinvestigate winter episodes