1. Le projet CRTI: développement d’un système de modélisation à l’échelle urbaine Jocelyn Mailhot Stéphane Bélair Mario Benjamin Najat Benbouta Bernard Bilodeau Gilbert Brunet Frédéric Chagnon Michel Desgagné Jean-Philippe Gauthier Bruno Harvey Richard Hogue Séminaire CMC / RPN – 24 février 2006 RPN / CMC / Région du Québec Michel Jean Aude Lemonsu Alexandre Leroux Gilles Morneau Radenko Pavlovic Pierre Pellerin Claude Pelletier Lubos Spacek Linying Tong Serge Trudel Yufei Zhu

2. Objectives and Context Improve the representation of cities in Canadian meteorological models: accurate prediction of urban flows and atmospheric dispersion over major North American cities. improve urban surfaces and urban boundary layer in meso-  -scale and micro-  -scale (~ 20km down to 200m) atmospheric models Part of a larger-scale project within CRTI: development of an integrated multi-scale modeling system to provide decision making framework to minimize consequences injuries, casualties, and contamination prototype for Environmental Emergency Response Division in 2007 Project partners: R&D Defence Canada, AECL Universities of Waterloo and Calgary CFD microscale models (at street- and building-scales) Lagrangian stochastic dispersion models

3. « Urbanized » Regional-15 km GEM-variable « Urbanized » Meso-  -scale 2.5 km GEM-LAM « Urbanized » Micro-  -scale 250 m MC2-LAM High-res Microscale (CFD) Partners IC + LBC Operational Prototype Built areas are parameterized, i.e., we need TEB Urban surface databases Anthropogenic heat sources Built areas are resolved 1D (vertical) turbulence is sufficient 3D turbulence is required Off-line surface modeling At 100-200 m TEB Urban surfaces interface still TBD Urban Modeling System

4. WORK BREAKDOWN STRUCTURE Meso-  and off-line Regional NWP High-level management (Jean, Hogue) Scientific management (Mailhot, Bélair) MODELINGDATABASESTRANSFERS MEASUREMENTS and OBSERVATIONS TEB 3D-turbulence CFD Surface fields Anthropo. heat sources MUSE-1 MUSE-2

5. NameDescriptionPeople TEBInclude representation of urban surfaces in MSC’s modeling and forecasting systems and study the impact on the boundary layer Lemonsu (RPN), Bélair (RPN) Surface fieldsDevelop a methodology to generate urban surface databases that are required to run TEB Leroux CMC-Emer), Lemonsu (RPN), Bélair (RPN), Trudel (CMC-Emer), Gauthier (CMC-Emer) Anthropogenic heat sources Create a database that will provide anthropogenic heat fluxes over every major city of Canada (and eventually North America) Benbouta (CMC-Emer), Bélair (RPN), Hogue (CMC) 3D TurbulenceInclude a 3D-turbulence scheme in MSC’s atmospheric models (required to run these models at microscale) and evaluate the impact on atmospheric mixing Pelletier (RPN), Mailhot (RPN), Zhu (RPN) Meso-  -scale and off-line modeling Transfer the new technologies developed in this project to CMC’s forecasting systems (2.5 km and high-res off-line surface system) Tong (CMC-Devel.), Bélair (RPN), Lemonsu (RPN) Regional NWPTransfer the urban surface technology developed in CRTI to CMC’s 15-km operational regional weather forecasting system Pavlovic (CMC-AQ), Bélair (RPN), Mailhot (RPN) Micro-scale modeling (CFD) Develop MSC’s capabilities for building scale modelingPellerin (RPN), Pelletier (RPN), Mailhot (RPN) MUSE expsField experiments in Montreal to provide observational data for the verification of TEB in North American weather conditions Mailhot (RPN), Bélair (RPN), Lemonsu (RPN), Chagnon (CMC-E), Jean (CMC), Benjamin (Que. Region), Morneau (Que. Region) + more List of Activities

6. Urban Modeling System Main features of the new urban modeling system: High-resolution capability for micro-α scale applications (down to ~250m) Urban processes with Town Energy Balance (TEB) scheme (Masson, 2000) Generation of fields characterizing urban type covers (Lemonsu et al., 2006) 3D LES-type turbulent diffusion scheme. First validation of the urban modeling system: Impact of urban processes on structure of urban boundary layer Comparison against observations from the Joint Urban 2003 experimental campaign in Oklahoma City in July 2003 (Allwine et al., 2004) Comparison against observations from MUSE-1 (March-April 2005) for cold conditions and snow melt period.

7. TEB urban surface scheme roof road wall z bld W a bld Town Energy Balance (Masson, 2000) Urban canopy model parameterizing water and energy exchanges between canopy and atmosphere (based on urban canyon concept of Oke 1987) Model specifically dedicated to the built-up covers Three-dimensional geometry  Radiative trapping and shadow effect  Heat storage  Wind, temperature and humidity inside the street  Water and snow Idealized urban geometry  Mean urban canyon: 1 roof, 2 identical walls, 1 road  Isotropy of the street orientations  No crossing streets

8. To couple TEB with MC2 and GEM requires : Implementing a new type of surface in the physics package in order to take into account the urban areas Developing urban land-cover databases to document the spatial distribution and spatial variability of urban areas Defining the heat and humidity releases due to human activities (Anthropogenic sources) Sea ice Soil/Vegetation Glaciers Water Urban Coupling with MC2 and GEM

9. Urban Land-Cover Classification Methodology:  Based on joint analysis of satellite imagery (ASTER, Landsat-7) and digital elevation models (SRTM-DEM, NED, CDED1)  Produce 60-m resolution urban land-use land-covers  Methodology applied to major North American cities Classification:  Horizontal resolution adapted to micro-α-scale modeling  Number of urban classes (12) allowing the representation of urban variability Interest of the method:  Semi-automatic treatment  Limited number of data sources  Large availability of the databases

10. Methodology Surface element identification ASTER satellite image 15 m database Building height estimation SRTM-DEM - NED 1/3 10 m database Classification criteria to describe the urban landscapes and identify urban classes Aggregation at a lower resolution to compute the statistics of selected criteria on the new grid Decision tree Regrouping pixels whose criteria are similar and identification of urban classes Attribution of descriptive parameters Town Energy Balance input data  Water  Trees  Low vegetation  Grass  Bare soil and rocks  Roofs  Roads and parkings  Asphalt roads  Residential mixing  Veg/road mixing  Building height  Built fraction with elevation

11. Urban classification OKC 60-m resolution classification Including 12 new urban classes N High buildings Mid-high buildings Low buildings Very low buildings Sparse buildings Industrial areas Roads and parkings Road mix Dense residential Mid-density residential Low-density residential Mix of nature and built Soils Crops Short grass Mixed forest Mixed shurbs Water Excluded

12. NN Montreal 60-m resolution classification Vancouver 60-m resolution classification High buildings Mid-high buildings Low buildings Very low buildings Sparse buildings Industrial areas Roads and parkings Road mix Dense residential Mid-density residential Low-density residential Mix of nature and built Zoom

13. Inclusion of Anthropogenic Heating Anthropogenic sources:  importance of heat and humidity releases, especially during wintertime  based on estimates for a typical US city:  ~60% due to traffic  ~40% due to residential/industrial activities  a few % due to metabolism (neglected)

14. Anthropogenic Heating: Production of a database for Canada & USA Current TEB:  uses constant forcing of fluxes due to traffic and industrial activities Methodology:  under development for more realistic representation of anthropogenic fluxes  based on “top-down” approach of Sailor and Lu (2004)  estimates of diurnal, weekly and seasonal cycles  prototype and validation for Montreal  generalize to major North American cities

15. Evaluation Of Anthropogenic Heating Top-down approach (D. J. Sailor, USA, 2004)  ρ pop (t)Population density [person/km2]  F V (t)Non-dimensional vehicle traffic profile  E V Vehicle energy used per kilometer [Wkm-1]  DVDDistance traveled per person [km]  Analysis at the city scale  Hourly non-dimensional profile functions per capita  Spatial refinement through the hourly density of population profile Daily total energy released by 1 vehicle

16. Anthropogenic Heating: Top-Down Approach, Vehicle Traffic Profile Hourly fractional traffic profiles – f v (t) for various US cities and states (Sailor and Lu, 2004).

17. Plan: Search for data sources Analysis of the data Definition of the anthropogenic profiles per sector Building of the anthropogenic heating database Anthropogenic Heating: Top down approach Production of a database for Canada & USA Validation of the approach with detailed high resolution data

18. Implementing 3D Turbulence Current 1D (vertical) turbulent diffusion scheme parametrizes effects of large eddies in PBL High-resolution models (< 1km) partly resolve large eddies Adjustments needed to avoid “double-counting” of diffusion processes Must also include XY contributions as grid resolution increases and move toward LES (quasi-isotropic 3D diffusion) Cascade to LES-type model resolution (Large-eddy simulation - i.e. 10-50m) with Smagorinsky-Lilly approach Smooth transition of diffusion intensity as function of model resolution

19. Included all XY components of the dynamic Reynolds stress tensor Added TKE gradient terms Horizontal corrections introduced in all remaining transport equations Finite difference discretization on Arakawa-C grid and Charney- Phillips vertical staggering Modified operator splitting technique used by TKE solver Modified appropriate scale- dependent mixing length Implementing 3D Turbulence

20. Vertical heat flux: published LES results Moeng et al., J. Atmos.,Sci., 1994 30 m resolution SB1 and SB2: strong shear + moderate convection SGS (sub-grid-scale parameterization) model mostly active: - lower levels (near surface) -top of PBL (entrainment zone)

21. Vertical heat flux: resolved and subgrid scales (OKC 16:00 CDT) 40 m200 m

22. TKE resolved and subgrid scales (OKC 16:00 CDT) 40 m200 m

23. 1D vs. 3D TKE profiles (OKC 16:00 CDT) - “double-counting” problem - 40 m200 m

24. Current studies : Offline modeling over OKC (Joint Urban 2003) to evaluate TEB over North American cities 3D modeling over OKC (Joint Urban 2003) to study the impact of the urban parameterization on the boundary layer Future works : Offline modeling over Montreal (MUSE period) to evaluate TEB under winter condition and to improve the snow parameterization Modeling objectives

25. The Joint Urban 2003 Experiment Atmospheric dispersion study 28 June to 31 July 2003 Include the following meteorological measurements: 22 surface met stations 6 surface energy budget stations 2 CTI windtracer lidars 2 radiosonde systems 4 wind profiler/RASS systems 1 FM-CW radar 3 ceilometers 9 sodars + Oklahoma mesonet + NEXRAD radars of the US weather service In collaboration with our CRTI partners (U. of Waterloo, Defence R&D Canada)

26. ModelRes.GridVersionStart timeDur.Step GEM reg operational 15 kmGEM320 PHY42 20030716 0000 UTC 48 hrs450 s GEM/LAM operational 2.5 km201x201GEM322 PHY44 20030716 0600 UTC 42 hrs60 s GEM/LAM1 km201x201GEM322 PHY44 20030716 1200 UTC 36 hrs30 s GEM/LAM (planned) 250 m201x201GEM322 PHY44 20030716 1200 UTC 30 hrs6 s GEM/LAM 2.5 km GEM/LAM 1 km GEM/LAM 250 m Preliminary results based on Joint Urban 2003 IOP 3 (16 July 2003) - Clear sky / southerly winds Cascade of grid nesting down to 1-km resolution Modeling configuration

27. Evaluation on Joint Urban 2003 Observations Simul CROPS Simul URBAN Sensitivity tests conducted with 2 model simulations at 1-km: CROPS = no TEB (city is replaced by crops resolved by ISBA) URBAN = with TEB + urban land-cover classification (12 urban classes) Rural sites (7 MESONET stations around OKC): good agreement on day 1 between observations and model runs model slightly too warm during nighttime and day 2 minor impact of TEB in rural areas (as expected) Suburbs (PNNL stations) and urban sites (13 PWIDS stations in CBD): marked positive impact of TEB during nighttime significant overestimate during daytime with TEB (examination is underway) Observations Simul CROPS Simul URBAN

28. Evaluation on Joint Urban 2003 At 1200 LST well-mixed BL (with θ ~ 34°C) to about 1300 m at upwind site (PNNL south of OKC), with strong inversion. A few km downwind (ANL site), UBL is colder (by about 1°C) and reaches height of 1200 m. The 1-km model run indicates a relatively good agreement, except at upper levels: too much mixing in the entrainment zone! BL warms up in afternoon (~ 36°C). While the upwind BL stays relatively steady, the UBL top rises to 1650 m at the ANL site, likely as a result of the urban heat island plume. The 1-km model run does not capture well this evolution of the BL structure. Work underway to improve simulations with: Higher horizontal (250 m) and vertical resolutions (especially in entrainment zone); More appropriate vertical diffusion scheme (3D LES-type) 1500 LST 1200 LST Evolution of the Urban Boundary Layer

29. Objectives of MUSE-1 Document the evolution of surface characteristics and energy budgets in a dense urban area during the winter-spring transition –Evolution of snow cover from ~100% to 0% in an urban environment –Impact of snow on the surface energy and water budgets –Quantify anthropogenic fluxes in late winter and spring conditions Evaluate TEB in reproducing the surface characteristics and budgets in these conditions (aspect not well examined so far) Gain expertise in urban measurements Prepare for a wider effort to be submitted to CFCAS Preliminary results of the 2005 Montreal Urban Snow Experiment (MUSE-2005)

30. Incoming and outgoing radiation CNR1 radiometer Kipp & Zonen Radiative surface temperatures IR camera in heated case Turbulent fluxes by eddy covariance 10Hz 3D sonic anemometer CSAT3 H 2 O/CO 2 analyzer Li-Cor 7500 Fine wire thermocouple ASPTC Air temperature and humidity in canyons Radiative temperature of walls Continuous measurements 17 March to 14 April 2005 20 m tower

31. March 17 th March 22 nd March 30 th April 5 th Evolution of snow cover 100 % 95 % 50 %10 % Clear skies and southwest winds Four 26-hour IOPs (March 17-18, 22-23, 30-31, April 5-6) Measurements: –Hourly radiative surface temperatures using IR thermometer –Albedo (5 daytime measurements) –Snow depth and density (5 daytime measurements) –Pictures to document snow cover, snow melt, wet fraction Intensive observation periods

32. Energy balance summary Daily average in W/m² Residual term = Radiative balance – (sensible heat + latent heat) 1 st sequence With snow 2 nd sequence Without snow

33. Project management: Michel Jean, Operations Branch, CMC, Dorval Jocelyn Mailhot, MRB, Dorval Mario Benjamin, Quebec Region - MSC Field work (installation and observations): Bruno Harvey, Frédéric Chagnon, Stavros Antonopoulos, Najat Benbouta, Mario Benjamin, Olivier Gagnon, Aude Lemonsu, Gilles Morneau, Radenko Pavlovic Modelling team: Stéphane Bélair, Aude Lemonsu, Claude Pelletier External contributions from: Prof Sue Grimmond, Indiana University Prof Tim R. Oke, University of British Columbia Prof James A. Voogt, University of Western Ontario Sarah M. Roberts This project was funded by CBRN Research and Technology Initiative as project # 02-0093RD The MUSE-2005 team

34. MUSE-2: follow-up 10 February until end March 2006 Wintertime conditions Similar location (Rosemont/Petite-Patrie) and instrumentation Longer-term wider effort in Canada: Development of a national observation network Urban sites for surface and upper-air profiles Monitoring of the urban boundary layer Partnership with various organizations across Canada Seek funding by CFCAS (Canadian Foundation for Climate and Atmospheric Sciences) Outlook

35. CFCAS Urban Proposal Network Grant Proposal to the Canadian Foundation for Climate and Atmospheric Sciences “FORECASTING WEATHER FOR CANADIAN CITIES” Co-Principal Investigators: J.A. Voogt (The University of Western Ontario) T.R. Oke (The University of British Columbia) Total requested Budget: $1,447,000 February 10th, 2006

36. CFCAS Urban Proposal NameInstitutionRoleExperience * Objectives J.A. VoogtUWOco PIObs, Mod, RS, TEB1, 5 T.R. OkeUBCco PIObs, Mod, TEB1,2 I. StrachanMcGillco applicantObs1,2 N. CoopsUBCco applicantRS, Mod5 J. WangUWOco applicantRS5 M. BenjaminMSC Quebec Regionco applicantObs1,2 J. MailhotRPN / MSCco applicantMod, TEB2, 3, 4 S. BélairRPN / MSCco applicantMod, TEB, RS2, 3, 4, 5 A. LemonsuRPN / MSCco applicantMod, TEB, RS2, 3, 4, 5 C.S.B. GrimmondKing’s College Londonco applicantObs, Mod, TEB,RS1, 2, 5 V. MassonMétéo Franceco applicantTEB, Mod, Obs2, 3 I. Zawadzki,McGillcollaboratorObs, RS3 A. ChristenBerlin Univ. of Tech.collaboratorObs1 G. BrunetRPN/MSCcollaboratorMod2, 3, 4 R. HogueCMC/MSCcollaboratorMod2, 3, 4 * Obs: field observation acquisition and analysis, Mod: numerical modeling, RS: remote sensing, TEB: TEB-ISBA use. Table 1. Proposal participants.

37. Forecasting Weather for Canadian Cities 5 Major Objectives 1.Field observations (Montreal + Vancouver: urban / suburban / rural sites) –Oke, Benjamin, Strachan, Grimmond, Voogt –Detailed urban heat and water balances (continuous 2-year measurements) 2.Canadian optimized version of TEB-ISBA –Bélair, Lemonsu, Mailhot, Oke –Specifics of Canadian cities: building materials, vegetation, snow and cold winter conditions 3.Modeling studies of the urban boundary layer –Mailhot, Bélair, Lemonsu, Masson, Zawadzki –Impact of TEB on UBL and clouds/precipitation/types; urban-induced circulations 4.Urban component of off-line modeling system –Bélair, Lemonsu 5.Urban remote sensing –Voogt, Coops, Wang, Bélair, Lemonsu Forecasting Weather for Canadian Cities 5 Major Objectives

38. Recently: 39 th Annual CMOS Congress: June 2005 in Vancouver (5 presentations) Royal Met Society 2005 Conference: September 2006 in Exeter UK (1 presentation) 6 th Symposium on Urban Environment / AMS Annual Meeting: Jan. 2006 in Atlanta, GA (5 presentations) Upcoming: 17 th Symposium on Boundary Layers and Turbulence: May 2006 in San Diego, CA (1 presentation) 6 th International Conference on Urban Climate: June 2006 in Göteborg, Sweden (4 presentations) Presentations at conferences

39. Funding through… CRTI Project # 02-0093RD Advanced Emergency Response System for CBRN Hazard Prediction and Assessment for the Urban Environment