Simulations for a Houston ozone episode & the NYC DHS MSG tracer study with an urbanized MM5 R. Bornstein*, R. Balmori E. Weinroth, H. Taha San Jose State.

Slides:



Advertisements
Similar presentations
Fong (Fantine) Ngan and DaeWon Byun IMAQS, Department of Earth Sciences, University of Houston 7 th Annual CMAS Conference, October 6th, 2008.
Advertisements

University of Houston IMAQS MM5 Meteorological Modeling for Houston-Galveston Area Air Quality Simulations Daewon W. Byun Bonnie Cheng University of Houston.
June 2003Yun (Helen) He1 Coupling MM5 with ISOLSM: Development, Testing, and Application W.J. Riley, H.S. Cooley, Y. He*, M.S. Torn Lawrence Berkeley National.
Observation & simulation of urban-effects on climate, weather, and air quality Bob Bornstein Dept. of Meteorology, SJSU Haider Tahabbb, Altostratus, Inc.
WRF Physics Options Jimy Dudhia. diff_opt=1 2 nd order diffusion on model levels Constant coefficients (khdif and kvdif) km_opt ignored.
Jared H. Bowden Saravanan Arunachalam
Bay breeze enhanced air pollution event in Houston, Texas during the DISCOVER-AQ field campaign Christopher P. Loughner (University of Maryland) Melanie.
Development of Alternative Methods For Estimating Dry Deposition Velocity In CMAQ.
MM5 SIMMULATIONS OF SFBA TO SAC/SJV TRANSPORT DURING 30 JULY- 2 AUG 2000 CCOS OZONE EPISODE by Robert D. Bornstein: SJSU Tesfamichael.
Air-Sea Interaction in NYC: Urbanized Mesoscale Modeling for CB Threats Air-Sea Interaction in NYC: Urbanized Mesoscale Modeling for CB Threats with Alan.
Recent performance statistics for AMPS real-time forecasts Kevin W. Manning – National Center for Atmospheric Research NCAR Earth System Laboratory Mesoscale.
Middle-East Air-Pollutant Climatology by J. SAFI 0, M. Abu-Kubieh 0, K. Rishmawi #, S. Kasakseh* # M. Luria +, E. Weinroth + *, E. Tas +, V. Matziev +,
MM5 SIMMULATIONS OF SFBA TO SAC/SJV TRANSPORT DURING 30 JULY- 2 AUG 2000 CCOS OZONE EPISODE by Tesfamichael B. Ghidey: LBNL, SJSU, DRI.
Middle-East Air-Pollutant Climatology by J. SAFI 0, M. Abu-Kubieh 0, K. Rishmawi #, S. Kasakseh* # M. Luria +, E. Weinroth + *, E. Tas +, V. Matziev +,
1 The lifecycle of what kind of thunderstorm is this? Choose from: (single-cell, multi-cell, or super-cell)
How to Improve Mesoscale Atmospheric-Modeling Results Bob Bornstein San Jose State University San Jose, CA Presented at UNAM Mx City.
Simulations of ozone over Israel, West Bank, and Jordan E. Weinroth, M. Luria, A. Ben-Nun, C. Emery, J. Kaplan, M. Peleg and Y. Mahrer Seagram Center for.
Urbanized-MM5 urban-climate simulations of Houston-Galveston Bob Bornstein* R. Balmori and H. Taha Dept. of Meteor., San Jose State Univ. San Jose, CA.
1 Tim Oke and the extension-upwards of UHI-observations into the PBL Prof. Robert Bornstein Dept. of Meteorology, San Jose State University San Jose, CA,
Use of urbanized meso-met models for air quality applications for Houston R. Bornstein, H. Taha, R. Balmori San Jose State University San Jose, CA
MM5, RAMS, & CAMx Simulations of Summer- time Middle-East O 3 (Funding: USAID-MERC Program) Shoukri Kasakseh †o, Robert Bornstein.
Urbanized MM5 simulations for a Houston ozone episode and for the NYC DHS MSG tracer study R. Bornstein*, R. Balmori E. Weinroth, H. Taha San Jose State.
Global-warming reverse-impact: observed summer-daytime coastal-cooling in coastal California air-basins R. Bornstein, San Jose State University
Urbanized MM5 simulations of Houston: land-use, UHIs, and August 2000 ozone transport patterns Presented at 86 th AMS Annual Meeting, Atlanta, GA 30 January.
Coastal front formation at the Llobregat delta. Preliminary study David Pino 1,2 & Jordi Mazón 1 1 Applied Physics Department (UPC) 2 Institut d’Estudis.
CAMx simulations of Middle-East ozone concentration-trends by use of RAMS and MM5 input Shoukri J. Kasakseh Shoukri J. Kasakseh †º,
MM5 SIMMULATIONS OF MESOSCALE TRANSPORT FROM THE SFBA TO SACRAMENTO & SJV DURING A CCOS 30 JULY-02 AUG OZONE EPISODE By Tesfamichael B. Ghidey, LBNL,
Impacts from urban & rural surface modifications on meteorology and air quality in Houston: preliminary results Haider Taha Altostratus.
CORRECTABLE BC-ERRORS WITHIN MESO-MET MODELS R. Bornstein San Jose State University San Jose, CA Presented at 86th AMS Annual Meeting,
Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land.
RAMS, MM5, & CAMx SIMULATIONS OF MIDDLE-EAST O 3 TRANSBOUNDARY TRANSPORT Erez Weinroth 1,2, Shoukri Kasakseh 1,3 Robert Bornstein 1
1 Urban Climate Studies: applications for weather, air quality, and climate change Prof. Robert Bornstein Dept. of Meteorology San Jose State University.
NYC SEA BREEZE EVENT William T. Thompson, Teddy Holt, and Julie Pullen Naval Research Laboratory Monterey, CA.
NYC METEOROLOGY: MODELS by BOB BORNSTEIN Dept of Meteorology, SJSU for DHS/UDS Meeting EML, NYC June 2004.
NYU/NYC STUDY 10 IOPs – FIVE DAYS EACH (DAY AND NIGHT) – ALL SEASONS 80 SFC WIND SITES  HOURLY FLOW CHARTS PIBALS: – 1- 4 THEODOLITES FOLLOWING 1OR 2.
Urbanized MM5 meso-met modeling for the Houston Texas ozone SIP Prof. Bob Bornstein Dept. of Meteorology San Jose State University San Jose, CA USA
NYC METEOROLOGY AND UDP MESOSCALE MODELING *Robert Bornstein: SJSU with input from Haider Taha & Erez Weinroth: SJSU Teddy Holt, Julie Pullen, Wm. Thompson:
Simulations of met conditions during a Houston ozone episode and the NYC NYC DHS MSG tracer study with urbanized MM5 (uMM5) R. Bornstein*, R. Balmori E.
Anthropogenic effects on urban and coastal climates R. Bornstein and co-workers San Jose State University Presented at Stanford University.
LAKE EFFECT SNOW SIMULATION John D McMillen. LAKE BONNEVILLE EFFECT SNOW.
The National Environmental Agency of Georgia L. Megrelidze, N. Kutaladze, Kh. Kokosadze NWP Local Area Models’ Failure in Simulation of Eastern Invasion.
Tracer Simulation and Analysis of Transport Conditions Leading to Tracer Impacts at Big Bend Bret A. Schichtel ( NPS/CIRA.
MESOSCALE MODELING FOR AIR QUALITY FORECASTING by ROBERT D. BORNSTEIN DEPT. OF METEOROLOGY SAN JOSE STATE UNIVERSITY SAN JOSE, CA USA
28 Jan 1815 UTC2135 UTC Clear patches due to canyon drainage/ Exchange from Utah Valley? PCAPS IOP January 2011.
Performance evaluation of isoprene in ozone modeling of Houston Mark Estes, Clint Harper, Jim Smith, Weining Zhao, and Dick Karp Texas Commission on Environmental.
EVALUATION AND IMPROVEMENT OF GAS/PARTICLE MASS TRANSFER TREATMENTS FOR 3-D AEROSOL SIMULATION AND FORECAST Xiaoming Hu and Yang Zhang North Carolina State.
UMM5 simulations of urban-reforestation effects on Houston UHIs for ozone-SIP emission-reduction credits R. Bornstein, H. Taha, R. Balmori San Jose State.
1/26 APPLICATION OF THE URBAN VERSION OF MM5 FOR HOUSTON University Corporation for Atmospheric Research Sylvain Dupont Collaborators: Steve Burian, Jason.
Seasonal Modeling (NOAA) Jian-Wen Bao Sara Michelson Jim Wilczak Curtis Fleming Emily Piencziak.
Erik Crosman 1, John Horel 1, Chris Foster 1, Erik Neemann 1 1 University of Utah Department of Atmospheric Sciences Toward Improved NWP Simulations of.
How well can we model air pollution meteorology in the Houston area? Wayne Angevine CIRES / NOAA ESRL Mark Zagar Met. Office of Slovenia Jerome Brioude,
Development Mechanism of Heavy Rainfall over Gangneung Associated with Typhoon RUSA Tae-Young Lee, Nam-San Cho, Ji-Sun Kang Kun-Young Byun, Sang Hun Park.
1 High-resolution regional climate simulations of the long-term decrease in September rainfall over Indochina Hiroshi G. Takahashi FRCGC/JAMSTEC.
THE SECONDARY LOW AND HEAVY RAINFALL ASSOCIATED WITH TYPHOON MINDULLE (2004) Speaker : Deng-Shun Chen Advisor : Prof. Ming-Jen Yang Lee, C.-S., Y.-C. Liu.
Are Numerical Weather Prediction Models Getting Better? Cliff Mass, David Ovens, and Jeff Baars University of Washington.
Session 5, CMAS 2004 INTRODUCTION: Fine scale modeling for Exposure and risk assessments.
1 Impact on Ozone Prediction at a Fine Grid Resolution: An Examination of Nudging Analysis and PBL Schemes in Meteorological Model Yunhee Kim, Joshua S.
Office of Research and Development Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory Simple urban parameterization for.
Positive Potential Vorticity Anomalies Generated from Monsoon Convection Stephen M. Saleeby and William R. Cotton Department of Atmospheric Science, Colorado.
Application of the urbanized MM5 to the Houston-Galveston region by R. Bornstein*, H. Taha, R. Balmori, SJSU S. Dupont, J. Ching, RTP/EPA/NOAA A. Martilli,
1 RAQMS-CMAQ Atmospheric Chemistry Model Data for the TexAQS-II Period : Focus on BCs impacts on air quality simulations Daewon Byun 1, Daegyun Lee 1,
Module 6 MM5: Overview William J. Gutowski, Jr. Iowa State University.
Off-line Air Quality Modeling Paradigms:
Characterizing urban boundary layer dynamics using
Distribution A: Approved for Public Release, Distribution Unlimited
Chris Misenis*, Xiaoming Hu, and Yang Zhang
MODELING AT NEIGHBORHOOD SCALE Sylvain Dupont and Jason Ching
Coastal Atmospheric Modeling for both Operational and Research Applications using the Weather Research Forecast (WRF) Model.
A Multiscale Numerical Study of Hurricane Andrew (1992)
WRAP 2014 Regional Modeling
Presentation transcript:

Simulations for a Houston ozone episode & the NYC DHS MSG tracer study with an urbanized MM5 R. Bornstein*, R. Balmori E. Weinroth, H. Taha San Jose State University San Jose, CA Presented at AMS Urban-Coastal Conference Sept 2007

Acknowledgements Data Data S. Burian, J. Ching S. Burian, J. Ching TCEQ, USFS TCEQ, USFS D. Byun D. Byun Urbanization scheme of Urbanization scheme of A. Martilli A. Martilli S. Dupont S. Dupont Funds: Funds: Past: NSF, USAID, DHS Past: NSF, USAID, DHS Pending: DTRA Pending: DTRA

OUTLINE Introduction Introduction Current uMM5 Applications Current uMM5 Applications Houston ozone Houston ozone NYC tracer study NYC tracer study Future: uWRF Future: uWRF Conclusion Conclusion

Recent Meso-met Model Urbanization Need to urbanize momentum, thermo, & TKE Need to urbanize momentum, thermo, & TKE surface & SfcBL diagnostic-Eqs. surface & SfcBL diagnostic-Eqs. PBL prognostic-Eqs. PBL prognostic-Eqs. Start: canopy model (Yamada 1982) Start: veg-canopy model (Yamada 1982) Veg-param replaced with GIS/RS urban-param/data Veg-param replaced with GIS/RS urban-param/data Brown and Williams (1998) Brown and Williams (1998) Masson (2000) Masson (2000) Martilli et al. (2001) in TVM/URBMET Martilli et al. (2001) in TVM/URBMET Dupont, Ching, et al. (2003) in EPA/MM5 Dupont, Ching, et al. (2003) in EPA/MM5 Taha et al. (2005), Balmori et al. (2006) in uMM5: Taha et al. (2005), Balmori et al. (2006) in uMM5: detailed input urban-parameters as f(x,y) for our two applications

uMM5 for Houston Goal: Accurate urban/rural temps & winds for Aug 2000 O 3 episode via uMM5 uMM5 Houston LU/LC & urban morphology parameters from S. Burian Houston LU/LC & urban morphology parameters from S. Burian TexAQS2000 field-study data TexAQS2000 field-study data USFS urban-reforestation scenarios  USFS urban-reforestation scenarios  UHI & O 3 changes

uMM5 Simulation period: August 2000 Model configuration Model configuration 5 domains: 108, 36, 12, 4, 1 km 5 domains: 108, 36, 12, 4, 1 km (x, y) grid points: (x, y) grid points: (43x53, 55x55, 100x100, 136x151, 133x141 full-  levels: 29 in D 1-4 & 49 in D-5; lowest ½  level=7 m full-  levels: 29 in D 1-4 & 49 in D-5; lowest ½  level=7 m 2-way feedback in D way feedback in D 1-4 Parameterizations/physics options Parameterizations/physics options > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Gayno-Seaman PBL (D-5) > Simple ice moisture, > Gayno-Seaman PBL (D-5) > Simple ice moisture, > urbanization module NOAH LSM > RRTM radiative cooling > urbanization module NOAH LSM > RRTM radiative cooling Inputs Inputs > NNRP Reanalysis fields, ADP obs data > NNRP Reanalysis fields, ADP obs data > Burian morphology from LIDAR building-data in D-5 > Burian morphology from LIDAR building-data in D-5 > LU/LC modifications (from Byun)

 GC influences: small  Air-mass movement: First along-shore (to west) from: flow along N-edge of cold-core atm-low  Then: Ship-Channel to Houston by Bay Breeze & UHI-convergence  max O 3  Finally: to NW of Houston by Gulf Breeze meso O 3 transport-patterns: D-5: UTC episode-day obs of meso O 3 transport-patterns: influences of sea breeze & UHI-convergence

Episode-day Synoptics: 8/25, 12 UTC (08 DST) H H 700 hPa Surface 700 hPa & sfc GC H’s: at weakest (no gradient) over Texas  meso-scale forcing (sea breeze & UHI convergence) dominates

MM5: episode day, 3 PM ( all graphs: flag = 5 m/s) > D–1: reproduces weak GC p-grad & flow > D-2: weak coastal-L > D-3: well-formed L  along-shore V L D-1 D-2 D-3

Domain 4 (3 PM) : cyclone off-Houston only on O 3 -day (25 th ) L L  Episode day day

Urbanized Domain 5: near-sfc 3-PM V, 4-days  Episode day day Cold-L Hot Cool

Along-shore flow, 8/25 (episode day): obs at 1500 UTC vs uMM5 (D-5) at 2000 UTC Tx2000 obs HGA obs D-5 (red box) uMM5 captured HGA obs of along-shore flow (from SST- BC cold-low) HGA Kriege uMM5 C

1 km uMM5 Houston UHI: 8 PM, 21 Aug Upper L: MM5 UHI (2.0 K) Upper L: MM5 UHI (2.0 K) Upper R: uMM5 UHI (3.5 K) Upper R: uMM5 UHI (3.5 K) Lower L: (uMM5-MM5) UHI Lower L: (uMM5-MM5) UHI LU/LCerror

8/23 Daytime 2-m UHI: obs vs uMM5 (D-5) H OBS: 1 PM uMM5: 3 PM Cold UHI

UHI-Induced Convergence: obs vs. uMM5 OBSERVEDuMM5 C C C C

Base-case (current) veg-cover (0.1’s)  urban min (red)  rural max (green) Modeled changes of veg-cover (0.01’s) > Urban-reforestation (green) > Rural-deforestation (purple) min max increase

Run 12 (urban reforestation) minus Run 10 (base case): 2-m ∆T at 4 PM reforested central urban-area cools & surrounding deforested rural-areas warm

D UHI(t) for Base-case minus Runs D UHI(t) for Base-case minus Runs U1 sea Ru U2 UHI = Average-T in urban-box minus that in rural-box UHI = Average-T in urban-box minus that in rural-box Runs 15-18: different urban re-forestation scenarios Runs 15-18: different urban re-forestation scenarios D UHI=Run-17 UHI minus Run-13 UHI (max effect) D UHI=Run-17 UHI minus Run-13 UHI (max effect) Reduced UHI  lower max-O 3 (not shown)  Reduced UHI  lower max-O 3 (not shown)  EPA emission-reduction credits  $ saved  Max-impact of –0.9 K of a 3.5 K Noon-UHI, of which 1.5 K was from uMM5

uMM5 for NYC DHS MSG UDS Goal: Accurate urban/rural temps & winds for for 9-15 March ‘05 tracer releases via uMM5 uMM5 NYC LU/LC & urban morphology NYC LU/LC & urban morphology parameters from S. Burian DHS MSG UDS field-study data DHS MSG UDS field-study data met met tracer tracer

 GC influences during tracer periods  Midtown: weak, slow synoptic speed  MSG: strong, fast synoptic speeds  Sea breeze & UHI influences  Midtown: strong, with UHI-convergence  MSG: weak  Urban-barrier influences  Midtown: weak  MSG: strong, with urban barrier divergence  Modeling studies by  Midtown: Pullen, Holt, Thompson at NRL  MSG: This presentation Obs of UDS Tracer Periods

NYC uMM5 DHS UDS MSG: 9-15 March ‘05 Model configuration Model configuration 4 domains: 36, 12, 4, 1 km 4 domains: 36, 12, 4, 1 km (x, y) grid points: (x, y) grid points: (110x85, 91x91, 91x91, 33x33) full-  levels: 29 in D 1-3 & 48 in D-4; lowest ½  level=7 m full-  levels: 29 in D 1-3 & 48 in D-4; lowest ½  level=7 m 2-way feedback in D way feedback in D 1-3 Parameterizations/physics options Parameterizations/physics options > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Grell cumulus (D 1-2)> ETA or MRF PBL (D 1-4) > Gayno-Seaman PBL (D-5) > Simple ice moisture, > Gayno-Seaman PBL (D-5) > Simple ice moisture, > urbanization module NOAH LSM > RRTM radiative cooling > urbanization module NOAH LSM > RRTM radiative cooling Inputs Inputs > NNRP Reanalysis fields, ADP obs data > NNRP Reanalysis fields, ADP obs data > Burian morphology from LIDAR building-data in D-5 > Burian morphology from LIDAR building-data in D-5 > LU/LC modifications (from Byun)

D04 D03 4 MM5 domains

1900 UTC, 3/11/05, MM5 Domain 3: Sfc-T(K) & synoptic wave-cyclone V ( flag = 5 m/s) W W C

Concurrent Domain-4 uMM5 Streamlines z = 60 m AGL & A-B is plane of following x-section A B Slowing & divergence Downwind convergence

Concurrent Domain-4 uMM5 Streamlines & Speed (purple lines, m/s) at 60 (left) & 700 (right) m AGL Note z-cells from urban-induced con- & divergence A 60 m 700 m B A B 1000 m

Concurrent Domain 4 uMM5 Speed (m/s, where flag = 5 m/s) at 60 (left) & 700 (right) m AGL Note large urban z  speed-min downwind of Manhattan & Brooklyn Note large urban z 0  speed-min downwind of Manhattan & Brooklyn (this is high-speed, non-UHI period) slow slow fast fast

Concurrent domain 4 uMM5 Div (1/s) & Wind (flag = 5 m/s) at 60 (left) & 700 (right) m AGL Note convergence (C) over Manhattan, as roughness slows wind Also compensating divergence (D) around convergence area C D C D D D

Concurrent Domain4- uMM5: w (m/s) & V (m/s) at 60 (left) and 700 (right) m AGL Note up-motion (+) over Manhattan conv-area (of previous fig) & compensating down-motion (-) in div-area around Manhattan

Pending: uWRF uWRF with NCAR (F. Chen) for DTRA uWRF with NCAR (F. Chen) for DTRA Martilli-Dupont urbanization Martilli-Dupont urbanization Burian lidar urban-parameters as f(x,y) Burian lidar urban-parameters as f(x,y) Taha stat-generalization of Burian urban- parameters for areas w/o lidar-obs Taha stat-generalization of Burian urban- parameters for areas w/o lidar-obs Freedman PBL-turbulence scheme Freedman PBL-turbulence scheme Zilitinkevich SfcBL stability-functions, z, etc. Zilitinkevich SfcBL stability-functions, z oh, etc. Steyn diagnostic h(x,y) scheme Steyn diagnostic h i (x,y) scheme SST (x,y,t) from J. Pullen SST (x,y,t) from J. Pullen

SJSU MM5 or uMM5 met output fields are available for ozone (design-day cases) and/or 4-D BCs for CFD &/or quick ER models for SFBA (MM5) SFBA (MM5) Houston (uMM5) Houston (uMM5) NYC (uMM5) NYC (uMM5) LA Basin (MM5) LA Basin (MM5) Israel (RAMS & MM5) Israel (RAMS & MM5)

Thanks Questions?