MESOSCALE MODELING FOR AIR QUALITY FORECASTING by ROBERT D. BORNSTEIN DEPT. OF METEOROLOGY SAN JOSE STATE UNIVERSITY SAN JOSE, CA USA

Slides:



Advertisements
Similar presentations
Chapter 13 Weather Forecasting.
Advertisements

The University of Reading Helen Dacre AMS 2010 Air Quality Forecasting using a Numerical Weather Prediction Model ETEX Surface Measurement Sites.
Urban Modelling 1 03/2003 © Crown copyright Urban Scale NWP with the Met Office's Unified Model Peter Clark Mesoscale Modelling Group Met Office Joint.
LARGE EDDY SIMULATION Chin-Hoh Moeng NCAR.
Section 2: The Planetary Boundary Layer
A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.
ANALYSIS OF TRACER DATA FROM URBAN DISPERSION EXPERIMENTS Akula Venkatram and Vlad Isakov  Motivation for Field Experiments  Field Studies Conducted.
Jared H. Bowden Saravanan Arunachalam
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.
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 +,
Meteorology Dr. Eugene Cordero Department of Meteorology San Jose State University, Fall 2003.
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 +,
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
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.
Towards Assimilating Clear-Air Radar Observations with an WRF-Based EnKF Yonghui Weng, Fuqing Zhang, Larry Carey Zhiyong Meng and Veronica McNeal Texas.
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.
CAMx simulations of Middle-East ozone concentration-trends by use of RAMS and MM5 input Shoukri J. Kasakseh Shoukri J. Kasakseh †º,
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.
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.
Weather Model Background ● The WRF (Weather Research and Forecasting) model had been developed by various research and governmental agencies became the.
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.
“NYC Climate Projections & New Atmospheric Observational Capacity” Stuart R. Gaffin, Cynthia Rosenzweig Center for Climate Systems Research Columbia University.
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.
Understanding the Weather Leading to Poor Winter Air Quality Erik Crosman 1, John Horel 1, Chris Foster 1, Lance Avey 2 1 University of Utah Department.
Session 1, Unit 1 Course Overview. Introduction Course – ENV 7335 Air Quality Modeling Instructor – Yousheng Zeng, Ph.D., P.E. Prerequisite – ENV 7331.
Model Simulations of Extreme Orographic Precipitation in the Sierra Nevada Phillip Marzette ATMS 790 March 12, 2007.
Chris Birchfield Atmospheric Sciences, Spanish minor.
Yamada Science & Art Corporation PROPRIETARY A Numerical Simulation of Building and Topographic Influence on Air Flows Ted Yamada ( YSA.
METR202- Study Urban Climate System Using Satellite Remote Sensing and Climate Model Professor Menglin Jin San Jose State University Outline: Key Urban.
Prediction of Atlantic Tropical Cyclones with the Advanced Hurricane WRF (AHW) Model Jimy Dudhia Wei Wang James Done Chris Davis MMM Division, NCAR Jimy.
Verification and Case Studies for Urban Effects in HIRLAM Numerical Weather Forecasting A. Baklanov, A. Mahura, C. Petersen, N.W. Nielsen, B. Amstrup Danish.
Research and Development to Meet Urban Weather and Climate Needs Dr. Richard D. Rosen NOAA Research September 23, 2004 Presentation at “Challenges in Urban.
Presentation Slides for Chapter 1 of Fundamentals of Atmospheric Modeling 2 nd Edition Mark Z. Jacobson Department of Civil & Environmental Engineering.
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.
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.
Large Eddy Simulation of PBL turbulence and clouds Chin-Hoh Moeng National Center for Atmospheric Research.
Dispersion conditions in complex terrain - a case study of the January 2010 air pollution episode in Norway Viel Ødegaard Norwegian Meteorological.
Sources of Surface Wind Fields for Climate Studies From Surface Measurements –Ships –Buoys From Models –GCM (with K-theory PBLs) –UW Similarity Model.
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,
R. A. Brown 2003 U. Concepci Ó n. High Winds Study - Motivation UW PBL Model says U 10 > 35 m/s Composite Storms show high winds Buoy limits:
CITES 2005, Novosibirsk Modeling and Simulation of Global Structure of Urban Boundary Layer Kurbatskiy A. F. Institute of Theoretical and Applied Mechanics.
Session 5, CMAS 2004 INTRODUCTION: Fine scale modeling for Exposure and risk assessments.
Office of Research and Development Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory Simple urban parameterization for.
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,
Numerical Investigation of Air- Sea Interactions During Winter Extratropical Storms Presented by Jill Nelson M.S. Marine Science Candidate Graduate Research.
Initial Results from the Diurnal Land/Atmosphere Coupling Experiment (DICE) Weizhong Zheng, Michael Ek, Ruiyu Sun, Jongil Han, Jiarui Dong and Helin Wei.
Challenges in PBL and Innovative Sensing Techniques Walter Bach Army Research Office
Impacts of Meteorological Conditions Modified by Urban Expansion on Surface Ozone over Yangtz River Delta and Pearl River Delta region, China Xuemei Wang,
AMS Conference January 2010 Atlanta, GA NCAR/RAL - National Security Applications Program Evaluation of Large Eddy Numerical Simulations (LES) with.
Summary of the Report, “Federal Research and Development Needs and Priorities for Atmospheric Transport and Diffusion Modeling” 22 September 2004 Walter.
Numerical Weather Forecast Model (governing equations)
Meso-scale Model's Results
Characterizing urban boundary layer dynamics using
Grid Point Models Surface Data.
The Turbulent Structure of the Urban Boundary Layer
In the past thirty five years NOAA, with help from NASA, has established a remote sensing capability on polar and geostationary platforms that has proven.
Distribution A: Approved for Public Release, Distribution Unlimited
Models of atmospheric chemistry
COMPUTATIONAL MODELING OF PARTICLE TRANSPORT IN TURBULENT AIRFLOW
MODELING AT NEIGHBORHOOD SCALE Sylvain Dupont and Jason Ching
Genesis and Morphology of the Alberta Dryline
Presentation transcript:

MESOSCALE MODELING FOR AIR QUALITY FORECASTING by ROBERT D. BORNSTEIN DEPT. OF METEOROLOGY SAN JOSE STATE UNIVERSITY SAN JOSE, CA USA Prepared for FORUM ON: CHALLENGES IN URBAN METEOROLOGY ROCKVILLE, MD SEPT 2004

ACKNOWLEDGEMENTS CO WORKERS H. Taha, ALTOSTRATUS, SJSU R. Balmori, SJSU J. Ching and S. Dupont, EPS/RTP S. Burian, Univ of Utah S. Stetson, SWS, Inc. D. Byan, Univ of Houston J. Allwine, DHS M. Reynolds, BNL FUNDING AGENCIES DHS, USAID, State of Texas, LBNL, NSF

OUTLINE ISSUES IN ISSUES IN –URBAN CLIMATE –URBAN WEATHER –URBAN AIR QUALITY –GLOBAL CLIMATE-CHANGE IMPACTS REQUIRED RESEARCH REQUIRED RESEARCH –FIELD STUDIES –THEORETICAL DEVELOPMENT –MODEL DEVELOPMENT

Scales in an Urban Environment

OBSERVATIONAL NEEDS: URBAN CLIMATE URBAN PBL URBAN PBL –ROUGHNESS DECELERATION VS UHI ACCELERATION –UHI CONFLUENCE VS BARRIER DIFLUENCE –RA FLUX DIV FROM AEROSOLS ROUGHNESS SUB-LAYER ROUGHNESS SUB-LAYER –U * AS f (z) –PROFILERS FROM: SODARS, LIDARS, RADARS, RASS URBAN CANYON LAYER URBAN CANYON LAYER –LINKAGE B/T ROOFTOP AND CANYON FLOWS –STACKED ASYMMETRIC VORTICIES –WALL INDUCED VERTICAL VELOCITIES URBAN SURFACE RS/GIS DATA BASES FOR URBAN SURFACE RS/GIS DATA BASES FOR –LU/LC –SOIL MOSITURE: UHI VS UCI –ALBEDO, ROUGHNESS, EMISSIVITY –3-D UHI ON ALL SFCS

Incorporate Stetson’s high- resolution Houston z o data

URBAN MESO-MODELING URBANIZED MESO-MET MODELS URBANIZED MESO-MET MODELS –AEROSOLS AND RFD –PBL EQUATIONS WITH DRAG TERMS –SFC ENERGY AND MOISTURE BALANCES –MM5  WRF ROUGHNESS SUBLAYER MODELS ROUGHNESS SUBLAYER MODELS –REPLACE MONIN-OBUKHOV THEORY –LOWER B.C. FLUXES FROM CANYON MODELS SST (x, y, t) from ocean models SST (x, y, t) from ocean models

 From Masson (2000)

1 km uMM5 end of daytime ΔUHI: 8 PM 21 Aug Upper L: MM5 Upper L: MM5 Upper R: uMM5 Upper R: uMM5 Lower L: uMM5-MM5 Lower L: uMM5-MM5 uMM5  1.5 K warmer uMM5  1.5 K warmer Blob is LU/LC error Blob is LU/LC error

URBAN EFFECTS ON WEATHER SEA BREEZE FLOWS SEA BREEZE FLOWS –RETARDED MOVEMENT SYNOPTIC FRONTS SYNOPTIC FRONTS –RETARDED MOVEMENT THUNDERSTORMS THUNDERSTORMS –UHI INITIATION VS. BARRIER SPLITTING –PREVIOUS: METROMEX, NYC, AND ATLANTA –AEROSOL MODIFICATIONS –PROJECT HEAT STUDY OBS AND MESO-MODELS REQUIRED OBS AND MESO-MODELS REQUIRED

MM5 section of potential T and w through strongest UHI- induced updraft at 1700 UTC. Max w is 4.3 m/s.

URBAN-SCALE AIR QUALITY OZONE AIR QUALITY OZONE AIR QUALITY –EMISSIONS –URBAN EFFECTS ON DISPERSION –MEOS-SCALE NETWORKS PM2.5 PM2.5 –SUMMER PHOTOCHEMISTRY –WINTER COMBUSTION DURING ALL WEATHER CONDITIONS DURING ALL WEATHER CONDITIONS IN ALL CLIMATE TYPES IN ALL CLIMATE TYPES –OBS –MESO-MODELS

URBAN-CANYON MODELING CANYON SCALE NUMERICAL MODELS CANYON SCALE NUMERICAL MODELS –FOR ER APPLICATIONS –BOTH CFD AND REAL-TIME WIND TUNNEL MODELS PROVIDE WIND TUNNEL MODELS PROVIDE –COMPARISON DATA –PARAMETERIZATION GUIDANCE 2-WAY LINKED MESO & CANYON 2-WAY LINKED MESO & CANYON SCALE MODELS –FOR ER APPLICATIONS –NEED TRANSPORT AND DIFFUSION PROCESSES 2-WAY LINKED INDOOR & OUTDOOR MODELS 2-WAY LINKED INDOOR & OUTDOOR MODELS –ER APPLICATIONS –TRUE DOSAGE CALCULATIONS

This and next three are from A. HUBER, EPA/RTP

from EPA/RTP WIND TUNNEL

ER AIR-QUALITY ER PLANNING FOR ER PLANNING FOR –ACCIDENTAL RELEASES –TERRORIST RELEASES ER PLANNING: NEEDS ER PLANNING: NEEDS –TRACER STUDIES (URBAN 2000, JOINT URBAN, DHS/UDS/ NYC) –SECURE DATA-COMMUNICATIONS –MULTISCALE MODELS (SYNOPTIC, MESO, CANYON, INDOOR) –UNDERSTANDABLE DATA DISPLAY FOR RESPONERS DURING ALL WEATHER CONDITIONS IN ALL CLIMATES DURING ALL WEATHER CONDITIONS IN ALL CLIMATES

QUIC Simulation with dd = 215 deg (from M. Brown, LANL) wind vectors at 5 m height

from LBNL

URBAN IMPACTS FROM GLOBAL CLIMATE CHANGE URBAN POLLUTANT EMISSIONS URBAN POLLUTANT EMISSIONS –SOURCES FOR GLOBAL CONTAMINATION –CLIMATE CHANGE INDUCED TRENDS INCREASED URBAN THERMAL-STRESS MORTALITY INCREASED URBAN THERMAL-STRESS MORTALITY (COLUMBIA/GISS, U of H, & PSU PROJECTS) CHANGES IN CHANGES IN –WINTER AND SUMMER STORM TRACKS –URBAN PRECIP –URBAN FLOODING LITTLE COMMUNICATION B/T RESEARCH GROUPS LITTLE COMMUNICATION B/T RESEARCH GROUPS –GLOBAL CHANGE –URBAN CLIMATE

NYC OBS REFERENCES Bornstein 1968: J. Appl. Met.., 7., Bornstein 1968: J. Appl. Met.., 7., Born. & Johnson 1977: At. Env., 11, Born. & Johnson 1977: At. Env., 11, Loose & Born. 1977: MWR, 105, Loose & Born. 1977: MWR, 105, Born. & Thompson, 1981: JAM, 20, Born. & Thompson, 1981: JAM, 20, Gaffen & Born. 1988: Met. and Atmos. Phys, 38, 185 ‑ 94 Gaffen & Born. 1988: Met. and Atmos. Phys, 38, 185 ‑ 94 Born.1987: Modeling the Urban BL, AMS, 53 ‑ 93. Born.1987: Modeling the Urban BL, AMS, 53 ‑ 93.