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11 th CMAS Meeting, RTP October 15 – 17, 2012 1 Fine Resolution Air Quality Forecasting Capability for limited-area domains – tested over Eastern Texas.

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Presentation on theme: "11 th CMAS Meeting, RTP October 15 – 17, 2012 1 Fine Resolution Air Quality Forecasting Capability for limited-area domains – tested over Eastern Texas."— Presentation transcript:

1 11 th CMAS Meeting, RTP October 15 – 17, 2012 1 Fine Resolution Air Quality Forecasting Capability for limited-area domains – tested over Eastern Texas Pius Lee, Hyuncheol Kim, Li Pan, Daniel Tong, and Tianfeng Chai Air Resources Laboratory, NOAA Shobha Kondragunta, Pubu Ciren, Qiang Zhao, Chuanyu Xu, and Xiaoyang Zhang National Environmental Satellite, Data, and Information Service Jianping Huang, Sarah Lu, and Jeff McQueen National Centers for Environmental Predictions, NOAA Ivanka Stajner Office of Science and Technology

2 2 NMMB grids: CONUS (green)*, nested Discover-AQ (red); in relation to 5x (blue) *1326*795=1.05 million horizontal grid cells @ 22 vertical layers 11 th CMAS Meeting, RTP October 15 – 17, 2012 Need for fine resolution Limited-area domain: affordability Study finer scale processes Talk (Tues): Ivanka Stajner -- NAQFCTalk (Wed): Tianfeng Chai – Chemical D.A.

3 3 11 th CMAS Meeting, RTP October 15 – 17, 2012  Next generation operational AQ modeling – consensus among many operational centers (e.g. Lee and Ngan 2011)  Better describes complex terrain & land/sea interface processes  Helps field campaign planning (e.g. NAQFC for DISCOVER-AQ 2010)  Imperative to capture certain pollution scenarios, e.g. wild fire induced hazards -- smoke (Hu et al. 2008 )  Fire weather forecasting a minimum of 24 hours lead time (e.g. NOAA 2012) Some applications of fine resolution AQ modeling 1.3 km fire weather on-demand nest Courtesy: mmb/emc/NCEP Poster: Christopher Loughner – DISCOVER-AQ Baltimore-Washington Poster: Yongtao Hu

4 4 11 th CMAS Meeting, RTP October 15 – 17, 2012  An on-demand event-based chemistry and air quality forecasting system  Limited-area domain within the Conterminous U.S.A (CONUS)  Parent domain: 12 km horizontal spacing resolution CONUS  Child domain: 4 km resolution limited-area domain  Emission generated at 4 km back- aggregated to 12 km domain  Tested for Eastern TX Configuration of 4km AQ limited-area forecasting domain within CONUS NMMB NMMB -Post & AqmPrdgen PREMAQ CMAQ GRiB products & graphics Verification ICON BCON from CONUS results SMOKE MOBILE6 Poster: Li Pan – Emission upgrades NAQFC 2012

5 5 11 th CMAS Meeting, RTP October 15 – 17, 2012  Versatility of selecting a limited- area domain of interest  Limited-area domain forecasts are heavily influenced by boundary conditions and their derivation is critical e.g. exo-domain wild fire emissions ~21x ~12x 5x Agricultural burning prevails in the months of March and April in Mexico HMS wildfire detections during Apr. 2010 Talk (Wed): Hyuncheol Kim – Fire Emission Poster: Yongtao Hu – Wildfire Impact Poster: Ka-wa Chan – Concept model

6 6 11 th CMAS Meeting, RTP October 15 – 17, 2012  Lowest: one to one lowest 5 layers  PBL: Next 6 CMAQ levels corresponds to 12 NAM levels up to about 1350 m AGL,  Free Troposphere: Next 7 CMAQ levels corresponds to 21 NAM levels to 5000 m AGL,  Tropopause: Next 4 CMAQ levels corresponds to 8 NAM levels embedding the transition @ 200 hPa  The remaining CMAQ full-interface level caps the model at 100 hPa. It corresponds to 3 NAM levels. Vertical coupling between NMMB and CMAQ: Layer correspondence 61 60 59 1 2 n NMMB Layer 200hPa 15 layers PD

7 7 11 th CMAS Meeting, RTP October 15 – 17, 2012 5x  Obtain CO concentration at lateral boundaries for 5x from predicted PM concentration e.g. PM/CO ratio: Forest: 0.13±0.05 Savanna: 0.08±0.03 Grass: 0.07±0.03 (Vicente et al. 2011;Janhäll et al. 2010)  Obtain NO x, VOC, NH 3, SO 2 Concentrations scaled from CO using EPA SPECIATE data 2010  HMS-Bluesky-SMOKE for wild fire emissions within 5x  5x provides IC and BC for HOU Limited-area 4km domain HYSPLIT CMAQ

8 8 11 th CMAS Meeting, RTP October 15 – 17, 2012 Modeled O3 difference between 12km and 4km domains at 13UTC August 26, 2012 At 4km resolution model simulates higher ozone concentrations aloft and resolves smaller features at all levels: interaction of emissions and meteorology at finer scales Surface 900 m

9 12-km (cut from 5X CONUS)4-km Houston domain Comparison of verification results – O3 Finer descriptions helped

10 12-km (cut from 5X CONUS)4-km Houston domain Comparison of verification results for pm Finer descriptions helped

11 Comparison of HOU domain-wide averaged surface concentrations Study other metrics?

12 Stats for Daily Maximum 8-hr O 3 at All AQS Sites within 4km Domain Metrics Paired (4km) Paired (12km) RMSE (ppb)15.6514.94 NME (%)25.3624.29 MB (ppb)1.862.43 NMB (%)3.925.13 R0.550.61 The performance measures over the 4 km resolution may not be necessarily better than over the coarser (12 km) resolution; it may be even worse if it is evaluated using the traditional evaluation metrics based on paired obs-mod data Courtesy: Daiwen Kang, CMAS 2011 12 Statistical metrics for high resolution AQ model evaluation -- Need New paradigm ! 11 th CMAS Meeting, RTP October 15 – 17, 2012

13 Preparing the Air Quality Community for GOES-R Advanced Baseline Imager (ABI) Aerosol Products GOES-R ABI Air Quality Proving Ground project successfully deployed a web-based dissemination of aerosol proxy data to air quality forecasters from different states in preparation for day one readiness of GOES-R products. GOES-R Aerosol Optical Depth (AOD), aerosol type, RGB image on the hour for every hour of the day are streamed via a website located on a STAR computer. ABI aerosol proxy retrievals are generated using ABI radiances generated by Community Multiscale Radiative Transfer Model (CRTM). The 24-hr aerosol forecast fields from 00Z run of WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model are provided as inputs to CRTM. 13 http://www.star.nesdis.noaa.gov/smcd/spb/aq/aqpg / Key instrument on GOES-R is the Advanced Baseline Imager (ABI): –16 bands with spatial resolution of 2 km (nadir) and 5 min refresh rate for CONUS –AOD with accuracy similar to MODIS (multi-channel aerosol retrieval) –Aerosol type information (smoke vs. dust) –Fire/hot spot characterization –Visible, IR, water vapor imagery Huff et al., The NOAA Air Quality Proving Ground: Preparing the Air Quality Community for Next Generation Products from The GOES-R Satellite, EM, accepted, 2012. Courtesy: S. Kondragunta

14 14 11 th CMAS Meeting, RTP October 15 – 17, 2012 Courtesy: S. Kondragunta and C. Xu, NESDIS STAR Flow Chart : Process for Generating Proxy ABI Aerosol Products 12km and 4 km results were input to CRTM – attempted for ABI imagery

15 15 11 th CMAS Meeting, RTP October 15 – 17, 2012 Examples of Near Real-Time ABI Proxy Aerosol Products for July 30, 2011, 14:00 UTC: AOD (left), Aerosol Type (center), RGB (right). Courtesy: S. Kondragunta and C. Xu, NESDIS STAR 12km and 4 km results were input to CRTM – attempted for ABI imagery

16 RGB at 15:00 2012-08-13RGB at 17:00 2012-08-13 RGB at 19:00 2012-08-13 RGB at 21:00 2012-08-13 11 th CMAS Meeting, RTP October 15 – 17, 2012 ABI Proxy Aerosol Products for 12 km results

17 AOD at 15:00 2012-08-13AOD at 17:00 2012-08-13 AOD at 19:00 2012-08-13 AOD at 21:00 2012-08-13 11 th CMAS Meeting, RTP October 15 – 17, 2012 ABI Proxy Aerosol Products for 12 km results -- cont’d

18 18 Summary 11 th CMAS Meeting, RTP October 15 – 17, 2012  4km AQ forecasting system for a limited-area domain has been tested: o Houston domain was tested for multiple days o The fine resolution window over HOU showed more local sfc O3 maxima and stronger concentration gradient o Inner-nest domain averaged time series showed mixed results. The grid-to-obs paired statistics may not be adequate  Multiple application of 4m limited-area domain QA forecasting: o Intensive measurement campaigns o Pre-launch calibration of retrieval algorithms.  Looking ahead: o CMAQ5.0 Options: lightning NO x, Windblown-dust o Explore metrics for 4km domain verification and evaluation Poster: Daniel Tong – Windblown dust emission module

19 Acknowledgement: This work is partially supported through NASA Air Quality Applied Sciences Team (AQAST) Tiger Team project.


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