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AIRS Profile Assimilation: Real-Time Demonstration Brad Zavodsky

AIRS Profile Assimilation: Real-Time Demonstration Brad Zavodsky Shih-hung Chou, Gary Jedlovec, Bill Lapenta SPoRT Science Advisory Committee: June 13, 2007. Overview.

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AIRS Profile Assimilation: Real-Time Demonstration Brad Zavodsky

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  1. AIRS Profile Assimilation: Real-Time Demonstration Brad Zavodsky Shih-hung Chou, Gary Jedlovec, Bill Lapenta SPoRT Science Advisory Committee: June 13, 2007

  2. Overview Relevance to SPoRT: Illustrates the ability to assimilate AIRS L2 profile data into a numerical weather prediction system in real time to aid forecasting of sensible parameters for short-term, regional, operational 6 – 48h forecasts • Motivation • Insights From Past Case Study Work • Real-Time Sample Timeline • Example of Real-Time Web Interface • Summary/Future Plans

  3. Motivation • Profiles may add value to WFOs running NWP systems not equipped to handle radiance data (e.g. MFL, MLB): • moisture return over Gulf • coastal processes • weather features over oceanic regions • Operationally, assimilation/forecasts must be completed in timely manner to be valuable for forecasters (e.g. available in AM for PM forecasts) • demonstrate ability using real-time system with near-real-time data • provide AIRS-enhanced initial conditions (ICs) to local WFOs • Select new case studies and compile long-term statistics

  4. L L L L L L Surface analysis 11/20/05 12 UTC Surface analysis 11/21/05 12 UTC Surface analysis 11/22/05 12 UTC WRF Domain for Nov. 2005 Case Study Insights From Case Study Work • Learned proper assimilation procedure for timely regional forecasts • scale factors and error characteristics of background and observations • use of quality indicators • initialization time to take into account model spin-up—assimilate only once • Positive impact on the initial conditions; varying results on regional forecasts • Need a larger number of forecasts (i.e. larger set of statistics) to determine true value of adding AIRS profiles • Must select proper case studies to show impact

  5. 0730Z 0800Z WRF 1100Z 0830Z ADAS WRF WRF 8h forecast CNTL WRF forecast complete CNTL ADAS analysis complete Wait for AIRS… Sample Timeline for Real Time Simulations • 12-km WRF & ADAS domains • Non-parallel, ADAS analysis; 15 nodes parallel WRF • AIRS 48h forecast at 1500 UTC; web products by 1600 UTC • 1600 UTC = 10:00 am CDT — timely enough for forecasters to use for afternoon forecasts Initialization by NAM 00Z analysis Obtaining and using AIRS profiles in real-time is not trivial!

  6. too far west granule center out of range currentplan • Challenges using NRT data from hyperspectral sounder on polar orbiter • data not available in real-time • wait for satellite overpass • ≈1 hr computation of L2 products • combine multiple swaths • data coverage and overpass time changes from day to day (too far west) • missing granules of data (out or range, error in retrieval) 7 June 2007 AM missing granule 1 June 2007 AM Challenges Using Near-Real-Time AIRS Data • Multiple NRT data sources through our collaborations • NESDIS • GES DISC • UW direct broadcast

  7. 0730Z 0800Z WRF 1100Z 0830Z ADAS WRF WRF 8h forecast CNTL WRF forecast complete CNTL ADAS analysis complete 1500Z 1230Z 1100Z Wait for AIRS… WRF ADAS AIRS WRF forecast complete AIRS ADAS analysis complete 0700Z 0900Z AIRS granules from Direct Broadcast AIRS overpass AIRS overpass Sample Timeline for Real Time Simulations • 12-km WRF & ADAS domains • Non-parallel, ADAS analysis; 15 nodes parallel WRF • AIRS 48h forecast at 1500 UTC; web products by 1600 UTC • 1600 UTC = 10:00 am CDT — timely enough for forecasters to use for afternoon forecasts Initialization by NAM 00Z analysis

  8. Real-Time Products to the Web • Results posted to private, in-house website • Daily Posting • surface and pressure-level maps • T, q, h, and V at 1000, 850, 700, 500 and 200 hPa • difference fields: T, q, h • T, q, h at 1000, 850, 700, 500, and 200 hPa • Delayed Posting • precipitation difference fields • verification statistics • bias and RMSE for T and q against east coast RAOBs and NAM analysis • qualitative precipitation forecasts (QPF) • bias score and equitable threat score against Stage IV precipitation • Website: Real-Time AIRS Assimilation Website Backup website

  9. Summary • Analysis/forecast system currently running in real-time for V4 AIRS profiles—waiting for V5 • Assist in selection of case studies and calculation of long-term statistics of sensible weather parameters (e.g. precipitation) • 48h forecast with AIRS data assimilation complete in 4 hours • difference fields between control and AIRS-assimilated forecasts posted daily to web by 1600 UTC • in time to aid forecasters in making afternoon/evening forecasts using output • WFOs can use AIRS-enhanced initial conditions for local model runs and help assess value of AIRS profiles in regional modeling

  10. Future Work • Continue collaboration with AIRS Science Team and University of Wisconsin to get V5 AIRS data onto the direct broadcast server as quickly as possible • Monitor daily weather and AIRS impact to select case studies • Calculate statistics over extended period of time for more thorough determination of AIRS impact • AIRS-enhanced ICs to WFOs—they help assess value • Optimize analysis/forecast: • introduce parallelized variational assimilation system • explicit use of observation error in AIRS profiles • parallelization speeds up analysis procedure • improve analysis/forecast dynamic balance constraints • use three-dimensional intelligent data thinning (IDT; being developed through SPoRT partnership with FIT and UAH ITSC) to reduce data volume

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