Future NCEP Guidance Support for Surface Transportation by qob12941

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									Future NCEP Guidance Support
  for Surface Transportation

              Stephen Lord
     Director, NCEP Environmental
            Modeling Center
              26 July 2007
                                    1
                     Overview
• Weather for Roads, Air transportation, etc.
  – National picture
     • New ensemble products
  – Local picture
     • Downscaling
        – Real-time Mesoscale Analysis (RTMA)
        – Land Information System (LIS)
        – Dynamical – Statistical approach
• Marine applications
  – Waves
  – Water levels
• Data availability
• What’s needed to move ahead
                                                2
        New Ensemble Products from
        NCEP Storm Prediction Center
  • NCEP Short-Range Ensemble Forecast (SREF) System
  • National coverage ~ 30 km grid
  • Probabilistic guidance with extremes
SREF Maximum (any member)      SREF Pr[Ptype = ZR] and Mean   SREF 6h Calibrated Probability
  3h Accumulated Snowfall            P03I (contours)              of Snow/Ice Accum




                                                                Accumulation based on MADIS
                                                                   road surface condition
                         D. Bright
                        NCEP/SPC                                                          3
SREF Likely PTYPE and Mean P03I (contours)
                      24 h Fcst
                 Precip Type, Amount
                    32 F Isotherm

                ZR
                                         Snow




                                                 D. Bright
                                                NCEP/SPC
      IP



                                       Rain




                                                      4
                                    Downscaling
   • Future computing requirements
           – National scale ~20 years to reach sufficient resolution
   • Dynamical-statistical approach
           – Real time Mesoscale Analysis (RTMA)
           – Land Information System (LIS)
           – Bias correction and statistical processing
   • Components under development

Forecast      Current      Current      Future       Future       Other factors   Total     Years to
System        Horizontal   Vertical     Horizontal   Vertical                     Compute   Achieve at
              Resolution   Resolution   Resolution   Resolution                   Factor    current
                                                                                            constant
                                                                                            funding
NAM               12           60           2           100       2x physics         720        19
SREF              37           48           5           100                          844        20
                                                                                                     5
         Real-Time Mesoscale Analysis
                    (RTMA)
    •    5 km National (NGDG) grid (eventually 2.5 km)
    •    Hourly analysis
          – Focus on “drawing to obs” (mesonet)
          – Temperature, precipitation, surface wind, dew point
          – Anisotropic (e.g. land-water contrast)
    •    Analysis uncertainty                                                           M. Pondeca
    •    To include cloud cover                                                          J. Purser
    •    Will cover CONUS, Alaska, Hawaii, Puerto Rico, Guam                            G. DiMego
                                                                                      NOAA/GSD - RUC
RTMA Temperature Analysis (° F)   RTMA Temperature Analysis Uncertainty (° F)   RTMA 1-hour Precipitation Analysis
        (17Z 6/14/07)                          (17Z 6/14/07)                         (inches) (01z 6/14/07)




                                                                                                           6
     Land Information System (NASA/NOAA)
     •    Land states forced by                                           S. Kumar
           – Observed precipitation                                       Jim Geiger
           – Model solar, long wave radiation,                         C. Peters-Lidard
             cloudiness                                                     J. Meng
     •    Noah Land Surface Model (LSM) defines                           K. Mitchell
          skin temperature, soil moisture, etc.
     •    Can be run at 1 km resolution (below)

Surface (skin) Temperature      50 km area         Washington DC    NASA LSM GFS forcing
                                    00 UTC 1 July – 21 UTC 1 July

 00 UTC                   03 UTC                    06 UTC            09 UTC
  7 PM                    10 PM                      1 AM              4 AM




 12 UTC                   15 UTC                    18 UTC            21 UTC
  7 AM                    10 AM                      1 PM              4 PM


                                                                                    7
 Dynamical Statistical Approach
• Bias correction of forecast fields with respect to model
  analysis (e.g. NAM)
• “Downscaling Transformation” (DT)
   – Produces time-dependent differences between coarse forecast
     model (e.g. 12 km NAM) and RTMA (5 km)
• Downscaled (local) fcst =
           NAM fcst + Bias correction + DT
   – On local grid
• Probabilistic products
   – Created from ensemble systems (SREF, GENS) through
     Bayesian Model Averaging (BMA) approach
   – Applications for
       • Road transportation
       • Air transportation management (NEXTGEN)                   8
       • Severe weather forecasting
                    Marine Applications
                  Multi-Grid Wave Modeling
               Higher coastal
              model resolution               Deep ocean model resolution




Highest model resolution
   in areas of special                                       Multi-grid wave model tentative
         interest                                          resolutions in minutes for the parallel
                   Hurricane nests moving                    implementation in FY2007-Q4.
                   with storm(s) like GFDL
                          and HWRF                                                              9
                                               Wave ensemble system application for ship routing
 NCEP Real-Time Ocean Forecast System (RTOFS)
 Operational December 2005, upgraded June 2007
• RTOFS provides
   – Routine estimation of the ocean
     state [T, S, U, V, W, SSH]
       • Daily 1 week forecast
   – 5 km coastal resolution
   – Initial and boundary conditions
     for local model applications
• Applications
   – Downscaling support for water levels
     for shipping                           Chesapeake Bay
   – Water quality
   – Ecosystem and biogeochemical
     prediction
   – Improved hurricane forecasts
   – Improved estimation of the
     atmosphere state for global and
     regional forecasts                                      10
• Collaboration with NOAA/NOS
           Product Availability
•   Three levels of information
    – Routinely delivered
      1. Pointwise, single-valued, downscaled MLF* from
         all available guidance on NDGD grid
      2. Description of forecast uncertainty through
         probability density function (mode & 10/90 %ile)
      • Accompanying post-processed fields
         – Meteorologically consistent
         – Closest to MLF*
    – “On-demand” (via publicly accessible server)
      3. Individual ensemble member forecasts available
      • Prototype: NOMADS                               11
                                         * MLF – Most Likely Forecast
          What’s Needed?
• Written requirements for surface
  transportation to NWS
• Operational (and research) computing
  resources
• Acceleration of current dynamical-
  statistical efforts
• Outreach and coordination with local users

                                           12
      Concurrent execution of global and
      regional forecast models (Phase 2)
Analysis              Global/Regional Model Domain                    Model Region 1




  •   Real time boundary and initial conditions
      available hourly                                                Model Region 2
       – “On-demand” downscaling to local applications
            • Similar to current hurricane runs but run either
                 – Centrally at OR
                 – Locally (B.C, I. C. retrieved from on-line data)
            • No boundary or initial conditions older than 1 hour
       – Flexibility for “over capacity” runs (e.g. Fire Wx, Hurricane)
            • Using climate fraction must be planned
            • No impact on remainder of services                          Local Solution

  •   For NEXTGEN: A consistent solution from global to local with a single
                                                                       13

      forecast system and ensembles providing estimate of uncertainty

								
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