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1 Examination of Nesting Requirements for CONUS and OCONUS in 2020+ Presented By: Geoff DiMego (NCEP/EMC) Contributors: Stan Benjamin, Curtis Alexander (ESRL/GSD) Eric Rogers, Tom Black, Jacob Carley (NCEP/EMC) Sam Trahan, Vijay Tallapragada (NCEP/EMC)
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2 Operational System Attribute(s) System NameAcronymAreal Coverage Horz ResCycle Freq Fcst Length High Resolution Rapid RefreshHRRRCONUS3 km1 hr15hr North American Mesoscale NestNAMnestO/CONUS3-6 km [3km pending] 6 hr [1hr pending] 60hr North American Mesoscale Fire WxNAMfrwxPlaceable 375x375 1.33 km 1.5 km 6 hr36hr High Resolution Window [00z & 12z] HiRESWCONUS, HI & Guam 3-4km12 hr48hr High Resolution Window [6z & 18z]HiRESWAlaska, PR3-4km12 hr48hr Hurricane WRFHWRFNest2 km6 hr120hr SystemAttributes HRRR GSI 3DVAR (hybrid pending) w/15min radar data for 1 hour [RAP] RAP/NAM GSI EnKF-3DVAR hybrid, Diabatic Digital Filter w/radar data [GFS] NAM nests GSI EnKF-3DVAR hybrid (w/radar reflectivity pending) [NAM] HiRESW Init conditions from RAP for CONUS, from GFS for OCONUS [GFS] HWRF GSI 3DVAR hybrid w/tail Doppler radar [2-way large basin] System Data Assimilation or Initialization Technique [LBC]
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3 Why System(s) are Operational Primary stakeholders and requirement drivers The Weather enterprise, NWS regions & WFOs, NCEP centers, Water Center, NIFC Boise & USFS, severe/hazardous wx, aviation/transportation, fire wx, energy, hydrology, disaster recovery, NextGen etc What products are the models contributing to? NDFD forecasts, watches/warnings, outlooks, RTMA/URMA (RUA Rapidly Updating Analysis - pending), AirQuality, WRF-hydro, WoF etc What product aspects are you trying to improve with your development plans? QPF, sensible & severe wx via physics development Move away from deterministic to all ensemble based guidance suite Move from irregular to regular/reliable convection allowing scale HREF with earlier delivery time, consolidates HRRR, NAM-nests & HiRESW. Top 3 System Performance Strengths Provides hi-res guidance to the whole nation albeit irregularly Provides both 1st look & outlook, highly efficient nesting in NMMB Hourly updates, aviation hazards, impactful storms/wx, aerosol capable Top 3 System Performance Challenges Convective initiation, QPF biases, stable PBL, cloud decks Advancing to 3km hourly/subhourly ensemble data assimilation Large/diverse enough membership of High-Res Ensemble Forecast (HREF)
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4 System Evolution Over the Next 5 Years Major forcing factors Increasing obs – GOES-R, aircraft, renewable energy, ceilometers, ccpp Increase of high-impact wx events (flash floods, t-storms, wildfires, etc.) Increase in NCEP High Performance Computing (HPC) Science and development priorities Move to probabilistic guidance Ensemble data assimilation Improved physical parameterizations Broader services e.g. atmospheric/land-surface forcing for WRF-Hydro Hazardous event detection tool – collaboration with FACETs, Provide initial/lateral boundary conditions for Warn-On-Forecast What are your top challenges to evolving the system(s) to meet stakeholder requirements? Resistance to ensembles & streamlining, must be able to drop legacy stuff HPC for ens DA and ens forecasts, observational data latency and QC, more tropical storms & basins, NextGen terminal requirements Leveraging selected NGGPS dynamic core and unifying regional efforts around this core once the capability is in place Potential opportunities for simplification going forward Unify all regional modeling applications with HREF & SREF consolidation, eventually including rapid refresh, hurricane, fire weather, AQ etc using a single-dycore [from NGGPS?]. Single ensemble DA including aerosols and even land-surface. Retain GSI common regional/global DA. Use same physics with scale-aware and aerosol-aware capability and inline aerosols for both regional and global models.
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5 Top 3 Things You Need From the UMAC 1.Start with the simplest possible future operational suite (single regional model/ens/assim and single global model/ens/assim). Then, UMAC can help NOAA consider if all forecast requirements can be met by them before adding complexity. Simplicity is more plausible with a 3km global model. Similarly, given a 1km regional ensemble Expanded CONUS including all area within 48h landfall Avoid all moving nests because fixed nests support ensemble effectiveness. 2.Help with trade offs among delivery time, forecast range, update frequency, number of nests, ensemble size & member configuration choices etc 3.Guidance on how to focus/balance resources (computing & manpower) based on multitude of requirements (convection allowing ensembles, ensemble DA, NGGPS dy-core, WOF, etc).
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