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William. M. Lapenta Acting Director Environmental Modeling Center NOAA/NWS/NCEP Geoff DiMego , John Derber , Yuejian Zhu , Hendrik Tolman , Vijay Tallapragada, Shrinivas Moorthi , Mike Ek , Mark Iredell , Suru Saha . The NOAA Operational Numerical Guidance System:

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slide1

William. M. LapentaActing DirectorEnvironmental Modeling CenterNOAA/NWS/NCEPGeoff DiMego , John Derber , Yuejian Zhu , Hendrik Tolman , Vijay Tallapragada, Shrinivas Moorthi , Mike Ek , Mark Iredell , Suru Saha

The NOAA Operational Numerical Guidance System:

Meeting the WoFand WRN Challenge

noaa center for weather and climate prediction a game changer
NOAA Center for Weather and Climate Prediction: “A Game Changer”

A.K.A.—the new building….

  • Four-story, 268,762 square foot building in Riverdale, MD will house 800+ Federal employees, and contractors
    • 5 NCEP Centers (NCO, EMC, HPC, OPC, CPC)
    • NESDIS Center for Satellite Applications and Research (STAR)
    • NESDIS Satellite Analysis Branch (SAB)
    • OAR Air Resources Laboratory
  • Includes 465 seat auditorium & conference center, library, deli, fitness center and health unit
  • Includes 40 spaces for visiting scientists
  • Represents a “Game Changer” in our ability to do business
noaa operational numerical guidance supports the agency mission
NOAA Operational Numerical Guidance Supports the Agency Mission

Lead Time and Accuracy!

  • Numerical Weather Prediction at NOAA
    • Related to ability to meet service-based metrics (below)
  • National Weather Service GPRA* Metrics

(* Government Performance & Results Act)

    • Hurricane Track and Intensity
    • Winter Storm Warning
    • Precipitation Threat
    • Flood Warning
    • Marine Wind Speed and Wave Height
  • Customer Service Provider
    • Operational numerical guidance provides foundational tools used by Government, public and private industry to Improve public safety, quality of life and make business decisions that drive US economic growth

3

slide4

DRAFT Storm Prediction Center

  • Potential Products and Services
slide5

DRAFTStorm Prediction Center

  • Desired Numerical Guidance Attributes
  • Inside every HRRRE member
  • Movable domain update SSEF:
  • 1 km movable regional domain
  • 20-30 member storm scale ensemble
  • advanced state-of-the-science DA
  • run every 1 hr with forecasts to 18-24 hr
  • focused on “severe weather of the day” areas

5

plans for a national mesoscale ensemble system
Convergence of NAM, RAP, HRRR and SREF between 2016 and 2018

System must meet requirements of today and future

Provide NextGen Enroute AND terminal guidance

Provide PROBABILITY guidance with full Probability Density Function specified

Address Warn-on-Forecast as resolutions evolve towards ~1 km

Core elements

Common data assimilation system

Code Infrastructure and management system

Potential Attributes of the North American Rapid Refresh Ensemble (NARRE)

Hourly updated with forecasts to 24 hours

Control data assimilation cycles with 3 hour pre-forecast period

84 hr forecasts are extensions of the 00z, 06z, 12z, & 18z runs

Plans for a National Mesoscale Ensemble System
noaa s operational numerical guidance suite
NOAA’s OperationalNumerical Guidance Suite

Oceans

HYCOM

WaveWatch

III

Forecast

  • NOS – OFS
  • Great Lakes
  • Northern Gulf of Mex
  • Columbia R.
  • Bays
  • Chesapeake
  • Tampa
  • Delaware

Climate Forecast

System

Hurricane GFDL

HWRF

Coupled

GFSMOM4

NOAH Sea Ice

Sea Nettle

Forecast

~2B Obs/Day

Satellites + Radar

99.9%

Dispersion

ARL/HYSPLIT

Regional NAM

WRF NMMB

Regional

DA

Global

Forecast

System

Global Data

Assimilation

Severe Weather

WRF NMM/ARW

Workstation WRF

Short-Range

Ensemble Forecast

Space

Weather

North American Ensemble Forecast System

Regional DA

WRF: ARW, NMM

NMMB

Air Quality

GFS, Canadian Global Model

ENLIL

NAM/CMAQ

Rapid Refresh

for Aviation

7

7

7

NOAH Land Surface Model

slide8

Numerical Guidance Suite Execution

on the Operational NOAA Supercomputer

24-h Snapshot 20 August 2012

Number of Nodes

High Water Mark 2010

SREF

12

18

GFS

00

06

00

NAM

CFS

GEFS

Time of Day (UTC)

8

slide9

Operational Compute Resource Consumption (%) by Component

  • Statistics accumulated over a 24-h period
  • Total 64.9% of production machine
  • NAM, CFS and SREF compose 29.7% of production

Percent of Total CPU

Numerical Guidance System Component

9

global data assimilation system upgrade
Global Data AssimilationSystem Upgrade

Implemented 22 May 2012

  • Hybrid system
    • Most of the impact comes from this change
    • Uses ensemble forecasts to help define background error
  • NPP (ATMS) assimilated
    • Quick use of data 7 months after launch
  • Use of GPSRO Bending Angle rather than refractivity
    • Allows use of more data (especially higher in atmos.)
    • Small positive impacts
  • Satellite radiance monitoring code
    • Allows quicker awareness of problems (run every cycle)
    • Monitoring software can automatically detect many problems
  • Partnership between research and operations
    • (NASA/GMAO, NOAA/ESRL, Univ OK, and NOAA/NCEP)
  • Consolidation across systems
    • Unify operational data assimilation system for global, regional and hurricane applications
    • Cost effective—O&M
    • Configuration management
ncep closing the international gap june july august 500hpa geopotential rmse
NCEP Closing the International GapJune, July, August 500hPa Geopotential RMSE

2011

2012

Meteo-Fr

CMC

NCEP

UKMO

ECMWF

Solid line lower than dashed indicates improvement between 2011 and 2012

NCEP Only System to show improvement between 2011 and 2012

  • NCEP achieved significant improvement in 2012 for day 3 and beyond
  • NCEP is now similar to UKMO skill in this metric and AC
gridpoint statistical interpolation gsi data assimilation system
Gridpoint Statistical Interpolation(GSI) Data Assimilation System
  • Unified variational data assimilation (DA) system
    • Global and regional applications
    • Weather and climate
  • Operational system being used by
    • NOAA (GFS, NAM, RTMA, HWRF, RAP…)
    • NASA (GMAO global)
    • AFWA (Testing in progress)
  • Distributed development:
    • NCEP/EMC, NASA/GMAO, NOAA/ESRL, NCAR/MMM, …
  • A community code used in NOAA operations and research
    • Supported by NCEP, NASA, DTC
    • Disciplined code management policy and procedures required to incorporate changes across user organizations

http://www.dtcenter.org/com-GSI/users/index.php

goals of community gsi efforts
Goals of Community GSI Efforts
  • Provide current operational GSI capabilities to the research community (O2R)
  • Provide a framework for distributed development of new capabilities & advances in data assimilation
  • Provide a pathway for data assimilation research to operations process (R2O)
  • Provide rational basis to operational centers and research community for enhancement of data assimilation systems
adding new analysis variables to gsi
Adding New AnalysisVariables to GSI
  • No longer a difficult procedure
    • Thanks to GSI Bundle infrastructure (via NCEP/NASA collaboration)
  • Generalized structure for analysis, guess, state, and control variables
    • e.g., hydrometeors, vertical velocity, double moment microphysics variables, etc.
  • Control through table in the anavinfo file
  • Greatly reduces the number of routines needed to be modified
    • Modify table(s) + possible additional model I/O steps + observation ingest + forward operator + background error
    • Can also disable the conventional large-scale balance constraints present in the NMC derived background errors
slide15
North America Model (NAM)

Implemented 18 October 2011

NEMS based NMM

Outer grid at 12 km to 84hr

Multiple Nests Run to ~60hr

4 km CONUS nest

6 km Alaska nest

3 km HI & PR nests

1.3km DHS/FireWeather/IMET (to 36hr)

Rapid Refresh (RAP)

Implemented 1 May 2012

WRF-based ARW

Use of GSI analysis

Expanded 13 km Domain to include Alaska

Experimental 3 km HRRR

NOAA Operational Mesoscale

Modeling for CONUS:

WRF-Rapid Refresh domain – 2010

RUC-13 CONUS domain

Original CONUS domain

Experimental 3 km HRRR

numerical guidance to support a nws operational warn on forecast capability

Numerical Guidance to Support a NWS Operational Warn on Forecast Capability

S. Lord – NWS/OST

and

NCEP/EMC Staff

V4.0

introduction
Introduction
  • Goal: field an operational, credible and skillful WoF capability by 2025
  • Combines forecast requirements for
    • NWS severe weather forecasts and warnings
    • Aviation (NEXTGEN)
    • Daily general weather guidance to 3 days, including QPF
  • Closely allied with Hurricane forecast technology (HFIP)
  • Effort exceeds decade-long development and implementation cycle
    • Current operational system provides look at the future pieces
    • Incremental system development provides a risk-managed path for operations
    • With sustained development of the operational pieces, and sufficient HPC, NOAA (OAR and NWS) can achieve the WoF goal
      • Development of operational systems provides enhancement and generalized capabilities to incorporate R&D and improve capabilities (including forecast skill)
      • Improved skill must be documented with appropriate performance measures (TBD)
  • HPC capability growth is essential to meet goal
    • Adequate resolution for predicting high impact weather events poses largest operational HPC requirements
      • Forecast model
      • Data assimilation
      • Ensemble & postprocessing system
    • Advanced nature of severe weather problem requires larger ratio of R&D HPC to operational HPC
    • Constant $$ HPC growth and new technology (e.g. GPU, MIC, etc) will be necessary but insufficient
international thrust ukmo 2014
International Thrust – UKMO 2014
  • UK is a very small country!
    • Area covers approximately Fire Wx nest (next slide)
    • Weather events less diverse
    • Regional high resolution NWP is more affordable computationally
  • US global system (planned for 2014) has comparable resolution
    • SL T1148 (17 km)
    • Hybrid DA (27 km ensemble) enhances skill to comparability with UKMO
  • US regional system lags in operational implementation (due to HPC constraints) but not technology level
global continental local nesting strategy
Global  Continental  Local Nesting Strategy
  • Discussion items
    • Nesting necessary to save computing; current NAM domain could be expanded to global 10 km
    • Advantages/disadvantages of same model for global and regional
    • Applicability (DA) of a multi-model ensemble-based covariance estimate with multiple bias characteristics
    • Data assimilation at resolution of 3 km or less poses challenges
      • Advanced assimilation of radar reflectivity
      • Consistent integration of radar and satellite info
      • Proper dynamically balanced analysis increments at multiple high resolution scales (10, 3, 1 km) to minimize spin-up/spin-down and maximize evolution of nascent disturbances
numerical guidance attributes 1
Numerical Guidance Attributes (1)
  • Analysis and uncertainty products
    • Hourly refresh but sub-hourly for rapidly changing observables (reflectivity, hydrometeors, wind shear)
    • 1 km resolution for rapidly changing observables
    • Hybrid analysis provides analysis uncertainty information and ensemble perturbations
    • Multi-model ensemble-based background (technology not developed)
    • Analysis variables
      • Surface (sensible wx) variables
      • Clouds
      • Radar reflectivity, hydrometeors
      • 3-D atmosphere
      • Aerosols
      • Skin temperature
      • Precipitation amount and hydrometeors
      • Land & hydrology
      • Eventual coupled system to add marine & coastal analysis (waves, water level, water quality)
    • Products support forecaster Situational Awareness (SA)
      • MRMS products are an initial capability
      • Enhancement to Rapidly Updating Analysis (RUA)
        • Combines obs. from
          • Radar
          • Satellite
          • In situ
        • Expands to hydrological and coastal marine domain
        • Provides best and consistent geophysical picture from all available information
    • Catchup cycle for late data produces “Analysis of Record” for verification
numerical guidance attributes 2
Numerical Guidance Attributes (2)
  • Initialized from hourly analysis
  • Evolved through RAP, HRRR & NAM development
    • North American Rapid Refresh Ensemble (NARRE)
    • High Resolution Rapid Refresh Ensemble (HRRRE)
  • 1-way nested
    • Technology available in NAM as prototype
    • 1 km resolution where needed
    • Ensemble-based probabilistic products support
      • Severe convective weather (incl. tornado environment)
      • Aviation and surface transportation
      • Landfalling hurricanes
      • Flash floods
    • Eventual support for
      • Storm surge
      • Waves
      • Water quality
  • High resolution analysis and nested forecast system provide consistency between real-time SA and forecast evolution
slide24

Runtime & optimal node apportionment for operational

NMMB nesting with a Fire Wx nest over CONUS (72 nodes)

12 km parent 8/72 or 11%

6 km Alaska nest 5.72 or 7%

1-way nests solved simultaneously

WRF-NMM takes 3.6 times longer than NEMS-NMMB to run

Fire Wxnest

Increased nest capability by adding processors!

4 km CONUS nest 40/72 or 56%

1.33 km CONUS FireWx nest 12/72 or 17%

3 km Hawaii nest 4/72 or 5%

3 km Puerto Rico nest 3/72 or 4%

24

summary
Summary
  • Ensemble-based probabilistic guidance for WoF is a major challenge
    • Scientific development
    • Demonstration of system capabilities
  • Current operational capabilities can provide basis for future system
    • But many changes necessary in response to R&D needs and results
  • HPC is second major challenge
    • Prototype system exceeds planned availability by factor of 4-6
      • R&D may suggest compromises and where to spend HPC resources to achieve required skill affordably
2015 2016
North American Rapid Refresh ENSEMBLE (NARRE)

NMMB (from NCEP) & ARW (from ESRL) dynamic cores

Common use of NEMS infrastructure and GSI analysis

Common NAM parent domain at 10-12 km

Initially ~6 member ensemble made up of equal numbers of NMMB- & ARW-based configurations

Hourly updated with forecasts to 24 hours

NMMB & ARW control data assimilation cycles with 3-6 hr pre-forecast period (catch-up) with hourly updating

NAM & SREF 84 hr forecasts are extensions of the 00z, 06z, 12z, & 18z runs – for continuity sake.

SREF will be at same 10-12 km resolution as NARRE by then

SREF will have 21 members plus 6 from NARRE for total of 27

NARRE requires an increase in current HPCC funding

DiMego

2015-2016
2017 2018
High Resolution Rapid Refresh ENSEMBLE (HRRRE)

Each member of NARRE contains 3 km nests

CONUS, Alaska, Hawaii & Puerto Rico/Hispaniola nests

The two control runs initialized with radar data & other hi-res obs

This capability puts NWS/NCEP[+OAR/ESRL] in a position to

Provide NextGenEnroute AND Terminal guidance (FWIS-like)

Provide PROBABILITY guidance with full Probability Density Function specified, hence uncertainty information too

Provide a vehicle to improve assimilation capabilities using hybrid (EnKF+4DVar) technique with current & future radar & satellite

Address Warn-on-Forecast as resolutions evolve towards ~1 km

NAM nests are extensions of the 00z, 06z, 12z & 18Z runs.

HRRRE requires an increase in HPCC funding over and above that required for the NARRE

DiMego

2017-2018