William. M. Lapenta
1 / 19

The NCEP Global and Regional Operational Numerical Guidance Systems  - PowerPoint PPT Presentation

  • Uploaded on

William. M. Lapenta Acting Director Environmental Modeling Center NOAA/NWS/NCEP With contributions from many EMC Staff ……. The NCEP Global and Regional Operational Numerical Guidance Systems . Presentation Outline. The EMC Mission Importance of satellite data to NWP

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' The NCEP Global and Regional Operational Numerical Guidance Systems ' - livingston-aron

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
William. M. LapentaActing DirectorEnvironmental Modeling CenterNOAA/NWS/NCEPWith contributions from many EMC Staff……

The NCEP Global and Regional Operational Numerical Guidance Systems 

Presentation outline
Presentation Outline

The EMC Mission

Importance of satellite data to NWP

Global Forecast & Data Assimilation System


Operational Requirements

Data Assimilated

Performance evolution since 1998

CONUS Mesoscale Model System

Hybrid GSI Var-EnKF Assimilation

System Upgrade Process

The emc mission
The EMC Mission…..

In response to operational requirements:

  • Develop and Enhancenumerical guidance

    • Improve NCEP’s numerical forecast model systems via:

      • Scientific upgrades

      • Optimization

      • Additional observations

  • Transition operational numerical forecast models from research to operations

    • Transform & integrate

      • Code

      • Algorithms

      • Techniques

    • Manages and executes transition process including technical and system performance review before implementation

  • Maintain operational model suite

    • The scientific correctness and integrity of operational forecast modeling systems

    • Modify current operational system to adapt to ever-present external changes

EMC location within the funnel

Nws seamless suite of forecast products spanning weather and climate
NWS Seamless Suite of ForecastProducts Spanning Weather and Climate



Threats Assessments

Forecast Lead Time



Warnings & Alert Coordination


NCEP Model Perspective






  • Climate Forecast System

2 Week

  • North American Ensemble Forecast System

  • Global Ensemble Forecast System

1 Week

  • Global Forecast System

  • Short-Range Ensemble Forecast



Real Time Ocean Forecast System

  • North American Mesoscale


  • Rapid Update Cycle for Aviation

Hurricane WRF & GFDL

Space Weather



  • Dispersion Models for DHS










Fire Weather

Life & Property

Energy Planning

Reservoir Control

Emergency Mgmt

Space Operations

Satellite data is required to help meet key performance metrics
Satellite Data is Required to Help Meet Key Performance Metrics

  • Numerical Weather Prediction

    • Global Anomaly Correlation Score – “Internal” metric

    • Related to ability to meet service-based metrics (below)

  • National Weather Service GPRA* Metrics

    (* Government Performance & Results Act)

    • Hurricane Track and Intensity Forecast Accuracy

    • Winter Storm Warning Lead Time and Accuracy

    • Precipitation Threat Accuracy

    • Flood Warning Lead Time and Accuracy

    • Marine Windspeed and Wave Height Forecast Accuracy

  • NAM and GFS are primary tools used by the NWS to meet the above goals

Global data assimilation system gdas
Global Data Assimilation System (GDAS) Metrics

Grid-point Statistical Interpolation (GSI)

3D-variational approach

Unified system for all NCEP atmospheric applications

Global (GDAS/GFS)

Regional (NDAS/NAM) & HWRF

Real Time Mesoscale Analysis (RTMA)

Rapid Refresh (RR)

Developed for operational application

Forecasts must be completed within schedule


More accurate formulation – higher resolution

Improved model – improved analysis

Enhanced physics – higher resolution

Must work everywhere – all the time

Manual intervention should be minimal

Both operational and research data used in systems

Assimilated satellite radiance data
Assimilated Satellite Radiance Data Metrics

GOES-11 Sounder: Thinned to 120km

Channels 1-15

Individual fields of view

4 Detectors treated separately

Over ocean only

AMSU-A: Thinned to 60km

NOAA-15 Channels 1-10, 12-13, 15

NOAA-18 Channels 1-8, 10-13, 15

METOP Channels1-6, 8-13, 15

AMSU-B/MHS: Thinned to 60km

NOAA-15 Channels 1-3, 5

NOAA-18 Channels 1-5

METOP Channels 1-5

HIRS: Thinned to 120km

NOAA-17 Channels 2-15

METOP Channels 2-15

AIRS: Thinned to 120km

AQUA 148 Channels

GOES-11 Sounder

Channels 1-15

Individual fields of view

4 Detectors treated separately

Over ocean only


NOAA-15 Channels 1-10, 12-13, 15

NOAA-18 Channels 1-8, 10-13, 15

NOAA-19 Channels 1-7, 9-13, 15

METOP Channels 1-6, 8-13, 1

AQUA Channels 6, 8-13


NOAA-15 Channels 1-3, 5

NOAA-18 Channels 1-5

METOP Channels 1-5


NOAA-17 Channels 2-15

NOAA-19 Channels 2-15

METOP Channels 2-15


AQUA 148 Channels


METOP 165 Channels

Global: All thinned to 145km


Assimilated Conventional Data and Satellite Products Metrics

Satellite Products


  • Radiosondes

  • Pibal winds

  • Synthetic tropical cyclone winds and pressures(when needed)

  • Wind profilers

  • Conventional aircraft reports

  • ASDAR aircraft reports

  • MDCARS aircraft reports

  • Dropsondes

  • Surface land observations

  • Surface ship and buoy observation

  • Doppler radial velocities (regional)

  • VAD (NEXRAD) Winds

  • TAMDAR aircraft data

  • Mesonet data

  • MODIS IR and water vapor winds

  • GMS, METEOSAT and GOES cloud drift IR and visible winds

  • GOES water vapor cloud top winds

  • TRMM TMI precipitation estimates

  • GPS precipitable water estimates

  • GPS Radio occultation refractivity profiles

  • SBUV ozone profiles (other ozone data under test)

  • OMI total ozone


Global data assimilation upgrade q3fy11 late april
Global Data Assimilation Upgrade MetricsQ3FY11—Late April

Analysis Changes

Recomputed background errors

New version of CRTM 2.0.2

Improved Field of View calculation

Updates for thinning and collocation calculations

QC and obs. error and data handling updates for


AMSU-A (channel 5)


SBUV/2 ozone

Ocean buoys

New analysis options (useful for next

round of development)

Model Changes

Thermal roughness length upgrade

(X. Zeng, U. Arizona)

Stratospheric tuning

5-Day 500MB NH AC

00Z Cycles 16 June-29 Sept 2010

Day 8

500-hPa Height AC Frequency Distribution, GFS 00Z Cycle Day-5 Forecast

Southern Hemisphere



Northern Hemisphere



Poor forecasts (AC < 0.7) decrease

Good forecasts (AC > 0.9) increase

Percentage of Poor Forecasts Day-5 Forecast

5-Day 500mb AC < 0.7 v.s. Model Upgrades

AMSU-A & HIRS-3 data

T126L28 (100km) to T170L42 (70km)

Physics upgrade to prognostic cloud water, cumulus momentum transport

T170L42 (70km) to T254L64 (55km)

T254L64 (55km) to T382 (38km)


T382L64 (38km) to T574L64 (27km)

New shallow convection; updated SAS and PBL; positive-definite tracer transport

Percentage of Good Forecasts Day-5 Forecast

5-Day 500mb AC < 0.9 v.s. Model Upgrades

T382L64 (38km) to T574L64 (27km)

New shallow convection; updated SAS and PBL; positive-definite tracer transport

Flow-dependent error covariance; Variational QC

T254L64 (55km) to T382 (38km)


T170L42 (70km) to T254L64 (55km)

AMSU-A & HIRS-3 data

NCEP Mesoscale Modeling for CONUS: Day-5 ForecastPlanned Q3 & Q4 FY11


NEMS based NMM

Bgrid replaces Egrid

Parent remains at 12 km

Multiple Nests Run to ~48hr

~4 km CONUS nest

~6 km Alaska nest

~3 km HI & PR nests

~1.5-2km DHS/FireWeather/IMET possible

Rapid Refresh

WRF-based ARW

Use of GSI analysis

Expanded 13 km Domain to include Alaska

Experimental 3 km HRRR

WRF-Rapid Refresh domain – 2010

RUC-13 CONUS domain

Original CONUS domain

Experimental 3 km HRRR

Development of gsi hybrid var enkf
Development of GSI Hybrid Var-EnKF Day-5 Forecast

  • Test Period: 01 Aug to 22 September 2010

  • Deterministic Forecasts: Operational GFS @ T574L64

  • Ensemble Configuration:

    • 80 ensemble members

    • GSI for observation operators

    • T254L64 operational GFS

  • Initialized 00 UTC 15 July 2010 from interpolated GEFS members

    • allowed over 2 weeks spin-up

  • Assimilate all operational observations

    • Includes early (GFS) and late (GDAS/cycled) cycles

    • Operational prepbufr files (no prep/additional qc)

  • Dual-resolution/Coupled

    • High resolution control/deterministic component

    • Includes TC Relocation on guess

    • Ensemble is recentered every cycle about hybrid analysis

    • Throw out EnKF analyis mean

  • Bias correction (satellite) coefficients come from GSI/VAR

  • Minimal tuning done for hybrid

    • 1/3 static B, 2/3 ensemble

500 hpa sh ac time series 6 aug to 21 sept 2011
500 hPa SH AC Time Series Day-5 Forecast6 Aug to 21 Sept 2011

Day 5

+0.026 AC

Black – Control

Red – Hybrid

Green – Operational

Day 6

+0.035 AC

Process to Implement Major Upgrades Day-5 Forecastto The NCEP Model Production Suite

  • Implementation Phase

  • SPA’s build NCO parallel from RFC’s

  • 30-day NCO parallel

    • Test code stability

    • Test dataflow

    • Products to NCEP Centers and EMC code developers

  • NCEP Centers

    • Evaluate impact

    • Assessments to NCEP OD

R&D and Pre-Implementation Phase



  • EMC Change Control Board

  • Scientific Integrity

  • Product Quality

  • EMC Mgmt Approval

  • 30-day NCO parallel stable

  • NCEP centers approve

  • Briefing to NCEP Director for final approval

  • Generate RFC’s

  • Submit RFC’s to NCO


Schedule For the GFS/GSI Day-5 ForecastDecember 2009 Implementation

  • 17 months required to develop, test and implement

  • 119 person months of effort (EMC, NCO, GFDL, TPC, SPC, HPC, AWC)

  • 17 months of continuous cycles 4/day with 16 day forecasts retrospective/real-time testing conducted for GFS/GSI

  • 500 HWRF and 600 GFDL TC/Hurricane cases simulated

  • 1000 Node hours and 75 TB of disk consumed

Thanks for your time… Day-5 Forecast

Impact of satellite data on nwp
Impact of Satellite Data on NWP….. Day-5 Forecast

Operational ECMWF system September to December 2008. Averaged over all model layers and entire global atmosphere. % contribution of different observations to reduction in forecast error.


1) Sounders on Polar Satellites reduce forecast error most

2) Results are relevant for other NWP Centers, including NWS/NCEP

Forecast error contribution (%)

Courtesy: Carla Cardinali

and Sean Healy, ECMWF