Overview

1

Overview of The Environmental

Modeling Center

Stephen J. LordDirector

NCEP Environmental Modeling Center

NCEP

2

Overview

• EMC Organization

• Scientific highlights– Weather Research & Forecast (WRF)

System– Hurricane Forecasting – Real-time Ocean Forecasting – Global Coupled Climate Forecast System– The NASA-NOAA-DOD Joint Center for Satellite

Data Assimilation

• Summary

3

EMC Mission In response to operational requirements:

• Maintain– The scientific correctness and integrity of operational

forecast modeling systems– Modify current operational system to adapt to ever-

present external changes

• Enhance numerical forecasts– Test and improve NCEP’s forecast model systems via

• Scientific upgrades• Tuning• Additional observations

• Transition and Develop operational numerical forecast models from research to operations

– Transform & integrate • Code• Algorithms• Techniques

– Manages and executes transition process including• Government technical and system performance review

before implementation EMC

4

NCEP Mission Requirements & Forecast Suite Elements

NCEP

UKMO

National Centers forEnvironmental

Prediction

United KingdomMeteorological Office

European Centre for Medium Range Weather

ForecastingECMWF

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X

X

X

X

X X X X X X

X X X

NCEP only

NCEP and UKMO

NCEP, UKMO and ECMWF

5

The Environmental Forecast Process

Observations

Analysis

Model Forecast

Post-processed Model Data

Forecaster

User (public, industry…)

NumericalForecastSystem

Data Assimilation

6

Scientific Highlights

• Weather Research & Forecast (WRF) System

• Hurricane Forecasting • Real-time Ocean Forecasting • Global Coupled Climate Forecast

System• Data Assimilation and Global

Modeling (JCSDA, etc)

7

WRF at NCEP

• 21 September 2004: 8 km WRF

ARW & NMM into HiRes Window runs

• April 2004 to present: explicit 4.5 km

NMM runs for SPC/NSSL Spring Programs

• 28 June 2005: 5-6 km HiResWindow explicit runs

• November 2005: Added 6-member WRF

ensemble to SREF (6 = 3 ARW +3 NMM)

• June 2006: WRF-NMM and WRF-GSI

replaced Eta Model and its 3D-Var in

North American Mesoscale (NAM) runs

• December 2006: Major upgrade

8

Observed Composite Reflectivity

Courtesy Kain, Weiss & Bright

NMM4 ARW4

Circles denote locations of rotating updrafts where updraft helicity is at least 50 m2s-2

Spring Program 2007

9






10

NCEP’s Hurricane Forecast Guidance

• GFS – T382/64L – 3-D var– Vortex relocation– State of the science physics

• GFDL– Movable nested – Air-sea coupled– Inner nest

• 9 km/42L– Specialized vortex initialization, – Upgraded with some GFS physics (2003, 2004)

• HWRF added to GFDL in 2007

11

Aug. 16, 18z

24 hr48 hr72 hr

96 hr

120 hr

12

Strategic Approach:Strategic Approach:Hurricane-Wave-Ocean-Surge-Inundation Coupled Hurricane-Wave-Ocean-Surge-Inundation Coupled

ModelsModels

High resolution Coastal, Bay & Estuarine hydrodynamic model

Atmosphere/oceanic Boundary Layer

HYCOM3D ocean circulationmodelWAVEWATCH III

Spectral wave model

NOAH LSM

NOSland and coastal waters

NCEP/Environmental Modeling CenterAtmosphere- Ocean-Wave-Land

runoff

fluxes

wave fluxes

wave spectra

windsair temp. SST

currents

elevations currents3D salinities temperatures

other fluxes

surgeinundation

radiativefluxes

HWRF SYSTEM NMM hurricane atmosphere

HWRF/multi-model hi-res ensembles for adv. storm surge modelHWRF/multi-model hi-res ensembles for adv. storm surge model

13






14

Real Time Ocean Forecasting• Wave Modeling

– Global and Regional– Unified model approach– NOAA Wavewatch III

• Basin-scale Ocean Model (new system)• Sea Surface Temperature & Winds

– NCEP Ocean Prediction Center support• Gulfstream analysis & forecast

• Real-time Sea Ice products– Alaska Region support (fishing)

15

Multi-Grid Wave Modeling

Multi-grid wave model tentative resolutions in minutes for the parallel

implementation in FY2007-Q4.

Deep ocean model resolution dictated by GFS model

Higher coastal model resolution

Highest model resolution in areas of special

interest

Hurricane nests moving with storm(s) like GFDL

and HWRF

16

NCEP Real-Time Ocean Forecast System (RTOFS)Operational December 2005, upgraded June 2007

Chesapeake Bay

• 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 (with NOS) for shipping

– Water quality– Ecosystem and biogeochemical

prediction– Improved hurricane forecasts– Improved estimation of the

atmosphere state for global and regional forecasts

17

S1: Nowcast for 20070405

S2 Test: Nowcast for 20070405

Quality, Class 1: Surface Salinity map for S1 (left panel) and S2 Test (right panel) compared to surface salinity map near mouth of Mississippi based on conductivity sensors and current meters data (middle panel) collected from moorings near the

LATEX coast in 1982 (Estuaries, Wiseman & Kelly, 1994). The offshore salinity front is non-existent in S1. In S2 test, it is weaker than the one observed and is located

closer to the coast.

Freshwaternearshore

18






19

ClimateForecastSystem(CFS)

Ocean ModelMOMv3

quasi-global1ox1o (1/3o in tropics)

40 levels

Atmospheric ModelGFS (2003)

T6264 levels

Seasonal to Interannual Prediction at NCEP

GODAS3DVAR

XBTTAO etc

ArgoSalinity (syn.)

(TOPEX/Jason-1)

Reanalysis-23DVART62L28

update of theNCEP-NCAR R1

D. Behringer

20

21

Assimilating Argo Salinity

ADCP GODAS GODAS-A/S

In the east, assimilating Argo salinity reduces the bias at the surface and sharpens the profile below the thermocline at 110oW.

In the west, assimilating Argo salinity corrects the bias at the surface and the depth of the undercurrent core and captures the complex structure at 165oE.

Comparison with independent ADCP currents.

22

Impact of Increasing Ensemble SizeOctober IC Lead 1 (DJF)

Surface Temperature

Precipitation

5 members 10 members 15 members

23






24Five Order of Magnitude Increases in Satellite

Data Over Fifteen Years (2000-2015)

Cou

nt (

Mill

ions

)

Daily Satellite & Radar Observation

Count

20001990 2015

100 M obs

125 M obs

Level 2 Radar

210 M obs

Satellite Data Ingest

Re

ceived

Da

ta

Daily Percentage of Data

Ingested into ModelsS

ele

cted

Data

100%

7%

Assim

ilate

d Da

ta

1.0 B

17.3M6.6M2%

2008 Data

Received = All observations received operationally from providersSelected = Observations selected as suitable for useAssimilated = Observations actually used by models

1.0 B obs

2008

25

NASA-NOAA-DOD Joint Center for Satellite Data Assimilation

(JCSDA)– NOAA, NASA, DOD partnership– Mission

• Accelerate and improve the quantitative use of research and operational satellite data in weather and climate prediction models

– Current generation data– Prepare for next-generation (NPOESS, METOP,

research) instruments

– Supports applied research• Partners• University, Government and Commercial Labs

26

JCSDA Instrument and Radiative Transfer Development Projects 2008-09

• New observations (implemented 1 May)– COSMIC– AIRS (all FOV)

• New observations (testing)– Implemented 29 May 2007

• METOP AMSU, HSB, HIRS• GOES 1x1 FOV sounder radiances

– Implemented Fall 2007• JMA high density winds• SBUV-8

– Implemented Summer 2008• Windsat

• Observations under development– IASI – to be implemented January 2009– OMI, GOME– ASCAT – AMSR-E– SSM/IS– CHAMP

• New analysis variables– Constituent gas assimilation– Aerosols

• Improved radiative transfer– Surface emissivity models– Cloud absorption & reflection

• Data sets (albedo, vegetation, land type)– Unified land surface treatment (data assimilation, model)

METOP advanced

instruments

27

EMC-GMAO-STAR Code Managementfor Atmospheric Data Assimilation

Time

GMAO

EMC

* * EMC, GMAO System change Repository change

+ Repository Merger (new tag)

* * * * * * * *

* * * * * * *

Repository

1 3Accepted changes

2

GSI & CRTM supported

Process: similar to ECMWF & Météo-Francewho have annual code mergers

But, to promote collaboration, EMC and GMAO use same repository and mergers are more frequent (3 months)

Protocols1 – EMC, GMAO take (agreed-upon) merged

code from repository to begin work2 – EMC, GMAO incorporate developments into

repository3 – Code mergers, repository changes and

timing are NCEP’s decision

+ +

3 months

28

Summary• Increasingly interdisciplinary and integrated

forecast systems to support weather, water and S/I climate (e. g. WRF)

• Increased emphasis on– Advanced data assimilation– Ocean forecasting– S/I climate– Severe weather– Ensemble systems

• Transition of community research to operations at NCEP is accelerating– Advanced satellite data assimilation through the

JCSDA

29

ThanksQuestions?

30

GFS implementation – 1 May 2007

• GSI– Unify the NCEP 3DVAR assimilation system– Some performance metrics improved (but most

neutral)– Prepare for future analysis improvements (e.g.

S4DVAR)

• Add new observing systems • Change vertical coordinate to hybrid sigma-

pressure, reducing some upper air model errors• Modernize the radiation package• Increase output particularly for hydrology

31

Dynamics changes

• Hybrid sigma-pressure vertical coordinate– Model surface remain terrain-following in the

lower troposphere but become pure pressure surfaces in the stratosphere

– Reduces vertical advection errors and pressure-gradient calculation errors in the upper part of the model

– Data assimilation and physics done on hybrid sigma-pressure coordinate as well

32

Vertical coordinate comparison across North America

33

Final testing set

• Retrospective testing– 15 June 2005 to 5 November 2005

http://wwwt.emc.ncep.noaa.gov/gmb/para/paralog.2005tropics_retro_gsihybrid.html

– 31 July 2006 to 5 November 2006 http://wwwt.emc.ncep.noaa.gov/gmb/para/paralog.2006tropics_retro_gsihybrid.html

– 24 October 2006 to 5 February 2007 http://wwwt.emc.ncep.noaa.gov/gmb/para/paralog.200607winter_retro_gsihybrid.html

• Real-time parallel– NCO started January 2007; in fairly final form about

March 1, 2007 to presenthttp://wwwt.emc.ncep.noaa.gov/gmb/para/paralog.gsihybrid.html

34

GSI

35

2005-2006 Atlantic Season Average Track Error Using The Current Operational and New GFS

GFDL GFS

36

~5 day forecasts from the operational GFS (top left) and the hybrid/GSI GFS (top right) and verifying analysis (bottom) on 1 April 1200 UTC

ExampleOf 5 dayForecast

10 m windValid

1 April 2007NCEP

ParallelSystem

GSIAnalysis

ParallelForecast

OpsFcst

37

Adding TOPEX/Jason-1 satellite altimetry to NCEP GODAS

Larger correlations betweenGODAS and Altimeter data inIndian and Atlantic Oceans

Smaller RMS errors

No assimilateddata

In situ dataAssimilated(operational)

OperationalPlus altimeter

38

Assimilating Argo Salinity

ADCP GODAS GODAS-A/S

In the east, assimilating Argo salinity reduces the bias at the surface and sharpens the profile below the thermocline at 110oW.

In the west, assimilating Argo salinity corrects the bias at the surface and the depth of the undercurrent core and captures the complex structure at 165oE.

Comparison with independent ADCP currents.

39

Real-Time Ocean Forecast System Mission

• Now– Routine estimation of the ocean state [T, S, U, V, W, SSH].

• Daily 1 week forecast• Every 5 years

– Evaluation– Re-initialization

• Future– Downscaling support for water levels (with NOS)– Improve ocean interaction in (nested) sub-domains for hurricane

forecasts– Support estimates of chemical components (water quality) and

organisms distributions in the water (ecosystems)– Improved estimation of the atmosphere state

• In short term global forecast• In short term regional forecast

40

CURRENT RT-OFS Atlantic Description (S1)

• State variables: Temperature, Salinity, Velocity, Sea surface elevation.

• Primitive equation with free surface.• Horizontal grid: orthogonal, dx/dy~1• Open boundaries (climatology and tidal model)

• Sub-grid scale parameterizations. Vertical and horizontal eddy viscosity and mixing.

• Tides, river outflow (USGS, climatology)• Atmospheric fluxes (GDAS, GFS)

Dynamical Model Dynamical Model (HYCOM)(HYCOM)

41


• Data: – SST: AVHRR, GOES, In-situ

• 2DVAR with vertical projection.– SST: Time interpolated analysis values are nudged

during nowcast in the mixed layer.

Data Assimilation

42


Daily Operations and Product Distribution

• Once daily (4Z)– Nowcast 1 day– Forecast 5 days

• Grib files for nowcast and forecast– Hourly surface T,S,U,V, SSH, barotropic velocity,

mixed layer depth– Daily T,S,U,V,W, SSH for 40 depths

• Product distribution– NCO servers (ftpprd)– NOMADS [sub-setting] (full data server functions)– MMAB Web server (ftp, graphics)

43

Updates (S2)• MODEL ALGORITHMS

– Surface initialized Montgomery Potential– Modify boundary condition, giving two invariant external modes– Stabilization of density function (T, p)– Enforced salinity minimum by refreshing the water column

• DATA ASSIMILATION ALGORITHM– SST: spatially varying bias removal algorithm– SSH

• Assimilation of absolute sea surface height• 2D variational sea surface height, with 1D vertical covariance of sea

surface height and layer thicknesses• Reset layer transports preserving momentum

– Temperature & Salinity• Assimilation of vertical profiles of temperature and salinity (ARGO &

CTD)• 2D variational of density, temperature and layer thickness

anomalies• Re-layering preserves volume, momentum; and updated mass and

heat

44

Updates (S2) DATA INPUTS:

• Revised vertical grid parameters:– 26 layers, with

• higher resolution in the shallow waters• better resolution on the shelf break• better representation of Denmark & Iceland overflows• resolving 4 vertical dynamical modes in major sub-basins

• Improved barotropic / baroclinic inputs at open boundaries– Updated Climatology (NCEP – version 6)– Mean dynamic topography (Rio 5)– Historical transports

• Revised river inflow data (location and strength) from USGS

• Remove noise in net heat flux

45

GFS+GOCART Offline System

• GFS – NCEP/EMC Global Forecast System

• GOCART– NASA Goddard Global Ozone Chemistry Aerosol

Radiation and Transport Model

• Steps– (1) dust modeling– (2) aerosol modeling

• Work with NRL (NAAPS)

46

Jung and Zapotocny

JCSDAFunded by

NPOESS IPO

Satellite data ~ 10-15% impact

Impact of Removing AMSU, HIRS, GOES Wind, Quikscat Surface Wind Data on Hurricane Track Forecasts in the Atlantic Basin - 2003 (34 cases)

-20.0

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

12 24 36 48 72 96 120

Forecast Hour

% Im

prov

emen

t NOAMSU

NOHIRS

NOGOESW

NOQuikscat

Impact of Removing AMSU, HIRS, GOES Wind, Quikscat Surface Wind Data on Hurricane Track Forecasts in the East Pacific Basin - 2003 (24 cases)

-60.0

-50.0

-40.0

-30.0

-20.0

-10.0

0.0

10.0

20.0

30.0

12 24 36 48 72

Forecast Hour

% Im

pro

vem

ent

NOAMSU

NOHIRS

NOGOESW

NOQuikscat

47

Aug. 19, 06Z

24hr

48hr

72hr

96hr120hr

Aug. 21, 00Z & Aug. 21, 12Z

48

NWW3 Data Assimilation and Future Upgrades

• Altimeter data assimilation (above)

• 2 way nesting

• Coastal applications

• Hurricane (moveable nests)

• Affordable ensemble forecasting

• Improved wave-wave interactions

• Parameterized with neural network

49

MMAB Ice Products

Present 25.4 km ResolutionNear Future 12.7 km Resolution

Future Concentration Model Ice Thickness Model

Sea Ice Concentration

50

The Gulf Stream Wind speed (Knots) 65 50 35 30 25 20

Sea Surface Temperature QuikSCAT Winds

SST-dependent wind speed difference across the North Wall of the Gulf Stream Gulf Stream Waters – 30 to 40 kt Cooler Slope Waters – 15 to 25 kt

Slope Waters

Gulf Stream

North Wall

Warm ring Warm ring

North Wall

51

52

Increased Use of POES Radiances with Improved Surface Emissivity

ModelAMSU-A Data Used Northern Hemisphere

0

1000

2000

3000

4000

5000

6000

7000

1 2 3 4 5 6 15 Total

Channel

OperationalImproved emissivity

AMSU-A Data Used Southern Hemisphere

0

1000

2000

3000

4000

5000

6000

7000

8000

1 2 3 4 5 6 15 Total

Channel

OperationalImproved emissivity

53

Ongoing work – GSIUse of observations

• GPS radio-occultation– Preparation for COSMIC well advanced– Local Refractivities done– Local Bending angle next– QC most significant problem

• Radiances– New data– Improved Radiative Transfer– Improved techniques including scattering and

absorption from clouds in microwave

54

GSI Overview (cont)

• Code re-designed for community use– Currently 38 registered groups/users– NCEP providing some support for external

groups

• Major focus of NCEP and NASA/GSFC/GMAO atmospheric analysis development– Multi-organizational code management

• Re-structuring for ESMF compatibility (underway)

55

GSI Overview (cont)• New features (implemented)

– Spatial derivatives – allows:• non-local operators• improved definition of balance operators• dynamical balance constraints

– Improved control over observational errors– Improved moisture analysis variable – Diagnostic files for background and each outer iteration

• New features (under testing)– Variational QC (global)– Variational bias correction for conventional data– SST analysis by direct use of radiances (global)

• IR and MW data– Simplified 4DVAR (global)– Situation dependent background error (RTMA, regional)

56

Data Assimilation Development Strategy (cont)

• Yearly upgrades of S4DVAR & SDBE from NCEP/EMC will– Result in improved analysis capability– Set the bar and provide risk reduction for other work

• C4DV + EnsDA – 2007-2008

• Prototype development– 2008

• Full parallel testing• Transition decision (between 3 candidates)

– 2009-2010 (if warranted)• Pre-implementation testing• Operational implementation

57

Ongoing work – Simplified 4DVAR

• Adiabatic time derivatives– Filtered to retain “slow” modes– Used to extrapolate state to obs times– Captures obs time changes due to slow

modes

• No additional cost since calculations already included in constraint term

58

First S4DVAR Results

S4DVAR

No S4DVAR

RMS Fits to Surface Pressure

59

First S4DVAR Results (cont)

S4DVAR

S4DVAR

SH

60

Data Assimilation Development Strategy

• Three closely related efforts1. Develop Simplified 4D-Var (S4DVAR) and Situation-Dependent

Background Errors (SDBE) 2. “Classical” 4D-Var (C4DV)3. Ensemble Data Assimilation (EnsDA)

• Partners– NCEP/EMC– NASA/GSFC/GMAO– THORPEX consortium – NOAA/ESRL

• CIRES• U. Maryland• U. Washington• NCAR

61

Environmental Modeling CenterDirector

Deputy DirectorTeam Leaders

Administrative Staff----------------------------

11

Marine Modeling& Analysis Branch

--------------------9

Mesoscale ModelingBranch

-------------------9

Global Climate & WeatherModeling Branch

--------------------------18

EMC Contractors-----------------------------

81EMC Visiting Scientists-----------------------------

11

Science CommunityUniversities

NOAA Labs & OGPNASANCAR

World NWP CentersFAA

JCSDATest Beds

62

CoupledRed: monthly bias

Observed

Simulation of El Nino & La Nina Events withNCEP’s Coupled Forecast System (CFS)

63

Weather Research and Forecast (WRF) Modeling System

Promote closer ties between research and operations

Develop an advanced mesoscale forecast and assimilation system

Concept:

Design for 1-10 km horizontal grids

Portable and efficient on parallel computers

Well suited for a broad range of applications

Community model with direct path to operations

Collaborators: NCEP/EMC, NCAR, AFWA, Navy, NOAA/FSL, U. Okla.

Overview

Documents

global modeling jcsda

nceps forecast model

wrf arw nmm

operational requirements

member wrf ensemble

eta model

dod joint center

system performance review