Charles E. Skupniewicz 1 Torsten Duffy 1 Douglas L. Westphal 2 Cynthia A. Curtis 2 Ming Liu 2

Charles E. Skupniewicz1 Torsten Duffy1

Douglas L. Westphal2Cynthia A. Curtis2

Ming Liu2

1 Operations Department, Fleet Numerical Meteorology and Oceanography Center Monterey, California, USA2 Marine Meteorology Division, Naval Research Laboratory Monterey, California, USA

Fleet Numerical Meteorology & Oceanography Center

FNMOC Operational Aerosol Modeling and Derived Products

23WAP/19NWPJune 2009

Fleet Numerical…Supercomputing Excellence for Fleet Safety and Warfighter Decision Superiority…


2

GlobalGlobalModelModel

Aerosol Models

MesoscaleModels

EnsembleModels

Ocean Models

Tropical Cyclone Forecasts

Optimum TrackShip Routing

Automated High Seas / Wind Warnings

Ballistic Wind Computations

Electro-Optical Forecasts

Aircraft RoutingOcean Acoustic

Forecasting

Long-Range Planning

Ice Forecasts

Target WeaponSystems

Visibility/DustForecasts

WRIP

CEEMS

Search and Rescue

FNMOC Models and Applications


Chinese Dust and Korean Smoke, 8 April, 2000Impact of Aerosol Plumes on Navy Activities

Korea


Climate Approach: Utilize first principles • Concerned with climate change and drift• Low-resolution weather• Theoretically based• Trace gasses, chemistry • Aerosol direct, indirect, and semi-direct effects• Produce monthly or seasonal averages of column integrated properties, e.g. AOD • Derive sensitivities

Navy Forecasting Approach: Pragmatic• Concerned with onset and cessation of events • High-resolution weather• More diagnostic and empirically based• Aerosol direct effects• Produce instantaneous forecasts of visibility• Surface-centric

Navy Aerosol Modeling: Different Goals / Different Approaches


Navy Aerosol Forecasting Approach

- Predict events as weather phenomena emphasizing sources and transport

- Simulate aerosols that impact visibility: dust smoke sea salt sulfate

- Develop operational capability (practical)

- Utilize real-time data streams

- Use nested models to cover the large range of scales


NAAPS: Navy Aerosol Analysis and Prediction System

Purpose: Forecasts aerosol concentrationsStatus: Operational, 4X dayInput: NOGAPS, dust source DB, FLAMBE (smoke),

MODIS Aerosol Optical Depth (AOD)Species: Dust, Smoke, Sulfate, SO2, Sea salt

Units: Mass concentrationHorizontal resolution: 1 degree, 360 X 180 gridVertical resolution: 20 m, 200 m inc. to 2 km, 1 km inc. to 16 kmOutput Filter: FAROP (Forecast of Aerosol Radiative and Optical Properties)

Output: Visibility, AOD, extinction, scattering, asymmetry parameter, phase function, species partition for extinction

Distribution: Ocean data analysis (SST), tactical decision aids,

forecaster web products, customer download (GRIB)

2007, Witek, M. L., P. J. Flatau, P. K. Quinn, and D. L. Westphal, Global sea-salt modeling: Results and validation against multicampaign shipboard measurements, J. Geophys. Res., 112, D08215, doi:10.1029/2006JD007779.


6 May, 2003

FLAMBE: Fire Locating and Modeling of Burning Emissions

Purpose: Determine real-time smoke fluxesInput: GOES, MODISOutput: Fire parameters: Location (lat, lon) Smoke flux, g m -2 s -1

Horizontal res.:GOES: 4 km; MODIS: 1 km Temporal res.: GOES: 30 min., MODIS: 2X Day

Next step: use foreign geostationary satellites

Fire detections for 2006092012

2004, Reid, J. S., E. M. Prins, D. L. Westphal, C. C. Schmidt, K. A. Richardson, S. A. Christopher, T. F. Eck, E. A. Reid, C. A. Curtis, and J. P. Hoffman: Real-time monitoring of South American smoke particle emissions and transport using a coupled remote sensing/box-model approach, Geophys. Res. Lett., 31, L06107, doi:10.1029/2003GL018845.

MODIS Fires, 3 May ,2003 Smoke Flux, 3 May, 2003


Version Area Data sources Status NAAPS Global USGS FY99NAAPS Global USGS, TOMS AI, and surface wx reports FY00

DSD v0.1 East Asia USGS, maps, reports, and sfc. wx. reports FY04DSD v1.1 East Asia DSD including DEP 4Q FY09

DSD v1.2 SW Asia DSD including DEP FY03DSD v1.2.8 SW Asia Updates based on field reports and DEP FY08 DSD v1.3 N. Africa DSD including DEP FY10

DSD v0.1 DSD v1.1

Dust Source Database (DSD)


NAVDAS-AOD: NRL Atmospheric Variational Data Assimilation System – Aerosol Optical Depth

Purpose: Data assimilation for aerosol optical depth (3-d Var)

Status: Operational 3Q09, 4x daily

Input: NRL Level 3 MODIS Over-Ocean AOD (6-h data window) Next step: Over-land and CALIPSO

Future input: NPP, NPOESS, AVHRR, MetOp, MSG, MTSAT, AATSR, GOES-R

Output: Aerosol analysis and: 3-d distribution of four species error statistics Temporal resolution: 3 hourly Distribution: NAAPS and FAROP; web

2008, Zhang, J., J. S. Reid, D. L. Westphal, N. L. Baker, and E. J. Hyer, A system for operational aerosol optical depth data assimilation over global oceans, J. Geophys. Res., 113, doi:10.1029/2007JD009065.


Data Assimilation Methodology

Next step: 4D-VAR

r =.83r =.69

NA

AP

S

MODIS MODIS

NAAPS AOD (no assimilation)

NAAPS AOD(w/ assimilation)

1) Convert NAAPS massconcentration to aerosol optical depth

2) Two-D variational assimilation of the optical depth field

3) Convert optical depth to NAAPS three-D mass concentration(ill-posed; simple conditional scaling scheme used)


NAAPS Validation against AERONET

• (a) AERONET versus NAAPS for 5-month (January –May 2006) NAAPS without data assimilation

• (b) AERONET versus NAAPS for 5-month (January–May 2006) NAAPS run with AOD assimilation

2008, Zhang, J., J. S. Reid, D. L. Westphal, N. L. Baker, and E. J. Hyer, A system for operational aerosol optical depth data assimilation over global oceans, J. Geophys. Res., 113, doi:10.1029/2007JD009065.


Opt

ical

Dep

th →

Current Real-Time Verification of NAAPS

Sede Boker, Israel, February 13 – March 4, 2007


FAROP: Forecast of Aerosol Radiative and Optical Properties

Purpose: Calculates Optical PropertiesStatus: Operational, 4X dayInput: NOGAPS, NAAPS

Physics Extinction: Mass extinction efficiencies

with RH effects for sulfate, smoke, and saltScattering: Mass scattering efficiencies Asymmetry parameter: Measurements and theoryPhase function: Heney-Greenstein function Optical depth: Vertical integral of extinctionSlant path range: Contrast transmittanceOutput3D: visibility, extinction (km-1), scattering (km-1),

asymmetry parameter, phase function, species partition for extinction on pressure/flight levels

Column: AOD (visible) for each species Frequencies: 19 wavelengths, 5 bands in UV, Vis, NIR, MWR and IR

Work in progress: performance surfaces - slant path visual range (nm)

0 3 6 9 12 15 18 21 24 271000

900

500

200

0.000

0.004

0.008

0.012

Extinction (1/km)

Forecast Time Pressure (mb)

1 .06 µm Extinction


NAAPS Forecast Example

14

February 2007 Optical Depth


Surface Visibility Example


MCSST Screening with NAAPS


Tactical Mission Support

Thermal Crossover Times / Polarity(for multiple targets)

Extinction, scattering, asymmetry parameter, phase function, species partitioning used to calculate slant path transmissivity, as a function of

- Altitude /Sensor/Target- Field Of View

- Probability of Detection

Detection Ranges / Best Attack Axis

( FOVs)

Uses realistictarget models andbackgrounds


MODIS DEP 0634 UTC 10 October, 2001

COAMPS 31-h forecast of dust mass load (µg m-2)

0700 UTC 10 October, 2001

DSD allows prediction of individual plumes

Regional Model (COAMPS) Dust Example


FNMOC Operational Aerosol Modeling and Derived Products

Questions?

Charles E. Skupniewicz 1 Torsten Duffy 1 Douglas L. Westphal 2 Cynthia A. Curtis 2 Ming Liu 2

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