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Douglas Westphal Anthony Bucholtz
Piotr FlatauArunas Kuciauskas
Ming LiuBetsy Reid
Jeffrey ReidKim RichardsonAnnette Walker
Aerosol and Radiation Modeling SectionMarine Meteorology DivisionNaval Research Laboratory
Monterey CA 93943
www.nrlmry.navy.mil/aerosol
Overview of Navy’s System for Global Modeling of Sulfate, Smoke & Dust
Conventional Navy view:•Marine aerosol (salt, sulfate) in marine boundary layer•Locally produced•EO propagation, TAWS, slant range visibility
But there are other aerosols and impacts:•Dust, smoke, pollution •Long-range transport•Operational constraints
–mission planning–hazard avoidance–navigation
•Numerical weather prediction–direct effect–indirect effect
•Satellite analyses–SST retrievals
Why?Aerosol Impacts on Navy Activities
Dust Over the Red Sea, 18 July, 1999
Mediterranean, 15 April, 2000Impact of Aerosols on Navy Activities
Southwest Asia, 10 October, 2001
Southwest Asia, 12 October, 2001
Pollution and Smoke over the Atlantic
June 28, 2001SeaWiFS
Impact of Aerosols on Navy Activities:Volcanic Ash in the Mediterranean
October 28, 2002SeaWiFS
“… helicopters encountered … several large layers of suspended dust about 190 nm long. Like flying in a milk bowl … pilots unable to see the surface from as low as 75 feet.” NDU staff report on Iran Hostage Rescue Mission
“After sunrise the visibility reduced to less than 1 nautical mile in blowing dust, prompting all squadrons to immediately begin preserving topside aircraft. … the harbor pilot was told that visibility was down to less than ¼ mile at the harbor and that no traffic would be moved until the visibility improved.” USS Carl Vinson, U.A.E, February 1999
“The ability to have DAMPS generate a dust forecast out to 48 hrs would provide us with an ability to reschedule flight operations or move ships to other locations. In the eleven months I’ve been out here, dust has had the biggest impact on limiting and/or canceling operations that have taken place in this AOR.” CO NAVCENTMETOCCEN, Bahrain, July 2000
At Roosevelt Roads/Vieques, Puerto Rico, drone operations over practice ranges were cancelled by conditions of reduced visibility due to Saharan dust; interfered with gunnery training schedules (couldn’t visually certify range was clear)
Impact of Dust on Navy Activities
Impact of Aerosol on Navy Activities
Aerosol climatology required for selection of High Energy LasersFocused on marine boundary layer (for ship defense)
Impact of Aerosols on NWP:Example of Visible Direct Effect
•SEAWIFS Visible wavelength imagery for March 17, 2002
•Plume of aerosol leaving Asia composed of dust, pollution and other aerosols
•Direct effects are obvious
•Indirect effects are possible as aerosol is entrained into synoptic weather system
KOREA
ACE-Asia Experiment, April 2001• Shipboard deployment• Sea of Japan (subject to dust
storms from China)• Main result: increased downward
infrared flux due to dust in atmosphere
Impact of Aerosols on NWP:Example of Infrared Direct Effect
Infr
ared
per
turb
atio
n (W
/m**
2)
Impact of Aerosols on NWP:Example of Indirect Effect
AVHRR Near-IR imagery for May 14, 1994, from MAST
“Ship tracks” are variations in cloud albedo due to aerosol-induced changes in cloud properties
Large-scale changes in cloud albedo likely due to polluted vs. clean air
Large-Scale Albedo Change
Ship Tracks
Impact of Aerosols on NWP:Indirect Effect on Hurricane Felix?
(El Niño) Dust Contamination Smoke Effect
Cummings/FNMOC
Impact of Aerosols on NWP:Aerosol Contamination of SST Retrieval
Why Global?Long-Range Transport
Often assumed that aerosol is locally produced and can be modeled based on local variables, ignoring long-range transport
However,
•Intercontinental aerosol transport occurs frequently•Regional aerosols can be significantly impacted by non-local sources
Other reasons for global modeling:
•Regional aerosol simulations require initial and boundary conditions•Validation data are scarce; validate model wherever data are available
Intercontinental Transport
Background: Composite of Several Retrievals of TOMS Absorbing Aerosol Index
Dust: Red Arrows, Smoke: Blue Arrows Background: Composite of several TOMS retrievals of Aerosol
Index
Intercontinental Transport
Objectives:
•Forecast global and regional distribution of aerosols •Measure and model the optical effects of aerosols•Forecast slant range visibility•Determine the importance of aerosol effects for NWP
Approach:
•Modeling•Global and regional predictive aerosol transport models with emphasis on dynamical forcing and transport, rather than microphysics and chemistry•Data assimilation of satellite data
•Theoretical•Calculate scattering by individual particles•Develop accurate and efficient forward modeling methods for NWP
•Experimental•Verify theoretical calculations using in situ and remotely sensed data•Validate transport models with in situ and satellite data
Aerosol Research at NRL/MRY
RegionalAerosol ModelCOAMPS
NCB Models
ObservationsRemote Sensing
Global and RegionalAerosol Analyses
GlobalAerosol Model
NOGAPS
Theoretical Studies, Field Measurements
NRL/MRY Aerosol Studies FlowchartE
xten
dkn
owle
dge
base
Impl
emen
t ex
istin
g kn
owle
dge
•Customers: TAWS (slant range) NAVO (SST) Metoc Det (Wx) HEL (visibility)•Validation
Transition tocustomer
• Twice-daily, 5-day forecasts of SO2, sulfate, dust and smoke
• Operational global weather model (NOGAPS) provides forecasts of P, T, q, u, v, w, Kz, cloud parameters, precip., stress, and ground wetness at 6-hour intervals on 1X1 degree grid; 14 levels to 100 mb
• Semi-Lagrangian horizontal transport; finite element horizontal diffusion; finite element vertical transport
• SO2 emission from GEIA inventory; oceanic DMS emission
• Deflation depends on threshold velocity, forecasted stress and ground wetness
• Smoke emission based on satellite detection of fires• Linear gas-phase chemistry• Dry deposition: function of specie, stress, stability, surface type• Wet removal: function of precipitation rate, specie, cloud type
*Modified DEHM model (Christensen, Atm. Env., 1998)
Global Aerosol Model
November 27 NAAPS 5-day Forecast for December 2, 2002
Total Optical Depth
Dust Optical Depth
Sulfate Optical Depth
Smoke Optical Depth
Analysis using NAAPS: JFK Jr. Study(collab. with Prospero@ U. Miami, Poirot@
Vermont)
Real-Time NAAPS analyses allowed rapid response to crash:– Determined atmospheric structure: deep continental
boundary layer above shallow MBL – Detected exceptional pollution event: high sulfate
concentrations– Results used in NTSB report
Research mode:– Validated with surface chemistry and satellite data– Compared NAAPS emissions inventory to current
emissions– Diagnosed impact of uncontrolled Midwestern
emissions on air quality of East Coast and New England
JFK Jr. Study:Accurate simulation of timing and location of anthropogenic
aerosol plume
SeaWiFS Imagery, 1620Z 16 July, 1999 NAAPS AOD, 1800Z 16 July, 1999
JFK Jr. Study:Environmental conditions analyzed using NAAPS and NOGAPS
JFK Jr. Study
Findings:
•Need to add other anthropogenic aerosols to NAAPS in order to quantify visibility/extinction
•JFK Jr. study shows GEIA dataset is outdated: some current sources greater than GEIA values; others less
•Conversion rates need modification (high ozone conc. increases rate of conversion to sulfate)
•Uncontrolled Midwestern emissions responsible for most of the haze
NAAPS Smoke Source:Global Fire Detection
• Wildfire-ABBA uses GOES data to provide western hemisphere fires
• Global MODIS fire product used for other regions
GOES-8 Wildfire ABBA Summary Composite of Half-Hourly
Processed and Saturated Fire Pixel Observations for the Western
Hemisphere
Time Period: September 1, 2000 to August 31,
2001
GOES Visible Imagery14 UTC 10 August, 2000
NAAPS Smoke Optical Depth12 UTC 10 August, 2000
NAAPS Smoke Simulation, August 10, 2000
Smoke Plume
Comparison of NAAPS Optical Depth andSeaWiFS True Color For 20 June, 2001
NAAPS Simulation ofLos Alamos Smoke Plume, May 12, 2001
Smoke detected at DOE/ARMsite in Oklahoma May 11 and 12 first attributed to Los Alamos Fires
NAAPS shows smoke is a combination of two plumes:
•Transport of Los Alamos smoke in elevated dry layer
•Transport of Central American smoke in low-level moist layer
5/12 5/11 5/10 5/9
NOGAPS RH, winds, θ
NAAPS Dust Source Specification
USGS Landuse database (1 km resolution) used to identify erodible regions of the world (based on AVHRR data)
TOMS Aerosol Index (AI) used to further refine source regions over Sahara and Middle East; needs further refinement over Asia
NOGAPS soil moisture must be less than 0.3
NOGAPS surface stress must exceed a threshold value
Then dust flux is proportional to square of stress
NAAPS Dust Erodibility Specification:Based on USGS Landuse and TOMS/AI
Dust emission allowed in proportion to the square of the stress in these areas when stress exceeds critical value and soil
moisture is less than 0.3
0.4
0.1
0.1
0.1
0.3
NAAPS
AERONET Data
Validation of NAAPS UsingSeaWiFS and AERONET Data, Oct. 30, 2001
NAAPS Dust Optical DepthSeaWiFS True Color
Dust Plume
Comparison of TOMS AI and NAAPS Optical Depth for April 1998
Event
April 20
April 22
April 24
April 26
Green - dust, Red - sulfate aerosol
Validation of NAAPS Simulation of Asian Dust Event
Comparison of San Nicolas AERONET Sunphotometer and NAAPS Optical Depth for April 1998 Event: Captures timing, misses
background aerosol
UNIV. UTAH LIDAR 00Z 25 APRIL 1998
LIDAR
7.5 KM
NAAPS
Pre
ssur
e (m
b)
Concentration
Backscatter Depolarization
7.9 KM
The ‘Perfect Dust Storm’, April 6-9, 2001
Large dust storm on April 6-7, 2001, then swept across East Asia, the Pacific, and N. America
Visibility reduced to 100 m in some Chinese cities
Coincided with large international field program – ACE-Asia; provides additional data for validation
Baicheng, Jilin Prov., April 7, 2001
Baicheng, Jilin Prov., April 8, 2001
SeaWiFS April 7, 2001
NAAPS Dust Forecast, April 10, 12 2001
SeaWiFS Imagery11 April 2001
NAAPS Dust Optical DepthApril 11, 2001
NAAPS Dust Simulation, April 11, 2001
Dust Plume
SeaWiFS ImageryApril 19, 2001
NAAPS Dust Optical DepthApril 19, 2001
NAAPS Dust Simulation, April 19, 2001
Dust Plume
NAAPS ACE-Asia Simulations, April 2001
0.0
0.5
1.0
1.5
2.0
Angs
trom
Expo
nent
()
0.0
0.2
0.4
0.6
AOD
CIMEL (500 nm) NAAPS Sulphate NAAPS Dust NAAPS Smoke NAAPS Total
-10
0
10
20 Saturna Island
TOMS
Aero
sol In
dex
Rogers Dry Lake
Missoula
Saturna Island Rogers Dry Lake Missoula
TO
MS
AI
AO
DA
ngst
rom
Exp
.
SeaWiFS Study:Pixels Grouped According to NAAPS Simulation
SeaWiFS Study:Retrieval Fails for Aged Asian Dust Case
Future Plans
• Update source specification– Smoke (NASA FLAMBE)
• Add biome and seasonal dependence• Apply persistence check to Wildfire-ABBA• Use MODIS for detection outside of W. Hemisphere
– Update GEIA sulfur dioxide sources– Add salt and black carbon components
• Analysis and simulation– Develop transition path for use in screening for SST retrievals– Assimilate satellite retrievals of aerosol properties– Mesoscale generation Global transport Mesoscale impact
• Have developed mesoscale dust model, triply nested: 9, 27, an 81-km resolution
• Working on mesoscale source inventory to drive mesoscale dust model
– Continue validation using PRIDE, ACE/Asia, and other data– Initiate aerosol monitoring at MRY including IOP: ADAM