Second GALION workshop, WMO, Geneva 20-23 Aerosol Lidar Observations: A Missing Component Of Near-Real-Time Data Assimilation Requirements for Weather and Air Quality Models S. Nickovic and L. Barrie WMO Research Department, Geneva G. Pejanovic, A. Vukovic, M. Vujadinovic, M. Dacic SEEVCCC, Met Service, Serbia L. Mona and G. Pappalardo CNR-IMAA, Potenza F. Russo ISAC, Bologna
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Second GALION workshop, WMO, Geneva 20-23 September 2010 Aerosol Lidar Observations: A Missing Component Of Near-Real-Time Data Assimilation Requirements.
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Second GALION workshop, WMO, Geneva 20-23 September 2010
Aerosol Lidar Observations: A Missing Component Of Near-Real-Time Data Assimilation
Requirements for Weather and Air Quality Models
S. Nickovic and L. BarrieWMO Research Department, Geneva
G. Pejanovic, A. Vukovic, M. Vujadinovic, M. Dacic SEEVCCC, Met Service, Serbia
L. Mona and G. Pappalardo CNR-IMAA, Potenza
F. RussoISAC, Bologna
Current Pre-operational Assimilation SystemsUS Navy (NAAPS aerosol model)
- operational- satellite (MODIS, etc)- global
GEMS/ECMWF aerosol model - operational- MODIS- global
Met Service (Serbia) DREAM model - operational- ECMWF objective analysis of dust (MODIS)- regional
Meteorological Research Institute (Japan) aerosol model - research- CALIPSO- global
Second GALION workshop, WMO, Geneva 20-23 September 2010
• None of the pre-operational systems use vertical profile observations
• Only the Japanese experimental system uses CALIPSO for reconstructing the vertical structure;
• The frequency of observation by CALIPSO is insufficient for routine assimilation
Second GALION workshop, WMO, Geneva 20-23 September 2010
NAAPS AOD (no assimilation)
NAAPS AOD(w/ assimilation)
1) Convert NAAPS mass concentration to aerosol optical depth
2) Two-D variational assimilation of the optical depth field (MODIS etc)
3) Convert optical depth to NAAPS three-D mass concentration
NAAPS Data Assimilation Methodology
AERONET versus NAAPS
(January –May 2006)
Zhang, J., J. S. Reid, D. L. Westphal, N. L. Baker, and E. J. Hyer, 2008, A system for operational aerosol optical depth data assimilation over global oceans, J. Geophys. Res., 113, doi:10.1029/2007JD009065.
without AOD assimilation
with AOD assimilation
Second GALION workshop, WMO, Geneva 20-23 September 2010
GEMS/ECMWF 4-D Variation Assimilation System
• Prognostic variables (mass concentrations):– 3 bins for dust– 3 bins for sea salt– Organic matter– Black carbon– Sulphate
Early Attempts (2002) at Assimilation of EARLINET Lidar Data in DREAM (I)
Second GALION workshop, WMO, Geneva 20-23 September 2010
∂C∂ t+K t,z C−C =0
Third Step
Assimilate lidar profiles by applying Newtonian relaxation (nudging) method :
C – concentration
C* - target concentration
K – nudging coefficient; increases with relaxing time; has max at 3.5 km
Early Attempts (2002) at Assimilation of EARLINET Lidar Data in DREAM (II)
Concentration (g/m^3) at 2 km Height
13 October 2002 at 0000 UTC
NO ASSIMILATION ASSIMILATION
Second GALION workshop, WMO, Geneva 20-23 September 2010
DIFFERENCE: (ASSIM-NOASSIM)
2 km concentration (g/m^3)
Second GALION workshop, WMO, Geneva 20-23 September 2010
Model validation against lidar observations
A systematic comparison between DREAM model and lidar observations is currently in progress
Among all EARLINET stations, the Potenza station was selected as the one with the largest database of Saharan dust observations to develop a methodology for the comparison.
Comparison for May 2000 – April 2005 period between lidar observations and DREAM forecasts over Potenza.
Comparison procedure taking into account different temporal and vertical resolution has been developed.
Second GALION workshop, WMO, Geneva 20-23 September 2010
Comparisons in terms of:
Geometrical properties base, top and center of mass of layers identified layers above the PBL
Extensive properties mean backscatter and extinction for lidar profiles
mean concentration for DREAM profiles
Integrated backscatter and optical depth for lidar profiles aerosol load for DREAM profiles
Profiles mean (and variability) of profiles of extinction and backscatter for Lidar
mean concentration (and its variability) profile for DREAM
correlation coefficient for each identified case between extinction (or backscatter) and concentration in the identified layer
2
4
6
8
10
0.0 5.0x10-5 1.0x10-4 1.5x10-4
0 20 40 60 80
Aerosol Concentration [ g m-3]
Aerosol Extinction Coefficient @ 355 nm
[m-1]A
ltit
ud
e a.
s.l.
[km
]
Second GALION workshop, WMO, Geneva 20-23 September 2010
Proposed conversions: lidar parameters to model concentrations
The first step for lidar data assimilation is the conversion of concentration into lidar measured optical quantities (like aerosol extinction). The BOLCHEM group at ISAC/CNR in Bologna started to work on these conversions.
BOLCHEM is a coupled meteorology-chemistry model.
• Meteorology is based on BOLAM (Bologna Limited Area Model) developed at ISAC-CNR by the Dynamic Meteorology group.
• Modelling of aerosols is in a test phase and is supported by the atmospheric chemistry group.
BOLCHEM interest in aerosol is due to:
• Implementation of the aerosol feedback on radiation.
• Aerosol optical depth validation by comparison with MODIS.
Second GALION workshop, WMO, Geneva 20-23 September 2010
AOD computation from BOLCHEMIndividual aerosol species:
• SO4, organic, black carbon, sea salt, NH4, NO3.
Example of monthly averaged total aerosol optical depthin the Po Valley
Sulfate component
Sea salt component
Second GALION workshop, WMO, Geneva 20-23 September 2010
Possible Way Forward For Near-Real-Time Data Delivery And Data Assimilation Of GALION
Observations • WMO frameworks in support of such approach:
– WIS– GAW supported integrated global aerosol observing and analysis
system (GALION, AOD consortium, surface in situ consortium, IAGOS partners, satellite partners) www.wmo.int/gaw
– Sand and Dust Storm Warning and Advisory System(SDS-WAS) www.wmo.int/sdswas
• Proposed GALION data exchange concept– Time frequency: 3 hours (alternative, 6 hours)– Vertical resolution: 100m– Delivery triggering: as indicated by aerosol models (e.g. EARLINET
stations may operate according to routine dust forecasts) – Format: WMO/WIS BUFER or CIREX– Data quality level: not controlled– Extend GALION network form a core of sophisticated research
based stations to include stations operating with relative cheap Lidar equipment (so that met services, airports and/or environment agencies could perform observation operations)