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Transcript of Algorithms and chemical data assimilation activities at Environment Canada Chris McLinden Air...
Algorithms and chemical data assimilation activities at Environment Canada
Chris McLindenAir Quality Research Division, Environment Canada
2nd TEMPO Science Team MeetingHampton, VA 21-22 May 2014
Retrievals over snow
• Fraction of OMI observations over snow (during ‘snow’ months November-March)
– Currently snow and cloud are difficult to distinguish and measurements over snow are less accurate; often these data are not used poor sampling in winter
– Improving retrievals would greatly improve monitoring capabilities
-140 -120 -100 -80 -6025
30
35
40
45
50
55
60
65
70
0
0.2
0.4
0.6
0.8
1
Fraction
Snow Cover
• Best products
IMS (Interactive multi-sensor) CMC CaLDAS (Cdn. Land Data Assimilation System)
Provider NOAA/NESDIS Environment Canada / Canadian Meteorological Centre
Availability Near-real time Near-real time
Spatial Extent Northern Hemisphere North America / Global
Spatial resolution (current) 4 x 4 km2 10 x 10 km2 / 24 x 24 km2
Spatial resolution (future) 1 x 1 km2 2.5 x 2.5 km2 / 10 x 10 km2
(~2015/2016)
Temporal resolution Current: daily; future: 12-hour Current: 12-hour; future: 6 hour or better
Field provided Snow extent (yes / no) Snow depth*
Input information satellite imagery; derived mapped products; surface observations
CMC: analysis using surface observations and (simple) surface modelCaLDAS: Data assimilation of land-surface model, satellite imagery; surface observations
* Could be used to identify fresh snow
Snow reflectivity
• Surface very heterogeneous
• Current OMI retrievals: 0.6 everywhere
Longitude
Lat
itud
e
-112.5 -112 -111.5 -111 -110.556.4
56.6
56.8
57
57.2
57.4
57.6
57.8
Longitude
-112.5 -112 -111.5 -111 -110.5
Alb
edo
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
OMI (354 nm, 0.5, from O'Byrne et al., 2010 )
Fort McMurray
Fort McKay
2005Fort McMurray
Fort McKay
2011
MODIS (477 nm, 5 km from MOD43C3 product)
Reflectivity
• Temporal changes can be important
• This change if unaccounted for amounts to a +1-1.5%/yr change in NO2
2000-2001
0.01
0.02
0.03
0.04
0.05
0.06
0.072002-2004 2005-2007 2008-2010 2011-2012
MODIS reflectivity, summer average
Reflectivity
2011
DOMINO SCD - DOMINO AMF
56.4
56.6
56.8
57
57.2
57.4
57.6
DOMINO SCD - EC AMF
Latit
ude
SP SCD - SP AMF
56.4
56.6
56.8
57
57.2
57.4
57.6
SP SCD - EC AMF
VC
D [ 1
01
5 cm
-2]
0
0.5
1
1.5
2
2.5
3
3.5
4
NASA SCD - AMF=0.36
-112.5 -112 -111.5 -111 -110.556.4
56.6
56.8
57
57.2
57.4
57.6
Longitude
NASA SCD - EC AMF
-112.5 -112 -111.5 -111 -110.5
VC
D [
DU
]
-0.1
0
0.1
0.2
0.3
0.4
135 W
120 W
105 W 90
W 75
W
60 W
45 N
60 N
75 N
Original New EC
100% increase
40% increase
Reprocessing leads to significant increases in NO2 and SO2
- profiles from GEM-MACH- monthy-mean albedo from MODIS (snow, snow-free)- snow flagging from IMS
NO
2S
O2
McLinden et al., ACP, 2014
CIMELAerosol Optical Depth at 340 nm
Pandora 104SO2 Vertical Column Density in DU(1 DU = 2.69 x 1016 mol cm-2)
Pandora 104NO2 Vertical Column Density in mol cm-2
August 23is in black
Local Time
Different colours represent different days
Remote sensingInstruments (CIMEL and Pandora) at Fort McKay
5 pm
Local Time
from Vitali Fioletov, EC
NO
2S
O2
Aer
osol
opt
ical
dept
h
• Comparisons of NO2 total vertical column density
• OMI NO2 using recalculated AMFs consistently in better agreement
• One exception is Sept 16 where VCDOMI,trop < 0
220 230 240 250 260 270 280 2900
0.5
1
1.5
2x 10
16
Julian Day Number
NO
2 V
CD
[cm
-2]
PandoraOMI(EC)OMI(TEMIS)
Satellite Validation – OMI NO2
Sept 16?
OMI pixel
Wind direction
-114 -113 -112 -111 -110 -10955.5
56
56.5
57
57.5
58
58.5
NO2 : 04 Sep 2013 13:58 MDT
Longitude
Lat
itu
de
0
1
2
3
4
5
6
7
-114 -113 -112 -111 -110 -10955.5
56
56.5
57
57.5
58
58.5
NO2 : 04 Sep 2013 13:58 MDT
Longitude
Lat
itu
de
0
1
2
3
4
5
6
7
OMI GEM-MACH 2.5 km forecast
Comparison of OMI NO2 with GEM-MACH2.5 forecast; where GEM-MACH values have been averaged over the individual OMI pixels
Vertical C
olumn D
ensity (x1015 cm
-2)
Removal of the stratospheric NO2 signal
-150 -100 -5020
30
40
50
60
70
0
0.1
0.2
0.3
0.4
0.5
Annual mean, from OMI (2009)
• Fraction of total NO2 column in the troposhere
– Urban/Industrial areas: 30-80%; Rural/background areas: 10-30%– With most of Canada <25%, it is crucial to have an unbiased method for
removing stratospheric NO2
– With 20% in trop: a 10% high bias in strat-NO2 a 40% low bias in trop-NO2
Fraction
OMI VCD, relative to 2005;(DOMINO+SP)/2(DOMINO-SP)/2
Surface vmr, relative to 2005/06
DOMINO – SP difference up to 0.5 ppb (10%) at surface
Two year running means –DOMINO and SP NO2 using Env. Canada AMFs
OMI VCD, relative to 2005;(DOMINO+SP)/2(DOMINO-SP)/2
Surface vmr, relative to 2005/06
DOMINO – SP difference up to 1 ppb (30%) at surface
Two year running means –DOMINO and SP NO2 using Env. Canada AMFs
Operational objective analysisOperational objective analysis
experimental since 2003, operational Feb 2013
ozonefine particles
Curently 10 km (2.5 km in 2 years) – O3, PM2.5, each hour (NO2, AQHI, AOD, SO2)
soon available on Weather Office http://weather.gc.ca/mainmenu/airquality_menu_e.html
Objective analysis of NO2
Real-time, hourly
zoom in OA near Toronto
OA average summer 2012 OA
averaged analysis increments
CDAT-Option 1CDAT-Option 1 Real-time maps of surface pollutants based on Airnow and TEMPO observationsCDAT-Option 2CDAT-Option 2 Stratospheric assimilation of NO2
CDAT-Option 3CDAT-Option 3 Integrated surface-tropospheric-stratospheric assimilation of NO2 (Airnow+TEMPO) and
other species and dataCDAT-OSSECDAT-OSSE OSSEs (pre-launch) and OSEs (post-launch)
Possible contribution to TEMPOPossible contribution to TEMPO
Thanks for your attention!