Post on 19-Jan-2016
description
Assimilation of OMI Data Into NCEP’s GFS
Craig Long,
S. Zhou, T. Beck, A.J. MillerNOAA/NWS/NCEP/Climate Prediction Center
L.Flynn
NOAA/NESDIS/STAR
Outline
Background Improvements due to OMI coverage OMI Issues Comparisons between SSI and GSI How OMI data is assimilated
Thinning possibilities
Summary What’s Next
Aspects of Ozone in NWP
Three aspects of dealing with ozone in NWP Assimilation of ozone observations
• Horizontal and vertical
• Agreement between multiple sources
Transport of ozone once in the model• Brewer Dobson Circulation
Ozone Chemistry• Homogeneous: Production and Loss
– f: Latitude, Pressure, Season
• Heterogeneous: 'Ozone Hole' type depletion
– Need additional observations
Background
Currently NCEP GFS assimilates SBUV/2 total and profile ozone measurements from both NOAA-16 and 17.
SBUV/2 provides about 90 nadir observations per orbit. Replacement instrument is the OMPS (Ozone Mapping
and Profiler Suite) Combination of scanning mapper and limb profile On NPP and NPOESS Will provide higher vertical and horizontal resolution
Current additional sources of ozone data available: Aura: OMI*, HIRDLS*, MLS, TES *NRT MetOp: GOME2*
Background cont.
Why is ozone assimilated? LW and SW radiation schemes need realistic ozone. Used to extract correct temperature component from the ozone
sensitive HIRS channels. Biggest impacts in terms of temperature and dynamics and
should occur in the UT/LS.• Won't improve short term skill (days 1-3)
• But should improve days >3
Ozone forecasts used in UV Index forecasts. Used for boundary conditions in Air Quality forecasts.
OMI
GFS
OMI Comparison with GFS using SBUV/2
OMI shows finer structure than the GFS, e.g., the relatively high ozone off the East coast is captured by OMI but
missed by GFS.
November 11, 2005
SBUV/2 only Adding OMI TOMS obs.
Adding OMI makes 5 day total ozone forecast agree more with NASA/TOMS
November 12, 2005
SBUV/2 only Adding OMI TOMS obs.
November 13, 2005
SBUV/2 only Adding OMI TOMS obs.
November 14, 2005
SBUV/2 only Adding OMI TOMS obs.
November 15, 2005
SBUV/2 only Adding OMI TOMS obs.
end
OMI Issues• Conflicts with SBUV/2 at high SZA
Also SBUV/2 is V6 product Is V8 much different? Where? When?
• Noise in some channels affects TO3 at high SZA Cloud climatology may degrade quality of TO3
• Comparisons with DOAS products DOAS has striping But, better estimate of cloud top heights
• High density of data 840 points per single SBUV/2 ob Needs thinning
• Comparisons with surface obs
N16 SBUV/2 & OMTO3 Nadir Total Ozone - 20051023
140160180200
220240260280300320340360
380400420440
-90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90
Tot
al O
zon
e (D
U)
N16 OMTO3
Comparison between OMTO3 (NASA/TOMS) and OMDOAO3 (KNMI/DOAS)
OMTO3 vs OMDOAO3 Zonal Mean Total Ozone
Mean may average out to near zero, but variability is quite high!
Striping in DOAS Total ozone makes it unusable
TOMS and SBUV/2 V8 Clim Cloud Tops Results in Total Ozone being too High
DOAS Cloud Top PressuresOMTO3 Cloud Top Pressures
OMTO3 Cloud Top Pressure Climatology Issue
0 10000 1000500 500
OMTO3 using cloud own climatology OMTO3 using DOAS cloud top heights
If DOAS Cloud Top Pressures are used,OMTO3 Total Ozone usually is lower
208 258 208 258
OMI N-17 SBUV/2 N-16 SBUV/2
(12Z)
GSI vs SSI
SBUV/2 only (N16,N17)
OMI only
SBUV/2 andOMI
GSI SSI
Total Ozone increment (DU)
SBUV/2 only
OMI only
SBUV/2 and OMI
GSI – SSI differences
Data Thinning• There are many ways to thin massive amounts of sat. obs.
• Experimentation is only way to determine best density: Sometimes “less is more”
• OMI vs SBUV # of obs 60 OMI obs/scan x 14 scans/SBUV retrieval
Or 840 points per SBUV retrieval
~76,000 points per orbit
• Need to restrict OMI to quality data points
• Thin by selection Fewer points in flat regions - more points in dynamic regions
Background errors may be adjusted to be more sensitive in dynamic regions
• Thin by averaging Uniform coverage
Average out noisy data
Flat region Dynamic regions
Dynamic ozoneregionsFlat region
Total Ozone Variability within Scan - 20051023
0
10
20
30
40
50
60
70
80
-90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90
Var
iab
ilit
y w
ith
in S
can
(D
U)
Orb1 Orb2 Orb3 Orb4 Orb5 Orb6 Orb7 Orb8 Orb9 Orb10 Orb11 Orb12 Orb13 Orb14
Dynamic ozoneregions
Flat region
Data thinning method tested
• Method: averaging data in 1o x 1o model grid box.
• Selection: when there are overlapped data from multiple orbits within a 1o x 1o box, select data only from one major orbit.
• Reduction: total number of data is reduced to ~ 6%.
OMI N-17 SBUV/2 N-16 SBUV/2
(12Z)
1o (lat) x 1o (lon) thinning
12Z
From ~ 76,000 obs per orbit to ~ 4000
1o (lat) x 2o (lon) thinning
12Z
From ~ 76,000 obs per orbit to ~ 2000
DU
Ozone difference of thinning and non-thinning (GSI)SBUV/2 and OMI
DU
GSI and SSI TOZ difference (1o x 1o thinning)
GSI and SSI TOZ difference (1o x 2o thinning)
DU
Summary
OMI adds additional information in horizontal
OMI data have issues to be rectified Are ways to improve it!
GSI assimilation of OMI data not significantly different from SSI
What’s Next
• Move to Aqua computer when available.
• Continue experimenting with thinning options.– Quality assessment of data
• Assess impacts in forecast mode.– Determine resolution dependence
– Impacts to temperatures and dynamics
– Strive for improvement in multi-day forecasts.
• Begin looking at OMI profile products– Profile total ozone may be better than ‘best’ ozone
– Additional profiles
• Use March 2006 as test month
• Compare profiles with ozonesonde and Lidar data.
• HIRDLS data
fini
MLS
OMI
TESHIRDLS
EOS AURA was launched in July 2004, which has 4 ozone measuring instruments.
Aura instruments
• OMI (ozone Monitoring Instrument)– total ozone and ozone profile, high horizontal resolution
• HIRDLS (High Resolution Dynamics Limb Sounder)
– ozone profile, high vertical resolution (1.25 km, 10-80 km)
• MLS (Microwave Limb Sounder)– ozone profile (3 km, 8-50 km)
• TES (Tropospheric Emission Spectrometer)
– tropospheric ozone (0-34 km)