Ground-based Ground-based spectroscopic studies of spectroscopic studies of
atmospheric gaseous atmospheric gaseous compositioncomposition
Yana Virolainen, Yuriy Timofeyev, Maria Makarova, Dmitry Ionov, Vladimir Kostsov, Alexander Polyakov,
Anatoly Poberovsky, Marina Kshevetskaya, Anton Rakitin, Sergey Osipov, Hamud Imhasin
Department of Physics of Atmosphere, Saint-Petersburg State University, St. Petersburg, Russia
European Geosciences UnionGeneral Assembly 2011
Vienna, Austria03-08 April 2011
Five most important air mass flow sectors for St. Petersburg:
1. Arctic Ocean and North Russia; 2. continental Russia and Eurasia; 3. Europe;
4. Baltic Sea;
5. Arctic Ocean and Scandinavia.
[1], 14%
[2], 11%[3], 16%
[4], 18%
[5], 41%
Air mass origin for St. Petersburg, RussiaAir mass origin for St. Petersburg, Russia
Devices for atmospheric gases Devices for atmospheric gases measurementsmeasurements
Device Start Method Spectral range Measured
gasesComments
Spectrometer SIRS-2
1991 Direct Sun 3 – 5 μmСО, CH4,
H2O Spectral
resolution 0.3 – 0.5 сm-1
Spectrometers:
Visible-IR - KSVU
OCEAN OPTICS HR4000 UV
HR4000 visible
2004
2009
Scattered solar
radiation
420 – 520 nm
290 – 430 nm410 – 630 nm
О3, NO2, O2-O2
Spectral resolution
1.3 nm
0.4 nm 0.6 nm
MW-radiometer 2007MW
atmospheric radiation
110 GHz О3 Vertical profile
(25 – 60 km)
Fourier-spectrometer
Bruker IFS-125 2009 Direct Sun 1 – 16 μm ~20 gases
Spectral resolution –
up to 0.002 см-1
http://troll.phys.spbu.ru
SIRS-2: CHSIRS-2: CH4 4 total column amount (TCA)total column amount (TCA)
In 1991-2009 the CH4 TCA linear trend is non-significant.
Trend index is positive for Jan-Feb and negative for Jul-Aug
[email protected] – Maria Makarova
The tendency is the increase of the amplitude of CH4 TCA annual cycle
1992 1994 1996 1998 2000 2002 2004 2006 2008 20101991 1993 1995 1997 1999 2001 2003 2005 2007 2009
year
3
3.5
4
4.5
CH
4 T
CA
, *10
19 m
ol/с
m2
3
3.5
4
4.5
Methane TCA seasonal variabilityMethane TCA seasonal variability
Month
CH
4
TC
A1
019m
ol/c
m2
mean
[email protected] – Maria Makarova
Dec-Jan – max values, Jun-Aug – min values. Annual cycle amplitude ~ 3.6%
The annual variations of TCA may differ significantly from the mean annual cycle
SIRS-2: COSIRS-2: CO total column amounttotal column amount
CO
TC
A1
019m
ol/c
m2
[email protected] – Maria Makarova
Linear trends for CO TCA are non-significant. The mean annual cycle for 1995-2009 has max values in Feb-Mar and min values in Jul with ~20% amplitude
Stratospheric NOStratospheric NO22: SCIAMACHY and KSVU: SCIAMACHY and KSVU
good agreement: “SCIAMACHY-KSVU” relative difference is +4±52%
[email protected] – Dmitry Ionov
Tropospheric NOTropospheric NO22: OMI, KSVU and HYSPLIT: OMI, KSVU and HYSPLIT
relatively reasonable agreement for the period of comparison in January-March 2006
[email protected] – Dmitry Ionov
Stratospheric OStratospheric O33: OMI and OceanOptics: OMI and OceanOptics
reasonable agreement: “OMI-OceanOptics” relative difference is +1.1±6.4%
[email protected] – Dmitry Ionov
Example of the ozone profile retrieval: November 28, 2010.
1 – retrieved ozone number density,2 -measured spectrum, 3 - simulated spectrum, 4 – discrepancy.
0 5 10 15 20 25 30December 2007 [days]
80
120
160
200
To
tal
ozo
ne
22
-60
km
[DU
]
ground-basedMLS
110.7 110.8 110.9 111f [GHz]
-0.4-0.2
00.2
[K
]
144
148
152
156
160
Tb
[K]2
3
4
0 2E+012 4E+012O3, cm-3
20
30
40
50
60z
[km
]
1
[email protected] – Vladimir Kostsov
Ozone sounding by microwave radiometerOzone sounding by microwave radiometer
Comparison with MLS AURA satellite data
Measured Measured gasesgases
Spectral Spectral windowswindows, с, сmm-1-1
Random error Random error for one for one
measurementmeasurement, , %%
Influenced Influenced gasesgases
H2O 2898 – 2905 1.5 CH4, HCl, HDO
CH4 2898 – 2905 0.8 H2O, HCl, HDO
N2O 2156 – 2164 1.0 CO, H2O, O3
CO 2156 – 2164 1.5 N2O, H2O, O3
CO2 2626.3 – 2627.0 1.8 CH4
C2H6 2976.6 – 2977.1 2.0 O3, H2O, CH4
HCl 2925.75 – 2926.0
1.7 CH4,H2O,
HF 4038.85 – 4039.05
2 H2O, HDO
CCl3F
(CFC-11)
830 – 870 13 H2O, HNO3, O3
Errors of Bruker spectrometer TCA Errors of Bruker spectrometer TCA retrievalsretrievals
[email protected] – Anton Rakitin
2009 2010 20111.2
1.6
2
2.4
2.8
CO
TC
A, 1
018 m
ol/c
m2
J F M A M J J A S O N D J F M A M J J A S O N D
2009 2010 20113.5
3.6
3.7
3.8
3.9
4
CH
4 T
CA
, 101
9 m
ol/c
m2
Bruker IFS125SIRS (grating spectrom eter)
J F M A M J J A S O N D J F M A M J J A S O N D
CHCH44 and CO TCA retrievals and CO TCA retrievals (Bruker)(Bruker)
[email protected] – Maria Makarova
Average values of CH4 TCA for Mar-Jun 2009 obtained by two instruments are agree within 0.5%.
NN22O TCA retrievals (Bruker/NDACC stations)O TCA retrievals (Bruker/NDACC stations)
[email protected] – Marina Kshevetskaya
Annual means of N2O TCA for local measurements are in good coincidence with annual means for NDACC stations
Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr 2009 2010
PeterhoffACE-FTS 500km
0
1
2
3
Max values – Feb-Mar, min values – summer-fall. Good agreement with measurements on NDACC stations.
Good coincidence with satellite ACE-FTS measurements.
Seasonal cycle of HF TCASeasonal cycle of HF TCA
[email protected] – Alexander Polyakov
Brem en, 53.1 NHartestua, 60.2 NEureka, 80.1 NPeterhoff, 59.9 N
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0
1
2
3
HF
T
CA
, 10
15
cm
-2
Bruker ozone TCA measurementsBruker ozone TCA measurements
[email protected] – Yana Virolainen
TCA ozone measurements near St. Petersburg made by different instrumentation
Dobson and M-124 – ground-based instruments located ~ 50 km NE of PeterhofOMI – satellite instrument, temporal-space coincidence ~ 100 km
[email protected] – Yana Virolainen
The example of ozone TCA diurnal variations measured by Bruker spectrometer (noise component of ~ 3 D.U.)
Correlation between ozone TCA obtained from different devices (mean – 0.3-1.7%, RMS – 3-4%)
Bruker ozone TCA measurementsBruker ozone TCA measurements
Combined method (IR+MW) for ozone: Combined method (IR+MW) for ozone: errorserrors
[email protected] – Yana Virolainen
Main characteristics:
S – measurement error matrix (1)A– averaging kernel matrix (2)
S=(Sa-1+KTSε
-1K)-1 (1)
A =(Sa-1+KTSε
-1K)-1 KTS ε-1K =
SKTSε-1K (2)
Sa – a priori variability matrix for sought vector of atmospheric state
K – the matrix of variational derivates of the radiation with respect atmospheric parameters
Sε – the matrix of non-correlated measurement errors
Errors of retrieving the ozone mixing ratio profile for different measurement scenarios
[email protected] – Yana Virolainen
Combined method (IR+MW): ozone Combined method (IR+MW): ozone profileprofile
Averaging kernels for ozone measurements by interferometer and microwave radiometer
Layer, km 0-10 10-1515-20
20-25 25-30 30-40 40-50
UO3, DU 34.4 38.2 62.2 100.7 86.1 82.2 14.2
σ apriori, % 30 33 32 32 32 30 31
σ aposteriori, % 3.7 6.4 5.6 3.8 4.0 3.6 5.9
Potential error of ozone retrieval in thick atmospheric layers
Main results and conclusionsMain results and conclusions
http://troll.phys.spbu.ru
• A large number of atmospheric trace gases (TG) are retrieved by different ground-based instrumentation • Temporal variations (from diurnal cycles to long-term trends) of TG are studied on the basis of experimental data
•The TG measurements are used for numerical modeling and for validation of satellite data
•Further development of techniques for TG profiles retrieving and expanding the list of TG are planned