Ground-based spectroscopic studies of atmospheric gaseous composition Ground-based spectroscopic studies of atmospheric gaseous composition 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 Union General Assembly 2011 Vienna, Austria 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, Russia

Devices for atmospheric gases measurements DeviceStartMethodSpectral range Measured gases Comments Spectrometer SIRS Direct Sun 3 – 5 μm3 – 5 μm СО, CH 4, H 2 O Spectral resolution 0.3 – 0.5 сm -1 Spectrometers: Visible-IR - KSVU OCEAN OPTICS HR4000 UV HR4000 visible Scattered solar radiation 420 – 520 nm 290 – 430 nm 410 – 630 nm О 3, NO 2, O 2 - O 2 Spectral resolution 1.3 nm 0.4 nm 0.6 nm MW-radiometer2007 MW atmospheric radiation 110 GHzО3О3 Vertical profile (25 – 60 km) Fourier- spectrometer Bruker IFS Direct Sun 1 – 16 μm ~20 gases Spectral resolution – up to см -1

SIRS-2: CH 4 total column amount (TCA) In the CH 4 TCA linear trend is non- significant. Trend index is positive for Jan-Feb and negative for Jul-Aug – Maria Makarova The tendency is the increase of the amplitude of CH4 TCA annual cycle

Methane TCA seasonal variability Month CH 4 TCA  mol/cm 2 mean – 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: CO total column amount CO TCA  mol/cm 2 – Maria Makarova Linear trends for CO TCA are non-significant. The mean annual cycle for has max values in Feb-Mar and min values in Jul with ~20% amplitude

Stratospheric NO 2 : SCIAMACHY and KSVU good agreement: “SCIAMACHY-KSVU” relative difference is +4±52% – Dmitry Ionov

Tropospheric NO 2 : OMI, KSVU and HYSPLIT relatively reasonable agreement for the period of comparison in January-March 2006 – Dmitry Ionov

Stratospheric O 3 : OMI and OceanOptics reasonable agreement: “OMI-OceanOptics” relative difference is +1.1±6.4% – Dmitry Ionov

Example of the ozone profile retrieval: November 28, – retrieved ozone number density, 2 -measured spectrum, 3 - simulated spectrum, 4 – discrepancy. – Vladimir Kostsov Ozone sounding by microwave radiometer Comparison with MLS AURA satellite data

Measured gases Spectral windows, сm -1 Random error for one measurement, % Influenced gases H2OH2O2898 – CH 4, HCl, HDO CH – H 2 O, HCl, HDO N2ON2O2156 – CO, H 2 O, O 3 CO2156 – N 2 O, H 2 O, O 3 CO – CH 4 C2H6C2H – O 3, H 2 O, CH 4 HCl – CH 4,H2O, HF – H 2 O, HDO CCl 3 F (CFC-11) 830 – 87013H 2 O, HNO 3, O 3 Errors of Bruker spectrometer TCA retrievals – Anton Rakitin

CH 4 and CO TCA retrievals (Bruker) – Maria Makarova Average values of CH4 TCA for Mar- Jun 2009 obtained by two instruments are agree within 0.5%.

N 2 O TCA retrievals (Bruker/NDACC stations) – Marina Kshevetskaya Annual means of N 2 O TCA for local measurements are in good coincidence with annual means for NDACC stations

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 TCA – Alexander Polyakov

Bruker ozone TCA measurements – Yana Virolainen TCA ozone measurements near St. Petersburg made by different instrumentation Dobson and M-124 – ground-based instruments located ~ 50 km NE of Peterhof OMI – satellite instrument, temporal-space coincidence ~ 100 km

– 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 – %, RMS – 3-4%) Bruker ozone TCA measurements

Combined method (IR+MW) for ozone: errors – Yana Virolainen Main characteristics: S – measurement error matrix (1) A– averaging kernel matrix (2) S=(S a -1 +K T S ε -1 K) -1 (1) A =(S a -1 +K T S ε -1 K) -1 K T S ε -1 K = SK T S ε -1 K (2) S a – a priori variability matrix for sought vector of atmospheric state K – the matrix of variational derivates of the radiation with respect atmospheric parameters S ε – the matrix of non-correlated measurement errors Errors of retrieving the ozone mixing ratio profile for different measurement scenarios

– Yana Virolainen Combined method (IR+MW): ozone profile Averaging kernels for ozone measurements by interferometer and microwave radiometer Layer, km U O3, DU σ apriori, % σ aposteriori, % Potential error of ozone retrieval in thick atmospheric layers

Main results and conclusions 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