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Global-scale atmosphere monitoring by in-service aircraft – current achievements and future prospects of the European Research Infrastructure IAGOS Cover

Global-scale atmosphere monitoring by in-service aircraft – current achievements and future prospects of the European Research Infrastructure IAGOS

Open Access
|Jan 2015

Figures & Tables

Fig. 1

Evolution of airborne observations using instrumented passenger aircraft from programmes MOZAIC and CARIBIC to IAGOS: the aircraft represent the number of equipped units in operation, with the larger aircraft symbol representing IAGOS-CARIBIC. Observation parameters are indicated for the various evolution stages of the programme.

Table 1. Objectives and scientific value of IAGOS research infrastructure

Scientific and technical objectivesIAGOS research infrastructureLong-term deployment (20 yr)
Open data policy (GEO/GEOSS)IAGOS-COREAtmosphere monitoring by up to 20 long-haul aircraft equipped with scientific instruments for
 • atmospheric chemical composition
 • (H2O, O3, CO, NO x , NO y , CO2, CH4)
 • aerosol particles
 • cloud particles
Global-scale coverage of observations
Near real-time data provision for CAMSIAGOS-CARIBICMonthly deployment of the instrumented CARIBIC container aboard one aircraft
Measurement of a large number of species (~100), including those of IAGOS-CORE plus
 • stratospheric H2O, cloud ice/water
 • N2O, SF6, VOCs
 • (H)CFCs
 • NMHCs
 • aerosol particle elemental composition
 • H2O isotopologues and
 • HgScientific valueChanges in the tropopause regionHigh spatial and temporal resolution of in-situ observations
Ozone background and trend
Water vapour background and trend
Stratosphere–troposphere exchange and related transport mechanismsValidation of atmospheric models and satellite retrievalsTropospheric profiles of H2O, O3, CO, NO x , CO2, CH4, aerosols, cloud particles
UTLS data of H2O, O3, CO, NO x , CO2, CH4, aerosols, cloud particlesGlobal air qualityInfluence of developing regions
Long-range transport of air pollutants
Vertical transport of air pollutants by deep convectionInternational transfer standardsUse of proven measurement technology
Global deployment of identical instruments
Regular quality assurance including calibration against reference instruments, based on GAW standard procedures

Table 2. Current IAGOS fleet

TypeIAGOSAirlineHome baseCall signMain destinationsStart dateA340CARIBICLufthansaFrankfurt/MunichD-AIHENorth and Central America, AsiaDecember 2004A340CORELufthansaFrankfurt/DüsseldorfD-AIGTNorth Atlantic routes to North America, few destinations in South America and in East AsiaJuly 2011A340COREChina AirlinesTaipeiB-18806Trans-Pacific routes to North America, destinations in Southeast Asia and EuropeJune 2012A340COREAir-FranceParisF-GLZUNorth and mid-Atlantic, Western AfricaJune 2013A330CORECathay PacificHong KongB-HLRSouth Asia and AustraliaAugust 2013A340COREIberiaMadridEC-GUQSouth and Central AmericaFebruary 2014A330CORELufthansaFrankfurtD-AIKOEquatorial Africa and Middle EastMarch 2015
Fig. 2

IAGOS-CORE installation position aboard the Lufthansa A340-300 ‘Viersen’ (photograph by courtesy of A. Karmazin); the inset shows details of the IAGOS Inlet Plate, which carries the inlet probes for trace gas sampling (photograph by courtesy of Lufthansa).

Fig. 3

Installation of IAGOS-CORE instrumentation in the avionics bay of Lufthansa D-AIGT.

Fig. 4

Available configurations for IAGOS-CORE instrumentation.

Table 3. IAGOS-CORE instrumentation

ParameterMethodTRaUncertaintybResponsibility/referencePackage 1All aircraftO3UV absorption4 s±2 ppbCNRS (Thouret et al., 1998; Nédélec et al., 2015)COIR absorption30 s±5 ppbCNRS (Nédélec et al., 2003, 2015)H2OCapacitive hygrometer5–300 s±5% RHFZJ (Helten et al., 1998; Neis et al., 2015a, 2015b)Cloud particlesBackscatter cloud probe4 sUniversity of Manchester, UK (Beswick et al., 2014)Package 2 (one option per aircraft)Opt. aNO y Chemiluminescence gold converter4 s±50 pptFZJ (Volz-Thomas et al., 2005; Pätz et al., 2006)cOpt. bNO x Chemiluminescence photolytic conversion4 s±50 pptFZJOpt. cAerosol particlesCondensation particle counter (0.01–3 µm)
Optical particle counter (0.25–3 µm)4 s±10 cm−3

±5 cm−3FZJ/DLR (Bundke et al., 2015)Opt. dCO2
CH4
H2O
COCavity ring-down spectroscopy4 s±0.1 ppm
±2 ppb
±6–15 ppm
±10 ppbMPI-BGC (Filges et al., 2015)

[i] aTR, time resolution or data rate, whatever is longer; bthe accuracy of each instrument includes potential inlet effects and will be reported as soon as experience has been gained for operating the instruments aboard the IAGOS-CORE aircraft; creferences refer to the MOZAIC NO Y instrument.

Fig. 5

Number of aircraft in operation (bottom panel), number of flights (mid-panel) and cumulative number of scientific publications (top panel) for MOZAIC (until 2014), IAGOS-CORE (from 2011) and IAGOS-CARIBIC.

Fig. 6

Map of IAGOS-CORE flights from July 2011 to August 2015.

Fig. 7

IAGOS-CARIBIC aircraft, air inlet system and measurement container (Brenninkmeijer et al., 2007).

Table 4. IAGOS-CARIBIC instrumentation (as of 2015)

ParameterMethodTRaUncertaintybResponsibility/referenceIAGOS databaseO3UV absorption
Chemiluminescence4 s
0.2 s±0.5 ppbv or 1% (the higher)KIT (Zahn et al., 2012)COVUV fluorescence2 s±1.6 ppbMPI-C (Scharffe et al., 2012)H2O totalLaser photoacoustic4–20 s<3%KIT (Zahn et al., 2014; Dyroff et al., 2015)H2O gaseousLaser photoacoustic
Dew point4–20 s
5–90 s<3%KIT (Zahn et al., 2014; Dyroff et al., 2015)Aerosol particlesCondensation particle counter (0.004–3 µm)
Optical particle counter (0.14–1.05 µm)2 s
180 s±15%
±19% (N140)
and
±25% (SD)TROPOS (Hermann and Wiedensohler, 2001)NO/NO y Chemiluminescence
Gold converter1 s±8% (5%) for 0.1 ppb (1.0 ppb)DLR (Ziereis et al., 2000)On requestOVOCsProton-transfer-reaction mass spectrometry30 s±15–30%KIT (Brenninkmeijer et al., 2007)BrO
SO2
NO2
CH2O
HONODifferential optical absorption spectroscopy30 s10 ppt
10 ppb
1 ppb
1 ppb
5 ppbUniversity of Heidelberg (Dix et al., 2009)HgEnrichment and atomic fluorescence300 s or 600 s±10%HZK (Slemr et al., 2009)Aerosol particle elemental compositionImpactor plus PIXE/PESA analysis100 min±12%University of Lund (Nguyen et al., 2006; Nguyen and Martinsson, 2007)Particulate sootSingle particle soot photometer1 sMPI-C (Schwarz et al., 2006)NMHCs~120 s sampling every 20–30 min0.1–5.4%MPI-C (Baker et al., 2010)(H)CFCs~120 s sampling every 20–30 min±2–20%University of East Anglia (O'Sullivan, 2008)GHGs (CO2, CH4, N2O, SF6)~120 s sampling every 20–30 min±0.08–0.8%MPI-C (Schuck et al., 2009)

[i] aTime response; bIAGOS-CARIBIC operates a specifically developed and well-characterised inlet system; uncertainty includes inlet effects.

Fig. 8

IAGOS-CARIBIC map of flights (May 2005–August 2015).

Fig. 9

Data processing path from the aircraft raw state to the user available state. Data levels refer to raw data (L0A), to automatically analysed data using pre-flight or in-flight calibrations (L0B), to data validated by the responsible PI and published as preliminary data (L1) and to final data (L2) after removal of instrument from the aircraft and post-flight calibration. Climatological data (L3) and added-value products (L4) are also available, whereas near real-time (NRT) data are made available for data assimilation and model evaluation.

Table 5. IAGOS data levels

LevelDescriptionL0ARaw dataL0BAutomatically validated dataNRTNRT for Copernicus use, bad data removedL1Data validated by PI (preliminary data)L2Calibrated data (final data)L3Averaged data and climatologiesL4Added-value products

Table 6. IAGOS database measurement products

MOZAICO3, CO, H2O, NO y IAGOS-COREO3, CO, H2O, NO y
NOx, CO2, CH4, aerosols, cloudsIAGOS-CARIBICO3, CO, H2Ogas, H2Ocloud, NO y
NO x , CO2, CH4
Particle (number) concentrations (N4–12, N12, N18, N140, M140)
Particle size distribution (140–1050 nm)
NO2

Table 7. Atmospheric state and aircraft parameters provided by the A340/A330 aircraft system

ParameterUnitUncertaintyBarometric altitudem15aRadio altitudem5%bGPS altitudem15bLatitude/longitude°0.01Total air pressurehPa0.25Static air pressurehPa0.35Total air temperature°C0.25Static air temperature°C0.50Aircraft ground speedm s−12.0Aircraft air speedm s−10.5Wind speedm s−12–3cMach number<0.2%

[i] Adapted from WMO (2003). aBased on the ICAO-Barometric Altitude Formula used in aviation; baltitude with respect to ground surface below aircraft; cuncertainty is here combining wind speed and direction as the vector error.

Fig. 10

Flights on 5 July 2013 showing enhanced CO at cruise altitude, in the boundary layer over the source region (North America) and in the mid-troposphere over Europe.

Fig. 11

Top panel: dispersion of Canadian fire plumes over Europe on 8 July 2013. Bottom panel: comparison of the vertical profiles of CO from the MACC-2 forecasts for the July 2013 episode to IAGOS measurements obtained over Frankfurt; the bottom right panel shows a LIDAR backscatter profile taken over Jülich on 12 July 2013 (adapted from Thouret and Petzold, 2015).

Fig. 12

Monthly mean vertical profiles of ozone (top panels) and CO (bottom panels) over Frankfurt in December 2012, as observed from MOZAIC-IAGOS (black lines) and modelled by different versions of the MACC model (coloured lines) in forecast mode (left panels) and reanalysis mode (right panel). Further examples and details may be found in www.iagos.fr/macc.

Fig. 13

CO (left panels) and ozone (right panels) seasonally averaged distributions in the UT (bottom panels) and in the LS (top panels) as recorded at cruise level by MOZAIC aircraft over the period 2001–2011. Data are averaged on 5°×5° grid cells. Lines UT display data observed between 15 and 45 hPa below the local tropopause (defined as the isoPV surface 2 pvu). Lines LS display data observed above −45 hPa above the local tropopause. Figures are adapted from Thouret et al. (2006) and extended to 2011.

Fig. 14

Climatology of water vapour in the upper troposphere (top panel) and lowermost stratosphere (bottom panel) from SPURT and MOZAIC; courtesy of A. Kunz (2010).

Fig. 15

Vertical profiles of H2O, CO, CO2 and acetone relative to the tropopause along a flight from Seoul (Korea) to Frankfurt (Germany) on 28 March 2012. Colour coding: potential temperature in Kelvin.

Language: English
Page range: 28452 - 28452
Submitted on: May 6, 2015
Accepted on: Sep 14, 2015
Published on: Jan 1, 2015
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2015 Andreas Petzold, Valerie Thouret, Christoph Gerbig, Andreas Zahn, Carl A. M. Brenninkmeijer, Martin Gallagher, Markus Hermann, Marc Pontaud, Helmut Ziereis, Damien Boulanger, Julia Marshall, Philippe Nédélec, Herman G. J. Smit, Udo Friess, Jean-Marie Flaud, Andreas Wahner, Jean-Pierre Cammas, Andreas Volz-Thomas, IAGOS Team, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.