UV-VISIBLE MEASUREMENTS

WHAT CAN WE RETRIEVE IN THE UV-VISIBLE? Most easily retrieved (strongest features): O 3 (~300 nm), NO 2 (~ nm), H 2 O(>500 nm) HCHO ( nm) ClO ( nm) BrO ( nm) SO 2 ( nm) [Gottwald et al., The SCIAMACHY Book, 2006]

DIFFERENCES BETWEEN UV-VISIBLE AND IR RETRIEVALS 1.Atmospheric Scattering must now be considered 2.There is no emission from the atmosphere  no vertical information from emission at different T, therefore total columns ONLY* 3.Absorption cross-sections generally extend across larger wavelength regions, unlike strong IR features In general, UV-visible retrievals are “physical retrievals” and do not employ optimal estimation* *exception = tropospheric ozone

UV-VISIBLE RETRIEVALS ARE A 2-STEP* PROCESS 1.From spectra estimate a slant column(  S ) Two common approaches employed: A.Direct Spectral Fitting B.DOAS (Differential Optical Absorption Spectroscopy) 2. Translate from slant column to vertical column (  ) Slant column depends on the location of the sun and the satellite and therefore the light path length is variable! Need to translate to some geophysical quantity that’s useful. But it’s not just geometry… Slant Column (along light path) Vertical Column AMF=air mass factor * There can be additional steps (corrections, considerations), depending on the species

DIRECT SPECTRAL FITTING Example: direct fit of GOME backscattered spectrum in nm HCHO band  [HCHO]=3.0x10 16 molecules/cm 2 Chance et al. [2000] REFERENCE SPECTRA + TEMPERATURE DEPENDENCE MEASURED SPECTRA LEAST SQUARES FITTING SLANT COLUMN OF [X]

DIFFERENTIAL OPTICAL ABSORPTION SPECTROSCOPY Use multiple wavelengths to characterize optical absorption of a species. C=concentration L=light-path length  =absorption cross-section  R  Raleigh extinction  M  Mie extinction I o ’=intensity in absence of differential absorber Separate slowly moving component (  io ) from rapidly moving component (  i ’): Differential optical density: DOAS requires species with reasonably narrow absorption features

AIR MASS FACTORS (AMF) Air mass factor (AMF) depends on the viewing geometry, the scattering properties of the atmosphere, and the vertical distribution of the absorber Requires an Radiative Transfer model and a Chemical Transport Model (CTM) w(z): satellite sensitivity (“scattering weight”), determined from radiative transfer model including clouds and aerosols S(z): normalized mixing ratio (“shape factor”) from CTM AMF G : geometric air mass factor (no scatter) Palmer et al., 2001 Accounting for scattering weights is far less important for stratospheric species (eg. BrO in the stratosphere)

GEOMETRIC AIR MASS FACTOR SZA vv SZA=solar zenith angle  v =satellite viewing angle d1d1 d2d2 dvdv Slant distance= d 1 +d 2 = d v /cos(SZA)+d v /cos(  v ) = d v [sec(SZA)+sec (  v ) ] AMF G =d/d v = sec(SZA)+sec(  v ) Values of the geometric air mass factor typically ~  Vertical column is ~ ½ of slant column purely from geometry 

GOME sensitivity w(  ) HCHO mixing ratio profile S(  ) (GEOS-Chem) what GOME sees AMF G = 2.08 actual AMF = 0.71 AMF FORMULATION FOR A SCATTERING ATMOSPHERE Palmer et al., 2001 Account for vertical instrument sensitivity (scattering increases towards the surface, inhibits the view of the lower atmosphere) + how this is convolved with the distribution of species X Example from GOME formaldehyde (HCHO) measurements

WHAT ARE AMFs SENSITIVE TO? Scattering weights are most sensitive to the surface albedo and aerosol loading Palmer et al., 2001 Increasing A allows more solar radiation into the lower atmosphere = increasing observational sensitivity Relatively insensitive to angle between sun & satellite (  E ): with larger angle physical path increase (AMF G larger) but scattering along the path reduces the sensitivity Aerosols increase the sensitivity to HCHO in this example: increasing AOD from 0.1 to 1.0 (typical range) increases AMF by 30% Scattering decreases the sensitivity to species AMF is typically ½ AMF G

HOW VARIABLE ARE AMFs? If most of the species X is in the BL, where the instrument is not as sensitive, the AMF will be lower to compensate  ocean AMFs are higher than over land * We should all be grateful that journals no longer charge for on-line colour Also see particularly low AMFs in California due to shallow BL Continuing with our HCHO example… Palmer et al., 2001 Given this variability, it is inappropriate to use single S(z) for tropospheric species

RETRIEVAL CONSIDERATIONS 1.CLOUDS: Cloud droplets scatter radiation and complicate the interpretation… Generally try to filter for < 40% cloudy conditions to ensure higher quality retrievals 2. AEROSOLS: Important sensitivity to aerosols means it’s important to include these in the scattering weight calculations. 3. ARTIFACTS: GOME solar diffuser plate bias: daily varying global bias – tricky correction! 4. STRATOSPHERIC CONTRIBUTION: For species with significant part of the column in the stratosphere, must develop a technique to remove this contribution. 4. SHAPE FACTOR: continual improvement of shape factors from model. Also shape factors may vary at spatial scales higher than represented by models…

THE ROLE OF CLOUDS Clouds enhance sensitivity to species above clouds and reduce (obscure) sensitivity for below cloud Early retrievals tried to limit cloud contamination by keeping F cloud <40% Later techniques: more sophisticated approach to separately estimate AMF for cloudy & clear scenes and combine based on cloud fraction Advantages: (1)correct cloud effects on backscatter (2) retrieve in partly cloud scenes Martin et al., 2002 a=clear-sky c=cloudy R=reflectivity f=cloud fraction

VARIABILITY OF AMFs and CLOUDS July AMFs for NO 2 Clear-sky AMFs Actual AMFs (accounting for clouds) Martin et al., 2002 AMF c >AMF a when little NO 2 is below the cloud (oceans) AMF c <AMF a when cloud obscures BL NO 2 (land) Note high spatial variability in the cloud correction

STRATOSPHERIC CONTRIBUTION MUST BE REMOVED FOR SOME SPECIES…. Significant fraction of the column is in the stratosphere (note poleward increase) General approach: (1)Pick low-tropospheric NO 2 region  Pacific * If assume NO tropospheric contribution here might remove too much! (2)Assume the stratospheric contribution is longitudinally invariant (3)Subtract stratospheric contribution from total slant column

TOMS/ Nimbus 7 (78-94) Meteor-3 (78-94) ADEOS (96) EP (96-06) GOME/ERS-2OMI/AURASCIMACHY/ ENVISAT Total O 3 (derived tropospheric column), AI, SO 2 Global coverage ~daily UV-vis O 3, NO 2, HCHO, BrO, OClO, H 2 O, SO 2 Global coverage 3 days UV-vis O 3, NO 2, HCHO, BrO, OClO, H 2 O, SO 2 Daily Global coverage UV-vis O 3, NO 2, HCHO, BrO, OClO, H 2 O, SO 2, CO, CH 4 Global coverage 3 days UV-vis-near IR ATMOSPHERIC MEASUREMENTS FROM UV-VISIBLE GOME-2/ METOP-A

TOTAL OZONE MAPPING SPECTROMETER ( ) 1 day of data Launched onboard several platforms, last in the series was EP-TOMS (NASA) EP-TOMS HORIZONTAL COVERAGE: 39 km x 39 km nadir footprint with 1365 km cross-track scanning  Global coverage ~ daily EP-TOMS OVERPASS TIME: ~11:16 equator cross-over

TOMS INSTRUMENT PRODUCTS: O 3 column Aerosol Index UV radiance SO 2 MEASUREMENT TECHNIQUE: Monochromator (SBUV) –6 wavelength bands (309, 313, 317, 322, 331, 360 nm) Chappuis band Huggins band Harrtley band

GLOBAL OZONE MONITORING EXPERIMENT (GOME) Launched Apr HORIZONTAL COVERAGE: 40 km x 320 km nadir footprint with 960 km cross-track scanning (GOME-2 40 km x80 km)  Global coverage in ~3 days (GOME-2 ~1day+) OVERPASS TIME: ~10:30 equator cross-over (note only daytime in UV-visible provides useful data) 1 day of data Launched onboard ERS-2 (ESA)

GOME INSTRUMENT Launched Apr PRODUCTS: O 3 (column & profile) NO 2 HCHO BrO OClO H 2 O SO 2 MEASUREMENT TECHNIQUE: Scanning Spectrometer –Spectral range: nm (covered in 4 channels) –Spectral resolution: nm GOME-2

SCANNING IMAGING ABSORPTION SPECTROMETER FOR ATMOSPHERIC CARTOGRAPHY(SCIAMACHY) Launched Mar 2002 HORIZONTAL COVERAGE: 30 km x 60 km nadir footprint with 1000 km cross-track scanning  Global coverage in ~3 days OVERPASS TIME: ~10:00 equator cross-over 1 day of data Launched onboard Envisat (ESA)

SCIAMACHY INSTRUMENT Launched Mar 2002 MEASUREMENT TECHNIQUE: Imaging Spectrometer (very similar to GOME) –Spectral range: , , , , , , and nm –Spectral resolution: nm

THREE VIEWING GEOMTRIES FOR SCIAMACHY (1)Nadir (2)Limb (3)Solar occultation

OZONE MONITORING INSTRUMENT (OMI) Launched July 2004 HORIZONTAL COVERAGE: 13 km x 24 km nadir footprint with 2600 km cross-track scanning  Daily Global coverage OVERPASS TIME: ~13:30 equator cross-over 1 day of data Launched onboard EOS-Aura (NASA) Reduced pixel size is a big advantage! (less cloud contamination)

OMI INSTRUMENT Launched July 2004 MEASUREMENT TECHNIQUE: Imaging spectrometer (CCD detector) –Spectral range: nm, nm, nm –Spectral resolution: nm PRODUCTS: O 3 (column & profile) NO 2 HCHO BrO OClO H 2 O SO 2

EFFECT OF SPATIAL RESOLUTION ON TROPOSPHERIC MEASUREMENTS Even at SCIAMACHY spatial resolution details are lost Courtesy: Andreas Richter * OMI is 13x24 km 2 GOME-2 is 80x40 km 2

OMI instrument March 2006 NASA INTEX-B aircraft mission Boersma et al. [2008] NO 420 nm NO 2 MAPPING OF NO x EMISSIONS FROM SPACE using measurements of tropospheric NO 2 columns satellite validation spirals NO x is mainly from fossil fuel combustion; limiting precursor for ozone formation

TROPOSPHERIC NO 2 RETRIEVAL Data analysis: 1.Cloud screening 2.DOAS retrieval of total slant columns 3.Subtraction of clean Pacific sector to derive tropospheric slant columns 4.Application of tropospheric airmass factor to compute tropospheric vertical column

ERROR ANALYSIS FOR TROPOSPHERIC NO2 min error [Martin et al., 2002]

HIGHER SPATIAL RESOLUTION FROM SCIAMACHY Launched in March 2002 aboard Envisat Potential for finer resolution of sources, but need to account for transport 320x40 km 2 60x30 km 2

K. Folkert Boersma (KNMI) TROPOSPHERIC NO 2 FROM OMI October 2004

NO X MEASUREMENTS REVEAL TRENDS IN DOMESTIC EMISSIONS East-Central China NO 2 emissions in US, EU and Japan decline … while emissions growing in China Importance of long- term record! Richter et al., 2005; Fishman et al., 2008

MEASUREMENT OF NO 2 SHIPPING EMISSIONS FROM SCIAMACHY Ship emissions: large source of NO x, SO x and aerosols relevant input into marine boundary layer well defined NO 2 - patterns in Red Sea and Indian Ocean in SCIAMACHY data consistent with pattern of shipping emissions Courtesy: Andreas Richter

MAPPING OF REACTIVE HYDROCARBON EMISSIONS FROM SPACE using measurements of formaldehyde columns Millet et al. [2008] Biogenic isoprene is the main reactive hydrocarbon precursor of ozone …and a major source of organic particles hydro- carbons 340 nm formaldehyde

FITTING OF HCHO SLANT COLUMNS FROM GOME SPECTRA  s = 1.0 ± 0.3 x10 16 cm -2  s = 3.0 ± 0.4 x10 16 cm -2  s = 8.4 ± 0.7 x10 16 cm -2 Fitting uncertainty of 4x10 15 molecules cm -3 corresponds to ~ 1 ppbv HCHO in lowest 2 km Chance et al. [2000]

FORMALDEHYDE COLUMNS MEASURED BY GOME (JULY 1996) High HCHO regions reflect VOC emissions from fires, biosphere, human activity x10 16 molecules cm -2 South Atlantic Anomaly (disregard) detection limit

SEASONALVARIATION OF GOME FORMALDEHYDE COLUMNS reflects seasonal variation of biogenic isoprene emissions SEP AUG JUL OCT MAR JUN MAY APR GOME GEOS-Chem (GEIA) GOME GEOS-Chem (GEIA) Abbot et al. [2003]

A NEEDLE IN A HAYSTACK: DERIVING TROPOSPHERIC OZONE FROM TOMS [Fishman and Larson, 1987; Fishman et al., 2008] Issues: high uncertainty seasonal averages only does not extend to high latitudes

GOME JJA 1997 tropospheric columns (Dobson Units) TROPOSPHERIC OZONE OBSERVED FROM SPACE IR emission measurement from TESUV backscatter measurement from GOME Liu et al., 2006 Zhang et al., 2006 Optimal estimation (MAP) also used for retrievals of ozone profiles in the UV-vis

COMPARING SENSITIVITY OF OZONE RETRIEVALS IN IR vs UV-VIS

TOMS: SO 2 MEASUREMENTS SO 2 has an absorption band in one of the TOMS channels (which can interfere with the ozone retrieval)  If concentrations are high enough SO 2 can be retrieved Courtesy: Andreas Richter Example: volcanic eruptions such as Mount Hekla (Iceland) on Feb 27, 2000

GOME: TROPOSPHERIC BrO IN THE ANTARCTIC Low ozone events in Arctic and Antaractic Spring are correlated with high BrO in the BL (catalytic cycle for ozone destruction = parallel to strat chemistry) GOME BrO Sep , 1996 [Wagner and Platt, 1999] Courtesy: Andreas Richter GOME data provided the first information of the spatial and temporal distribution of polar springtime BrO

GLYOXAL COLUMNS: WHAT DO THEY MEAN? SCIAMACHY data suggest a large marine source of glyoxal (not seen in models) [Wittrock et al., 2006]

SCIAMACHY RETRIEVALS OF CO First measurements of vertical column of CO with sensitivity down to the surface. Unfortunately long averaging times required to combat noisy retrievals. [Buchwitz et al., 2007]

NEAR-IR CLIMATE GAS RETRIEVALS: SCIAMACHY Retrieve column averaged mixing ratios, denoted XCH 4 and XCO 2. They are computed by normalizing the measured greenhouse gas columns by the measured total airmass (number of air molecules per cm 2 ) obtained from, e.g., simultaneously measured O 2 columns. Clearly visible are major methane source regions such as wetlands (e.g. Siberia, tropics) and rice fields (e.g. China) Northern hemispheric carbon dioxide during March-June, where CO 2 is relatively high mainly due to release of CO 2 to the atmosphere by decaying vegetation, and July-October, where CO 2 is relatively low mainly due to uptake of atmospheric CO 2 by growing vegetation [Buchwitz et al., 2007]