[Show abstract][Hide abstract] ABSTRACT: Sulphur dioxide (SO2) is an important atmospheric constituent that plays a crucial role in many atmospheric processes. Volcanic eruptions are a significant source of atmospheric SO2 and its effects and lifetime depend on the SO2 injection altitude. The Infrared Atmospheric Sounding Instrument (IASI) on the Metop satellite can be used to study volcanic emission of SO2 using high-spectral resolution measurements from 1000 to 1200 cm−1 and from 1300 to 1410 (the 7.3 and 8.7 μm SO2 bands). The scheme described in Carboni et al. (2012) has been applied to measure volcanic SO2 amount and altitude for fourteen explosive eruptions from 2008 to 2012. The work includes a comparison with independent measurements: (i) the SO2 column amounts from the 2010 Eyjafjallajökull plumes have been compared with Brewer ground measurements over Europe; (ii) the SO2 plumes heights, for the 2010 Eyjafjallajökull and 2011 Grimsvötn eruptions, have been compared with CALIPSO backscatter profiles. The results of the comparisons show that IASI SO2 measurements are not affected by underlying cloud and are consistent (within the retrieved errors) with the other measurements. The series of analysed eruptions (2008 to 2012) show that the biggest emitter of volcanic SO2 was Nabro, followed by Kasatochi and Grímsvötn. Our observations also show a tendency for volcanic SO2 to be injected to the level of the tropopause during many of the moderately explosive eruptions observed. For the eruptions observed, this tendency was independent of the maximum amount of SO2 (e.g. 0.2 Tg for Dalafilla compared with 1.6 Tg for Nabro) and of the volcanic explosive index (between 3 and 5).
[Show abstract][Hide abstract] ABSTRACT: The MIPAS spectrometer onboard the Envisat platform observed infrared emission from the Earth's limb between 2002 and 2012. It recorded high-resolution spectra during day and night, from pole to pole and between 6 and 70 km altitude in the nominal measurement mode or up to 170 km in special measurement modes, producing daily more than 1000 vertical profiles of various trace gases. The operational Level-2 data are processed by ESA/DLR but there exist three other, independent research Level-2 processors that are hosted by ISAC-CNR/University of Bologna, Oxford University, and KIT IMK/IAA. All four Level-2 processors rely on the same Level-1b data provided by ESA but their retrieval schemes differ. As part of ESA's Ozone Climate Change Initiative project, an intercomparison of the four MIPAS processors took place, in which vertical ozone profiles retrieved by these four processors from MIPAS nominal mode measurements were compared for 2007 and 2008. We present the results of this comparison exercise, which consisted of five parts: an information content study of the vertical averaging kernels, an intercomparison of zonal seasonal means and spreads, a determination of biases through comparison to ozonesonde and lidar measurements, a comparison to other satellite records (bias estimation and precision assessment with respect to ACE-FTS and Aura-MLS data), and a geophysical validation of the provided error bars using MIPAS–MIPAS collocations.
No preview · Article · Jun 2015 · Remote Sensing of Environment
[Show abstract][Hide abstract] ABSTRACT: This work presents a new iterative method for optimally selecting a vertical retrieval grid based on the location of the information content while accounting for inter-level correlations. Sample atmospheres initially created to parametrise the RTTOV forward model are used to compare the presented iterative vertical selection method with 5 two other common approaches, which are using levels of equal vertical spacing and selecting levels based on the cumulative trace of the averaging kernel matrix (AKM). This new method is shown to outperform compared methods for synthesized profile retrievals with IASI of temperature, H2O, O3 , CH4 , and CO. However, the benefits of using the more complicated iterative approach compared to the simpler method of referencing the cumulative trace of the AKM are slight and may not justify the added effort. Furthermore, comparing retrievals using a globally optimized static grid vs. an atmosphere specific one shows that a static grid is likely appropriate for retrievals of O3 , CH4 , and CO. However, developers of temperature and H2O retrieval schemes may at least consider using adaptive or location specific vertical retrieval grids.
[Show abstract][Hide abstract] ABSTRACT: The vast majority of emissions of fluorine-containing molecules are anthropogenic in nature, e.g. chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), and hydrofluorocarbons (HFCs). These molecules slowly degrade in the atmosphere, leading to the formation of HF, COF2 , and COClF, which are the main fluorine-containing species in the stratosphere. Ultimately both COF2 and COClF further degrade to form HF, an almost permanent reservoir of stratospheric fluorine due to its extreme stability. Carbonyl fluoride (COF2) is the second-most abundant stratospheric "inorganic" fluorine reservoir, with main sources being the atmospheric degradation of CFC-12 (CCl2F2), HCFC-22 (CHF2Cl), and CFC-113 (CF2ClCFCl2). This work reports the first global distributions of carbonyl fluoride in the Earth's atmosphere using infrared satellite remote-sensing measurements by the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS), which has been recording atmospheric spectra since 2004, and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, which recorded thermal emission atmospheric spectra between 2002 and 2012. The observations reveal a high degree of seasonal and latitudinal variability over the course of a year. These have been compared with the output of SLIMCAT, a state-of-the-art three-dimensional chemical transport model. In general the observations agree well with each other, although MIPAS is biased high by as much as ~30 %, and compare well with SLIMCAT. Between January 2004 and September 2010 COF2 grew most rapidly at altitudes above ~25 km in the southern latitudes and at altitudes below ~25 km in the northern latitudes, whereas it declined most rapidly in the tropics. These variations are attributed to changes in stratospheric dynamics over the observation period. The overall COF2 global trend over this period is calculated as 0.85 ± 0.34 (MIPAS), 0.30 ± 0.44 (ACE), and 0.88 %/year (SLIMCAT).
Full-text · Article · Nov 2014 · Atmospheric Chemistry and Physics
[Show abstract][Hide abstract] ABSTRACT: High-resolution infrared sounders, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the current MetOp series of satellites, produce several orders of magnitude more data per location than previous instruments used in operational retrieval and data assimilation schemes. Using the full spectrum (8641 channels for IASI) is impractical and a common approach is to identify a subset of channels which, ideally, conveys the most information on the target parameters (e.g. atmospheric temperature and water vapour) but using a relatively small number of measurements. Representing the problem as a one-dimensional retrieval, optimal estimation provides an efficient framework for channel selection, and is the basis of several current schemes. However, while modelling the propagation of random (spectrally uncorrelated) errors into the retrieval, the standard algorithm does not allow for spectrally correlated errors, particularly arising from the radiative transfer modelling, which are often the limiting factor in retrieval accuracy. Such errors are either ignored or represented only approximately during the selection. This article describes a modification to the standard algorithm which allows spectrally correlated errors to be properly modelled, and quantified, within the channel selection process. Comparing the results with an established selection scheme shows that significant improvements can be obtained when retrieving temperature regarding water vapour as an error term, but are less dramatic when both are retrieved together. The concept of ‘total’ information available from an IASI spectrum is also re-assessed.
No preview · Article · Oct 2014 · Quarterly Journal of the Royal Meteorological Society
[Show abstract][Hide abstract] ABSTRACT: Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid-to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified.
In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) Initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available.
This summary presents an overview of stratospheric ozone profile measurement data sets (ground and satellite based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information for each data set is also given.
Full-text · Article · May 2014 · Atmospheric Measurement Techniques
[Show abstract][Hide abstract] ABSTRACT: The Infrared Atmospheric Sounding Interferometer (IASI), on board both the MetOp-A and MetOp-B platforms, is a Fourier transform spectrometer covering the mid-infrared (IR) from 645-2760cm −1 (3.62-15.5 µm) with a spectral resolution of 0.5cm −1 (apodised) and a pixel diameter at nadir of 12km. These characteristics allow global coverage to be achieved twice daily for each instrument and make IASI a very useful tool for the observation of larger aerosol particles (such as desert dust and volcanic ash) and the tracking of volcanic plumes. In recent years, following the eruption of Eyjafjallajökull, interest in the the ability to detect and characterise volcanic ash plumes has peaked due to the hazards to aviation. The thermal infrared spectra shows a rapid variation with wavelength due to absorption lines from atmospheric and volcanic gases as well as broad scale features principally due to particulate absorption. The ash signature depends upon both the composition and size distribution of ash particles as well as the altitude of the volcanic plume. To retrieve ash properties, IASI brightness temperature spectra are analysed using an optimal estimation retrieval scheme and a forward model based on RTTOV. Initially, IASI pixels are flagged for the presence of volcanic ash using a linear retrieval detection method based on departures from a background state. Given a positive ash signal, the RTTOV output for a clean atmosphere (containing atmospheric gases but no cloud or aerosol/ash) is combined with an ash/cloud layer using the same scheme as for the Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. The retrieved parameters are ash optical depth (at a reference wavelength of 550nm), ash effective radius, layer altitude and surface temperature.
[Show abstract][Hide abstract] ABSTRACT: The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument which operated on the Envisat satellite from 2002-2012 is a Fourier transform spectrometer for the measurement of high-resolution gaseous emission spectra at the Earth's limb. It operates in the near- to mid-infrared, where many of the main atmospheric trace gases have important emission features. The initial operational products were profiles of Temperature, H2O, O3, CH4, N2O, HNO3, and NO2, and this list was recently extended to include N2O5, ClONO2, CFC-11 and CFC-12. Here we present preliminary results of retrievals of the third set of species under consideration for inclusion in the operational processor: HCN, CF4, HCFC-22, COF2 and CCl4.
No preview · Article · Jan 2014 · Annals of geophysics = Annali di geofisica
[Show abstract][Hide abstract] ABSTRACT: The remote sensing of volcanic ash plumes from space can provide a warning of an aviation hazard and knowledge on eruption processes and radiative effects. In this paper new algorithms are presented to provide volcanic plume properties from measurements by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Advanced Along Track Scanning Radiometer (AATSR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). A challenge of remote sensing is to provide near-real-time methods to identify, and so warn of, the presence of volcanic ash. To achieve this, a singular vector decomposition method has been developed for the MIPAS instrument on board the Environmental Satellite. This method was applied to observations of the ash clouds from the eruptions of Nabro and the Puyehue–Cordon Caulle in 2011 and led to a sensitive volcanic signal flag which was capable of tracking changes in the volcanic signal spectra as the plume evolved. A second challenge for remote sensing is to identify the ash plume height. This is a critical parameter for the initialization of algorithms that numerically model the evolution and transport of a volcanic plume. As MIPAS is a limb sounder, the identification of ash also provides an estimate of height provided the plume is above about 6 km. This is complemented by a new algorithm, Stereo Ash Plume Height Retrieval Algorithm, that identifies plume height using the parallax between images provided by Along Track Scanning Radiometer-type instruments. The algorithm was tested on an image taken at 14:01 GMT on 6 June 2011 of the Puyehue–Cordon Caulle eruption plume and gave a height of 11.9 +/- 1.4 km, which agreed with the value derived from the location of the plume shadow (12.7 +/-1.8 km). This plume height was similar to the height observed by MIPAS (12+1.5 km) at 02:56 GMT on 6 June. The quantitative use of satellite imagery and the full exploitation of high-resolution spectral measurements of ash depends upon knowing the optical properties of the observed ash. Laboratory measurements of ash from the 1993 eruption of Mt Aso, Japan have been used to determine the refractive indices from 1 to 20 um. These preliminary measurements have spectral features similar to ash values that have been used to date, albeit with slightly different positions and strengths of the absorption bands. The refractive indices have been used to retrieve ash properties (plume height, optical depth and ash effective radius) from AATSR and SEVIRI instruments using two versions of Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. For AATSR a new ash cloud type was used in ORAC for the analysis of the plume from the 2011 Eyjafjallajoekull eruption. For the first c. 500 km of the plume ORAC gave values for plume height of 2.5–6.5 km, optical depth 1–2.5 and effective radius 3–7 mm, which are in agreement with other observations. A weakness of the algorithm occurs when underlying cloud invalidates the assumption of a single cloud layer. This is rectified in a modified version of ORAC applied to SEVIRI measurements. In
this case an extra model of a cloud underlying the ash plume was included in the range of applied models. In cases where the plume overlay cloud, this new model worked well, showing good agreement with correlative Cloud–Aerosol Lidar with Orthogonal Polarization observations.
Full-text · Article · Nov 2013 · Geological Society London Special Publications
[Show abstract][Hide abstract] ABSTRACT: The MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument on the Envisat (Environmental satellite) satellite has provided vertical profiles of the atmospheric composition on a global scale for almost ten years. The MIPAS mission is divided in two phases: the full resolution phase, from 2002 to 2004, and the optimized resolution phase, from 2005 to 2012, which is characterized by a finer vertical and horizontal sampling attained through a reduction of the spectral resolution.
While the description and characterization of the products of the ESA processor for the full resolution phase has been already described in previous papers, in this paper we focus on the performances of the latest version of the ESA (European Space Agency) processor, named ML2PP V6 (MIPAS Level 2 Prototype Processor), which has been used for reprocessing the entire mission. The ESA processor had to perform the operational near real time analysis of the observations and its products needed to be available for data assimilation. Therefore, it has been designed for fast, continuous and automated analysis of observations made in quite different atmospheric conditions and for a minimum use of external constraints in order to avoid biases in the products.
The dense vertical sampling of the measurements adopted in the second phase of the MIPAS mission resulted in sampling intervals finer than the instantaneous field of view of the instrument. Together with the choice of a retrieval grid aligned with the vertical sampling of the measurements, this made ill-conditioned the retrieval problem of the MIPAS operational processor. This problem has been handled with minimal changes to the original retrieval approach but with significant improvements nonetheless. The Levenberg-Marquardt method, already present in the retrieval scheme for its capability to provide fast convergence for nonlinear problems, is now also exploited for the reduction of the ill-conditioning of the inversion. An expression specifically designed for the regularizing Levenberg-Marquardt method has been implemented for the computation of the covariance matrices and averaging kernels of the retrieved products. The regularization of the Levenberg-Marquardt method is controlled by the convergence criteria and is deliberately kept weak. The resulting oscillations of the retrieved profile are a posteriori damped by an innovative self-adapting Tikhonov regularization. The convergence criteria and the weakness of the self-adapting regularization ensure that minimum constraints are used and the best vertical resolution obtainable from the measurements is achieved in all atmospheric conditions.
Random and systematic errors, as well as vertical and horizontal resolution are compared in the two phases of the mission for all products, namely: temperature, H2O, O3, HNO3, CH4, N2O, NO2, CFC-11, CFC-12, N2O5 and ClONO2. The use in the two phases of the mission of different optimized sets of spectral intervals ensures that, despite the different spectral resolutions, comparable performances are obtained in the whole MIPAS mission in terms of random and systematic errors, while the vertical resolution and the horizontal resolution are significantly better in the case of the optimized resolution measurements.
[Show abstract][Hide abstract] ABSTRACT: Currently, most of the high-spectral-resolution infrared limb sounders
use subsets of the recorded spectra (microwindows) in their retrieval
schemes to reduce the computing time of rerunning the radiative transfer
model. A fast linear retrieval scheme is described which allows the
whole spectral signature of the target molecule to be used. We determine
that pressure and temperature retrievals can be treated linearly up to a
20% difference between the atmospheric state and the linearisation point
for a 3% error margin and up to 10 K "difference" for a 3 K error margin
near the stratopause and less than 0.5 K elsewhere. Assuming perfect pT
knowledge, CH4 retrievals can be be treated linearly up to a
20% CH4 concentration "difference" for a 2% error margin. As
an example, this technique is implemented for the Michelson
Interferometer for Passive Atmospheric Sounding instrument, but it is
applicable to any high-resolution limb sounder.
Preview · Article · May 2013 · Atmospheric Measurement Techniques
[Show abstract][Hide abstract] ABSTRACT: The IASI high resolution infrared spectra is exploited to study volcanic
emission of ash and sulphur dioxide (SO2). IASI is a Fourier transform
spectrometer that covers the spectral range 645 to 2760 cm-1 (3.62-15.5
μm). The IASI field of view consists of four circles of 12 km inside
a square of 50 x 50 km, and nominally it can achieve global coverage in
12 hours. The thermal infrared spectra of volcanic plumes shows a rapid
variation with wavelength due to absorption lines from atmospheric and
volcanic gases as well as broad scale features principally due to
particulate absorption. IASI spectra also contain information about the
atmospheric profile (temperature, gases, aerosol and cloud) and
radiative properties of the surface. In particular the ash signature
depends on the composition and size distribution of ash particles as
well on their altitude. The sulphur dioxide signature depends on SO2
amount and vertical profile. The results from a new algorithm for the
retrieval of sulphur dioxide (SO2) from the Infrared Atmospheric
Sounding Interferometer (IASI) data will be presented. The SO2 retrieval
follows the method of Carboni et al. (2012) and retrieves SO2 amount and
altitude together with a pixel by pixel comprehensive error budget
analysis. IASI brightness temperature spectra are analysed, to retrieve
ash properties, using an optimal estimation retrieval scheme and a
forward model based on RTTOV. The RTTOV output for a clean atmosphere
(containing gas but not cloud or aerosol/ash) will be combined with an
ash layer using the same scheme as for the Oxford-RAL Retrieval of
Aerosol and Cloud (ORAC) algorithm. We exploit the IASI measurements in
the atmospheric window spectral range together with the SO2 absorption
bands (at 7.3 and 8.7 μm) to study the evolution of ash and SO2
volcanic plume for recent volcanic eruptions case studies. Particular
importance is given to investigation of mismatching between the forward
model and IASI measurements which can be due, for example, to imperfect
knowledge of ash optical properties.
[Show abstract][Hide abstract] ABSTRACT: Sulphur dioxide (SO2) is an important atmospheric constituent that plays
a crucial role in many atmospheric processes. In the troposphere its
production leads to the acidification of rainfall while in the
stratosphere it oxidises to form a stratospheric H2SO4 haze that can
affect climate for several years. Volcanoes contribute about 1/3 to the
tropospheric sulphur burden of which the majority is SO2. However, the
absolute amount of the annual SO2 volcanic emission is both poorly
constrained, and highly variable. The uncertainty in SO2 released arises
for the stochastic nature of volcanic processes, very little or no
surface monitoring of many volcanoes (so their contribution to annual
emission is extremely uncertain) and from huge uncertainty in the
contribution of volcanic sulphur emitted by quiescent (non-explosive)
degassing. Volcanic SO2 retrievals from satellite data in the thermal
infrared spectrum are based on two regions of SO2 absorption around 7.3
and 8.7 μm. The strongest SO2 band is at 7.3 μm and is contained
in a strong water vapour (H2O) absorption band and is not very sensitive
to emission from the surface and lower atmosphere. Above the lower
atmosphere this band contains valuable information on the vertical
profile of SO2. Fortunately differences between the H2O and SO2 emission
spectra allow the signals from the two gases to be decoupled in high
resolution measurements. The 8.7 μm absorption feature is in an
atmospheric window so it contains information on SO2 from throughout the
column. The development of an SO2 retrieval algorithm that uses
measurements from 1000 to 1200 cm-1 and from 1300 to 1410 cm-1 (the 7.3
and 8.7 μm SO2 bands) made by the Infrared Atmospheric Sounding
Instrument (IASI) (Carboni et al., 2012) on the MetOp satellite permits
the quantification of SO2 amount and the estimate of the plume altitude.
This retrieval scheme determines the column amount and effective
altitude of the SO2 plume with high precision (up to 0.3 DU error in SO2
amount if the plume is near the tropopause) and can retrieve
informations in the lower troposphere. There are several advantages of
the IASI retrievals: (1) IASI makes measurements both day and night (so
has global coverage every 12 hours), (2) the IASI retrieval does not
assume plume height but retrieves an altitude for maximum SO2 amount
(under the assumption that the vertical concentration of SO2 follows a
Gaussian distribution). (3) IASI retrievals is not affected by
underlying cloud (if the SO2 is within or below an ash or cloud layer
its signal will be masked and the retrieval will underestimate the SO2
amount, in the case of ash this is a posteriori discernible by the cost
function value) (4) A comprehensive error budget for every pixel is
included in the retrieval. This is derived from an error covariance
matrix that is based on the SO2-free climatology of the differences
between the IASI and forward modelled spectra. In this work we present
the results for recent volcanic eruptions and we will demonstrate the
potential to monitor quiescent degassing from some volcano.
[Show abstract][Hide abstract] ABSTRACT: Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified
In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available.
This summary presents an overview of stratospheric ozone profile measurement data sets (ground- and satellite-based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information is for each data set is also given.
[Show abstract][Hide abstract] ABSTRACT: Currently most of the high spectral resolution infrared limb sounders
use subsets of the recorded spectra (microwindows) in their retrieval
schemes to reduce the computing time of rerunning the radiative transfer
model. A fast linear retrieval scheme is described which allows the
whole spectral signature of the target molecule to be used. We determine
how close the linearisation point needs to be to the solution in order
to fall in the linear regime and also suggest an adjustment to the
forward model and Jacobians to propagate the change in pressure and
temperature on the gas concentration retrievals. As an example, this
technique is implemented for the Michelson Interferometer for Passive
Atmospheric Sounding instrument, but it is applicable to any high
resolution limb sounder.
[Show abstract][Hide abstract] ABSTRACT: A new optimal estimation algorithm for the retrieval of sulphur dioxide
(SO2) has been developed for the Infrared Atmospheric
Sounding Interferometer (IASI) using the channels between 1000-1200 and
1300-1410 cm-1. These regions include the two SO2
absorption bands centred at about 8.7 and 7.3 μm (the
ν1 and ν3 bands respectively). The retrieval
assumes a Gaussian SO2 profile and returns the SO2
column amount in Dobson units and the altitude of the plume in millibars
(mb). Forward modelled spectra (against which the measurements are
compared) are based on the Radiative Transfer for TOVS (RTTOV) code. In
our implementation RTTOV uses atmospheric profiles from European Centre
for Medium-Range Weather Forecasts (ECMWF) meteorological data. The
retrieval includes a comprehensive error budget for every pixel derived
from an error covariance matrix that is based on the SO2-free
climatology of the differences between the IASI and forward modelled
spectra. The IASI forward model includes the ability to simulate a cloud
or ash layer in the atmosphere. This feature is used to illustrate that:
(1) the SO2 retrieval is not affected by underlying cloud but
is affected if the SO2 is within or below a cloud layer; (2)
it is possible to discern if ash (or other atmospheric constituents not
considered in the error covariance matrix) affects the retrieval using
quality control based on the fit of the measured spectrum by the forward
modelled spectrum. In this work, the algorithm is applied to follow the
behaviour of SO2 plumes from the Eyjafjallajökull
eruption during April and May 2010. From 14 April to 4 May (during Phase
I and II of the eruption) the total amount of SO2 present in
the atmosphere, estimated by IASI measurements, is generally below 0.02
Tg. During the last part of the eruption (Phase III) the values are an
order of magnitude higher, with a maximum of 0.18 Tg measured on the
afternoon of 7 May.
Full-text · Article · Dec 2012 · Atmospheric Chemistry and Physics
[Show abstract][Hide abstract] ABSTRACT: The infrared limb spectra of the Michelson Interferometer for Passive
Atmospheric Sounding (MIPAS) on board the Envisat satellite include
detailed information on tropospheric clouds and polar stratospheric
clouds (PSC). However, no consolidated cloud product is available for
the scientific community. Here we describe a fast prototype processor
for cloud parameter retrieval from MIPAS (MIPclouds). Retrieval of
parameters such as cloud top height, temperature, and extinction are
implemented, as well as retrieval of microphysical parameters, e.g.
effective radius and the integrated quantities over the limb path
(surface area density and volume density). MIPclouds classifies clouds
as either liquid or ice cloud in the upper troposphere and polar
stratospheric clouds types in the stratosphere based on statistical
combinations of colour ratios and brightness temperature differences.
Comparison of limb measurements of clouds with model
results or cloud parameters from nadir looking instruments is often
difficult due to different observation geometries. We therefore
introduce a new concept, the limb-integrated surface area density path
(ADP). By means of validation and radiative transfer calculations of
realistic 2-D cloud fields as input for a blind test retrieval (BTR), we
demonstrate that ADP is an extremely valuable parameter for future
comparison with model data of ice water content, when applying limb
integration (ray tracing) through the model fields. In addition, ADP is
used for a more objective definition of detection thresholds of the
applied detection methods. Based on BTR, a detection threshold of ADP =
107 μm2 cm-2 and an ice water
content of 10-5 g m-3 is estimated, depending on
the horizontal and vertical extent of the cloud. Intensive
validation of the cloud detection methods shows that the limb-sounding
MIPAS instrument has a sensitivity in detecting stratospheric and
tropospheric clouds similar to that of space- and ground-based lidars,
with a tendency for higher cloud top heights and consequently higher
sensitivity for some of the MIPAS detection methods. For the high cloud
amount (HCA, pressure levels below 440 hPa) on global scales the
sensitivity of MIPAS is significantly greater than that of passive nadir
viewers. This means that the high cloud fraction will be underestimated
in the ISCCP dataset compared to the amount of high clouds deduced by
MIPAS. Good correspondence in seasonal variability and geographical
distribution of cloud occurrence and zonal means of cloud top height is
found in a detailed comparison with a climatology for subvisible cirrus
clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II)
limb sounder. Overall, validation with various sensors shows the need to
consider differences in sensitivity, and especially the viewing
geometries and field-of-view size, to make the datasets comparable (e.g.
applying integration along the limb path through nadir cloud fields).
The simulation of the limb path integration will be an important issue
for comparisons with cloud-resolving global circulation or chemical
Full-text · Article · Aug 2012 · ATMOSPHERIC CHEMISTRY AND PHYSICS
[Show abstract][Hide abstract] ABSTRACT: The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a mid-infrared emission spectrometer which is part of the core payload of the Envisat satellite, launched by ESA in March 2002. It provides unique observations of the atmospheric spectral radiances in the 4.15 - 14.6 mu m spectral interval with innovative limb scanning capabilities for the three dimensional observation of the atmospheric composition and processes. The species, the processes and events that have been studied with this instrument in its 10 years of operation are briefly reviewed.
[Show abstract][Hide abstract] ABSTRACT: The recent advent of very high spectral resolution measurements by the Fourier Transform Spectrometer (FTS) on board the Greenhouse gases Observing SATellite (GOSAT) platform has made possible the retrieval of sun-induced terrestrial chlorophyll fluorescence (Fs) on a global scale. The basis for this retrieval is the modeling of the in-filling of solar Fraunhofer lines by fluorescence. This contribution to the field of space-based carbon cycle science presents an alternative method for the retrieval of Fs from the Fraunhofer lines resolved by GOSAT-FTS measurements. The method is based on a linear forward model derived by a singular vector decomposition technique, which enables a fast and robust inversion of top-of-atmosphere radiance spectra. Retrievals are performed in two spectral micro-windows (∼ 2-3 nm width) containing several strong Fraunhofer lines. The statistical nature of this approach allows to avoid potential retrieval errors associated with the modeling of the instrument line shape or with a given extraterrestrial solar irradiance data set. The method has been tested on 22 consecutive months of global GOSAT-FTS measurements. The fundamental basis of this Fs retrieval approach and the results from the analysis of the global Fs data set produced with it are described in this work. Among other findings, the data analysis has shown (i) a very good comparison of Fs intensity levels and spatial patterns with the state-of-the-art physically-based Fs retrieval approach described in Frankenberg et al. (2011a), (ii) the overall good agreement between Fs annual and seasonal patterns and other space-based vegetation parameters, (iii) the need for a biome-dependent scaling from Fs to gross primary production, and (iv) the apparent existence of strong directional effects in the Fs emission from forest canopies. These results reinforce the confidence in the feasibility of Fs retrievals with GOSAT-FTS and open several points for future research in this emerging field.
Full-text · Article · Jun 2012 · Remote Sensing of Environment