•CO2 spectroscopy and forward modelling accuracy for the ν2 and ν3 absorption bands.•CO2 retrieval performance using the whole IASI spectral coverage, 645–2760 cm−1.•Four years long record of IASI ...retrievals and comparison with in situ observations.•IASI data and products available on request.
Spectroscopy and forward modelling consistency and accuracy in the ν2 and ν3 fundamental absorption bands of CO2 have been assessed through IASI (Infrared Atmospheric Sounder Interferometer) spectra recorded over the Pacific Ocean Manus island (Papua New Guinea) validation station. Until 2014, the Manus station has been operated within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and has provided high quality radiosonde observations for temperature and water vapour. Because of its longitude and close to Equator position, the radiosonde regular launches at 00:00 and 12:00 UTC naturally coincide with Metop/IASI overpasses. Thus, IASI soundings and radiosonde observations can be co-located within a time slot of 30 min and a spatial distance of less than 50 km. Considering that radiosonde observations are limited to the troposphere and lower stratosphere, the usual analysis of spectral residuals (Observations-Calculations) yields the possibility to directly validate the spectroscopy of CO2 channels, which are sensitive to the troposphere. Furthermore, the combined use of radiosonde and ECMWF (European Centre for Medium range Weather Forecasts) analysis, to extend the radiosonde profiles in the upper atmosphere, has allowed us to check the CO2 spectroscopic consistency in spectral channels that are sensitive to the stratosphere. Our analysis shows that state-of-art CO2 spectroscopy and forward modelling have errors that are comparable or better than the IASI radiometric noise. This level of accuracy has proved to be enough for providing good CO2 retrievals. The fidelity of CO2 retrieval has been assessed by using in situ observations from the HIAPER (High-performance Instrument Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) flights and the Mauna Loa (Hawaii) validation station. An analysis of a four-year record of IASI soundings (2014–2017) over Mauna Loa shows that the correlation between IASI retrieved CO2 column amounts and in situ observations is ≈ 0.95. The IASI derived CO2 also shows trend and seasonality, which are consistent with those derived from in situ observations. The retrieval analysis has also been extended to N2O, which plays an important role in assessing the consistency of the forward model in the N2O/CO2ν3 band. We have found that N2O estimated from IASI radiances is accurate enough to derive a satellite growth rate consistent with in situ observations of less than 1 ppbv per year (but with some interannual variations).
A Kalman filter-based approach for the physical retrieval of surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager) infrared observations has been developed ...and validated against in situ and satellite observations. Validation for land has been provided based on in situ observations from the two permanent stations at Evora and Gobabeb operated by Karlsruhe Institute of Technology (KIT) within the framework of EUMETSAT's Satellite Application Facility on Land Surface Analysis (LSA SAF). Sea surface retrievals have been intercompared on a broad spatial scale with equivalent satellite products (MODIS, Moderate Resolution Imaging Spectroradiometer, and AVHRR, Advanced Very High Resolution Radiometer) and ECMWF (European Centre for Medium-Range Weather Forecasts) analyses. For surface temperature, the Kalman filter yields a root mean square accuracy of ≈ ±1.5 °C for the two land sites considered and ≈ ±1.0 °C for the sea. Comparisons with polar satellite instruments over the sea surface show nearly zero temperature bias. Over the land surface the retrieved emissivity follows the seasonal vegetation cycle and permits identification of desert sand regions using the SEVIRI channel at 8.7 μm due to the strong quartz reststrahlen bands around 8–9 μm. Considering the two validation stations, we have found that emissivity retrieved in SEVIRI channel 10.8 μm over the gravel plains of the Namibian desert is in excellent agreement with in situ observations. Over Evora, the seasonal variation of emissivity with vegetation is successfully retrieved and yields emissivity values for green and dry vegetation that are in good agreement with spectral library data. The algorithm has been applied to the SEVIRI full disk, and emissivity maps on that global scale have been physically retrieved for the first time.
Since data from the Infrared Atmospheric Sounding Interferometer (IASI) became available in 2007, a number of papers have appeared in the literature which have reported relatively large discrepancies ...between IASI spectra and forward calculations in the centre of the CO2 Q-branch at 667 cm−1. In this paper we show that these discrepancies are primarily due to errors in the temperature profiles used in the forward calculations. In particular, we have used forecasts of temperature profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) to demonstrate that, for the case study considered in this paper, these profiles are affected by systematic errors of the order of ≈10 K at the level of the stratopause. To derive the magnitude and the spatial location of the systematic errors in the temperature profile, we have carried out forward/inverse calculations for a number of clear-sky, daytime, IASI tropical soundings over the sea. The forward calculations have been performed using atmospheric state vectors which have been obtained either from the direct inversion of the IASI radiances or from space-time co-located profiles derived from radiosonde observations and from the ECMWF model. To rule out any effect due to the accuracy of the forward model, we have performed the forward calculations using two independent models. The sensitivity of the temperature biases to the variability of the CO2 profile and to spectroscopy errors has also been studied.
The Empirical Mode Decomposition (EMD) is a fully non‐parametric analysis of frequency modes and trends in a given series that is based on the data alone. We have devised an improved strategy based ...on a series of best practices to use EMD successfully in the analysis of the monthly time series of carbonyl sulfide (OCS) atmospheric mole fractions measured at NOAA network stations (2000–2020). Long‐term trends and intra‐ and inter‐annual variability has been assessed. After a phase of generally increasing mole fractions up to 2015, with a temporary decline around 2009, we found that the OCS atmospheric mole fraction subsequently decreased at all stations, reflecting a recent imbalance in its total sources and losses. Our analysis has revealed a characteristic time scale for variation of 8–10 years. The variance associated with this long‐term behavior ranges from ∼ $\sim $15% to 40% of the total strength of the signal, depending on location. Apart from this complex long‐term behavior, the OCS time series show a strong annual cycle, which primarily results from the well‐known OCS uptake by vegetation. In addition, we have also found one more frequency of minor variance intensity in the measured mole fraction time‐history, which corresponds to periods in the range of 2–3 years. This inter‐annual variability of OCS may be linked to the Quasi‐Biennial Oscillation.
Plain Language Summary
The Empirical Mode Decomposition has arisen as a new paradigm for the processing and analysis of time series. The tool has been applied to multi‐year mole fraction measurements of an atmospheric gas, carbonyl sulfide (OCS), which has important implications for understanding and analyzing the carbon cycle. OCS is the most abundant sulfur‐containing trace gas in the atmosphere and has recently emerged as a putative proxy for the terrestrial photosynthetic uptake of CO2 because OCS and CO2 have the same diffusion pathway into leaves. The study has analyzed OCS at 14 cooperative stations, which are distributed all around the world. We have found a characteristic time scale for 8–10 years variation. Apart from this complex long‐term behavior, the OCS time series show a robust yearly cycle, primarily from OCS uptake by vegetation. Finally, we have also found one more frequency, which corresponds to periods in the range of 2–3 years. This inter‐annual variability of OCS may be linked to the Quasi‐Biennial Oscillation, which is an almost periodic oscillation of the winds of the equatorial stratosphere.
Key Points
Atmospheric carbonyl sulfide has decreased at NOAA network stations in recent years
Time Series Analysis and trend identification
Empirical Mode Decomposition identified many characteristic frequencies of variability, some compatible with Quasi Biennal Oscillation
The Far-infrared Earth Harries, J.; Carli, B.; Rizzi, R. ...
Reviews of geophysics (1985),
December 2008, Letnik:
46, Številka:
4
Journal Article
Recenzirano
The paper presents a review of the far‐infrared (FIR) properties of the Earth's atmosphere and their role in climate. These properties have been relatively poorly understood, and it is one of the ...purposes of this review to demonstrate that in recent years we have made great strides in improving this understanding. Seen from space, the Earth is a cool object, with an effective emitting temperature of about 255 K. This contrasts with a global mean surface temperature of ∼288 K and is due primarily to strong absorption of outgoing longwave energy by water vapor, carbon dioxide, and clouds (especially ice). A large fraction of this absorption occurs in the FIR, and so the Earth is effectively a FIR planet. The FIR is important in a number of key climate processes, for example, the water vapor and cloud feedbacks (especially ice clouds). The FIR is also a spectral region which can be used to remotely sense and retrieve atmospheric composition in the presence of ice clouds. Recent developments in instrumentation have allowed progress in each of these areas, which are described, and proposals for a spaceborne FIR instrument are being formulated. It is timely to review the FIR properties of the clear and cloudy atmosphere, the role of FIR processes in climate, and its use in observing our planet from space.
•Among the first works showing Carbonyl sulphide (OCS) retrievals from IASI.•Case study based on two years long record of IASI soundings.•Comparison with in situ and airborne OCS observations.
The ...capability of IASI (Infrared Atmospheric Sounder Interferometer) for retrieving OCS has been assessed with a series of retrieval experiments, which have been carried out with a physical forward/inverse scheme, which can exploit the full IASI information content. We use random projections to reduce the dimensionality of the data space and to have a unified treatment of instrument and forward model errors. The OCS column amount is retrieved both by using a scaling parameterization of the profile and a non-parametric approach, in which we first derive the OCS profile and then its global amount is estimated by a proper integration over the profile. IASI OCS retrievals are compared to in situ flask observations at the Mauna Loa validation station, Hawaii, USA and observations from HIAPER Pole-to-Pole flights. We have found that the best way to retrieve OCS is through the non-parametric approach, which shows that the OCS cycle amplitude, phase and mean abundance can be retrieved with high accuracy for night and day time soundings. In fact, IASI captures the OCS seasonal cycle, with an overall difference with in situ observations, which is of the order of ≈ 1 pptv, provided we use HITRAN2012 OCS line compilation. HITRAN2008, which has been used in previous studies, is indeed affected by spectroscopic errors as far as OCS is concerned, which results in heavily biased OCS retrievals. Although the present paper is mostly intended to assess IASI retrievals over ocean, a demonstrative application to above land surface is considered as well. Preliminary results suggest that IASI can recover the OCS cycle in ecosystems governed by leaf and/or soil sources/sinks.
We introduce a classification method (cumulative discriminant analysis) of the discriminant analysis type to discriminate between cloudy and clear-sky satellite observations in the thermal infrared. ...The tool is intended for the high-spectral-resolution infrared sounder (IRS) planned for the geostationary METEOSAT (Meteorological Satellite) Third Generation platform and uses IASI (Infrared Atmospheric Sounding Interferometer) data as a proxy. The cumulative discriminant analysis does not introduce biases intrinsic with the approximation of the probability density functions and is flexible enough to adapt to different strategies to optimize the cloud mask. The methodology is based on nine statistics computed from IASI spectral radiances, which exploit the high spectral resolution of the instrument and which effectively summarize information contained within the IASI spectrum. A principal component analysis prior step is also introduced, which makes the problem more consistent with the statistical assumptions of the methodology. An initial assessment of the scheme is performed based on global and regional IASI real data sets and cloud masks obtained from AVHRR (Advanced Very High Resolution Radiometer) and SEVIRI (Spinning Enhanced Visible and Infrared Imager) imagers. The agreement with these independent cloud masks is generally well above 80 %, except at high latitudes in the winter seasons.
The high temporal resolution of data acquisition by geostationary satellites and their capability to resolve the diurnal cycle allows for the retrieval of a valuable source of information about ...geophysical parameters. In this paper, we implement a Kalman filter approach to apply temporal constraints on the retrieval of surface emissivity and temperature from radiance measurements made from geostationary platforms. Although we consider a case study in which we apply a strictly temporal constraint alone, the methodology will be presented in its general four-dimensional, i.e., space-time, setting. The case study we consider is the retrieval of emissivity and surface temperature from SEVIRI (Spinning Enhanced Visible and Infrared Imager) observations over a target area encompassing the Iberian Peninsula and northwestern Africa. The retrievals are then compared with in situ data and other similar satellite products. Our findings show that the Kalman filter strategy can simultaneously retrieve surface emissivity and temperature with an accuracy of ± 0.005 and ± 0.2 K, respectively.
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