A principal component based version of the RTTOV fast radiative transfer model

Matricardi, Marco

doi:10.1002/qj.680

Cited by 43 publications

(38 citation statements)

References 26 publications

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“…Jolliffe, 2002), the use of which to reduce the dimensionality of the radiative transfer equation has been exemplified by Masiello and Serio (2004) and Liu et al (2007Liu et al ( , 2009). Today, forward models for IASI capable of computing PC scores directly are available (see, for example, Masiello and Serio, 2004;Liu et al, 2006;Matricardi, 2010), which could speed up the process of adapting the assimilation process for IASI PC scores. Such assimilation experiments are currently performed at ECMWF (M. Matricardi, personal communication 2010).…”

Section: Introductionmentioning

confidence: 99%

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

Masiello

Serio

Antonelli

2011

Quart J Royal Meteoro Soc

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The problem of reducing the dimensionality of infrared atmospheric sounding interferometer (IASI) data space through a suitable transform and performing the retrieval process for thermodynamical parameters within the transformed data space is addressed in this paper. The reduction of dimensionality is performed with the principal components transform, which allows us to represent the full IASI spectrum with a few coefficients of the expansion. This truncated expansion could have a twofold beneficial effect: (i) it could improve the present exploitation and performance of IASI data for the retrieval of temperature and moisture; and (ii) it could save transmission bandwidth, data rate and costs for the dissemination to users of IASI data. A suitable form of the inverse/forward model completely embedded in the transformed space has been derived and applied to simulated and real IASI data. This methodology has allowed us to assess the IASI performance for temperature, water vapor and ozone based on the full IASI spectral coverage. The use of back-transformed spectral radiances (i.e. the filtered radiances obtained by the truncated expansion) instead of expansion coefficients has also been addressed and assessed. Retrieval exercises performed in simulation and with real observations lead us to conclude that the principal components space-based inverse approach is potentially superior over the current practice of using sparse channels. Copyright

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Section: Introductionmentioning

confidence: 99%

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

Masiello

Serio

Antonelli

2011

Quart J Royal Meteoro Soc

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“…In this paper, IASI simulations have been performed using two forward models, σ -IASI (Amato et al, 2002;Grieco et al, 2007;Masiello et al, 2009) and the newly developed principal component based version of the RTTOV fast radiative transfer model (Matricardi, 2010). The strategy of using two independent forward models allows us to determine whether or not there is any dependence of the bias on the forward model itself.…”

Section: Introductionmentioning

confidence: 99%

The use of IASI data to identify systematic errors in the ECMWF forecasts of temperature in the upper stratosphere

2011

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Abstract. 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 CO 2 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 MediumRange 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 CO 2 profile and to spectroscopy errors has also been studied.

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“…It is possible to calculate a set of predictor coefficients for SO 2 and incorporate them within RTTOV by replacing the properties of another gaseous species that has negligible impact on the total column transmittance within the selected HIRS/2 channels (in this case, carbon monoxide). The coefficients were generated by a "training" methodology using an extensive range of specimen atmospheric profiles, where the SO 2 was represented from very low/background levels to very large perturbations, after Matricardi (2008Matricardi ( , 2010 and . This approach retains the speed and accuracy offered by RTTOV and enables the model to be used to represent atmospheric gases for future instruments not already catered for (ECMWF, 2001).…”

Section: Retrieval Algorithm and Forward Modelmentioning

confidence: 99%

Retrieval of volcanic SO<sub>2</sub> from HIRS/2 using optimal estimation

Miles¹,

Siddans²,

Grainger³

et al. 2017

Atmos. Meas. Tech.

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Abstract. We present an optimal-estimation (OE) retrieval scheme for stratospheric sulfur dioxide from the HighResolution Infrared Radiation Sounder 2 (HIRS/2) instruments on the NOAA and MetOp platforms, an infrared radiometer that has been operational since 1979. This algorithm is an improvement upon a previous method based on channel brightness temperature differences, which demonstrated the potential for monitoring volcanic SO 2 using HIRS/2. The Prata method is fast but of limited accuracy. This algorithm uses an optimal-estimation retrieval approach yielding increased accuracy for only moderate computational cost. This is principally achieved by fitting the column water vapour and accounting for its interference in the retrieval of SO 2 . A cloud and aerosol model is used to evaluate the sensitivity of the scheme to the presence of ash and water/ice cloud.

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A principal component based version of the RTTOV fast radiative transfer model

Cited by 43 publications

References 26 publications

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

The use of IASI data to identify systematic errors in the ECMWF forecasts of temperature in the upper stratosphere

Retrieval of volcanic SO<sub>2</sub> from HIRS/2 using optimal estimation

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A principal component based version of the RTTOV fast radiative transfer model

Cited by 43 publications

References 26 publications

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space

The use of IASI data to identify systematic errors in the ECMWF forecasts of temperature in the upper stratosphere

Retrieval of volcanic SO&lt;sub&gt;2&lt;/sub&gt; from HIRS/2 using optimal estimation

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Retrieval of volcanic SO<sub>2</sub> from HIRS/2 using optimal estimation