1,721,104 research outputs found
An effective water vapor self-braodening scheme for look-up table based radiative transfer
No full textIn this work we describe a methodology for the inclusion of first-order water vapor self-broadening effects in look-up-table based radiative transfer calculations. The methodology does not increase the complexity and size of look-up-tables which continue to exist in a 1-D setting, although the inclusion of a new variable (i.e., the water vapor concentration) would raise the dimensionality to 2-D. The scheme is discussed for modern infrared sensors whose spectral resolution falls in the range 0.1 - 2 cm-
Esperimento per lo studio delle proprietà ottiche nel lontano infrarosso del vapore acqueo a Plateau Rosà
No full textAn Italian group of academic and National Research Council researchers, in cooperation with the National Centre for Meteorology and Climatology of the Air Force Meteorological
Service, has planned and conducted a measurements campaign at meteorological station of Testa Grigia, in the massive alpine region of Plateau Rosà. The campaign has allowed to observe
the atmospheric water vapour optical properties in a spectral electromagnetic region unexplored until now, but of vital mportance in relation to mechanisms that regulate the Planet greenhouse effects
Dimensionality-reduction approach to the thermal radiative transfer equation inverse problem
No full textAn original algorithm is illustrated for the inversion of geophysical parameters from spectral observations in the thermal band. The algorithm exploits the Hotelling transform and projects the linearized version of the radiative transfer equation in a space of reduced dimensionality. The inversion is performed in this latter space, which speeds up the computations and makes the method attractive for real-time retrieval from high spectral resolution infrared observations
Simultaneous physical retrieval of surface emissivity spectrum and atmospheric parameters from infrared atmospheric sounder interferometer spectral radiances
Full text linkThe problem of simultaneous physical retrieval of surface emissivity, skin temperature, and temperature, water–vapor, and ozone atmospheric profiles from high-spectral-resolution observations in the infrared is formulated according to an inverse problem with multiple regularization parameters.
A methodology has been set up, which seeks an effective solution to the inverse problem in a generalized L-curve criterion framework.
The a priori information for the surface emissivity is obtained on the basis of laboratory data
alone, and that for the atmospheric parameters by climatology or weather forecasts. To ensure that we
deal with a problem of fewer unknowns than observations, the dimensionality of the emissivity is reduced through expansion in Fourier series.
The main objective of this study is to demonstrate the simultaneous retrieval of emissivity, skin temperature, and atmospheric parameters with a two-dimensional L-curve criterion.
The procedure has been demonstrated with spectra observed from the infrared atmospheric
sounder interferometer, flying onboard the European Meteorological Operational satellite.
To check the quality and reliability of the methodology, we have used spectra recorded over regions characterized by known or stable emissivity. These include sea surface, for which effective emissivity models are known,
and arid lands (Sahara and Namib Deserts) that are known to exhibit the characteristic spectral
signature of quartz-rich sand
An optimal interpolation scheme for surface and atmospheric parameters: applications to SEVIRI and IASI
No full textIn this paper, we present a 2-Dimensional (2D) Optimal Interpolation (OI) technique for spatially scattered infrared satellite observations, from which level 2 products have been obtained, in order to yield level 3, regularly gridded, data. The scheme derives from a Bayesian predictor-corrector scheme used in data assimilation and is based on the Kalman filter estimation. It has been applied to 15-minutes temporal resolution Spinning Enhanced Visible and Infrared Imager (SEVIRI) emissivity and temperature products and to Infrared Atmospheric Sounding Interferometer (IASI) atmospheric ammonia (NH3) retrievals, a gas affecting the air quality. Results have been exemplified for target areas over Italy. In particular temperature retrievals have been compared with gridded data from MODIS (Moderate-resolution Imaging Spectroradiometer) observations. Our findings show that the proposed strategy is quite effective to fill gaps because of data voids due, e.g., to clouds, gains more efficiency in capturing the daily cycle for surface parameters and provides valuable information on NH3 concentration and variability in regions not yet covered by ground-based instruments
Inversion for atmospheric thermodynamical parameters of IASI data in the principal components space
No full textThe 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 © 2011 Royal Meteorological Societ
Qualifying IMG Tropical Spectra for Clear Sky
No full textThe problem of cloud detection for the Interferometric Monitoring of Greenhouse Gases spectrometer has been addressed by considering a set of thresholding tests which takes full advantage of the high spectral resolution of the sensor. The methodology has been applied to a case study consisting of spectra recorded in the tropics on sea surface, although the scheme may be easily extended to other latitudes. The algorithm is very efficient because it uses only the observed spectrum and no on-line radiative transfer calculation is needed. Based on this cloud detection scheme a set of clear-sky tropical spectra have been identified to be used by the scientific community for further studies such as retrieval of atmospheric properties and high spectral resolution radiative transfer modeling
Dimensionality reduction through random projections for application to the retrieval of atmospheric parameters from hyperspectral satellite sensors
No full textPhysical inverse problems found on appropriate forward models, which can have highly systematic errors. As an example, in remote sensing from satellite observations, the forward model depends on spectroscopy of atmospheric gas molecules and radiative transfer modelling, whose accuracy is not perfect. The problem of correctly addressing both error components (instrument and forward model) is one of major concern in retrieval methodology. Until now, the treatment has relied on ad-hoc strategies, which makes the retrieval algorithms sub-optimal or nonoptimal at all. Optimal estimation is based on the Gaussian assumption for noise, which is normally not satisfied in presence of forward model error. In this paper, we will show that a proper Random Projections approach can provide a) an unified and coherent treatment of systematic and random errors; b) a compression tool, which can reduce the dimensionality of the data space; c) a noise model which is truly Gaussian therefore, making it possible to apply rigorously Optimal Estimation and derive the correct retrieval error; d) a simplified treatment of the inverse algebra to get the final solution. The present paper addresses the specific point of how to fully exploit the compression capability of random projections to develop an inverse algorithm able to deal with big data, and minimal loss of information content. The approach will be exemplified for IASI (Infrared Atmospheric Sounder Interfermoter) and we will show the very first physical retrieval scheme, which exploits the full IASI spectral coverage for the simultaneous retrieval of surface and atmospheric parameters. The methodology can be applied to any inverse physical problem dealing with high-dimensionality data space, how normally arises in astrophysical and Earth remote sensing science. The performance of the methodology for the retrieval of temperature and water profiles has been assessed through comparison with radiosonde observations. The retrieval accuracy, for a tropical atmosphere, is better than ± 1.25 K and ± 1.5 g/kg for temperature and water vapour, respectively. We have also performed a retrieval exercise for the Eastern China and we have shown that air quality gases, such as CO, SO2 and NH3 can be simultaneously and confidently retrieved, meaning that Random Projections preserve information content of data
CarbonNET: carbon dioxide retrieval from satellite using neural networks
No full textIn this work, we will show the potential of a nonlinear statistical regressor method based on a Deep Neural Network (DNN) scheme for retrieving XCO2. Toward this objective, we set up a training exercise based on simulated IASI observations using the state-of-the-art radiative transfer mode (RTM) σ-IASI/F2N. A nine-year-long record from 2014 to 2022 of atmospheric state vectors using CAMS reanalysis dataset from ECMWF related to one day of each month at four synoptic hours (00-06-12-18 UTC) has been processed to capture typical seasonal and diurnal cycles, resulting in about 400,000 of IASI-L1 synthetic spectral radiances. In order to provide the regression scheme with the most representative information on the CO2 signature, we implemented principal component analysis (PCA) of different regression features. Specifically, the PCA transform was applied to IASI band-1 (645-1210 cm-1), which is most affected by CO2 absorption, and to atmospheric temperature profiles. For IASI measurements the base of 90 principal components from the EUMETSAT IASI Level one Principal Component Compression (PCC) has been considered. Finally, different locations at various latitudes were selected to validate and evaluate the retrieval scheme's performance. In terms of validation, a set of real IASI soundings was matched with in situ measurements collected at Mauna Loa station, renowned as a background site with minimal regional impact. Preliminary findings demonstrate a high level of accuracy in extracting growth rate, trend, and seasonality from the predictions, showing a correlation greater than 0.9 with the in-situ data
Assessing water vapour line parameters and continuum in the spectral range between 240 and 600 cm-1
No full textThe paper assesses the water vapour continuum and line parameters using FTS ground-based measurements in the spectral range 240-600 cm-1.
For the continuum, we compare two versions of the widely used Mlawer, Tobin-Clough, Kneizys-Davies (MT_CKD) models and the coefficients recently retrieved within the ECOWAR campaign. For the line parameters, the 2001 and the 2006 releases of HITRAN database have been considered. The new continuum coefficients, which result in a more transparent atmosphere, improve the consistency between model and observation.
Calculations performed using the latest HITRAN spectroscopic parameters shows a better consistency with the observations in the whole spectral range, when it is used with the new retrieved continuum coefficients
- …
