scholarly journals Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory

2020 ◽  
Vol 12 (22) ◽  
pp. 3724
Author(s):  
Sruthy Sasi ◽  
Vijay Natraj ◽  
Víctor Molina García ◽  
Dmitry S. Efremenko ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Model Selection ◽  
Optical Thickness ◽  
Marginal Likelihood ◽  
Likelihood Estimation ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Aerosol Model ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Atmospheric Remote Sensing

The retrieval of aerosol and cloud properties such as their optical thickness and/or layer/top height requires the selection of a model that describes their microphysical properties. We demonstrate that, if there is not enough information for an appropriate microphysical model selection, the solution’s accuracy can be improved if the model uncertainty is taken into account and appropriately quantified. For this purpose, we design a retrieval algorithm accounting for the uncertainty in model selection. The algorithm is based on (i) the computation of each model solution using the iteratively regularized Gauss–Newton method, (ii) the linearization of the forward model around the solution, and (iii) the maximum marginal likelihood estimation and the generalized cross-validation to estimate the optimal model. The algorithm is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements corresponding to the Earth Polychromatic Imaging Camera (EPIC) instrument onboard the Deep Space Climate Observatory (DSCOVR) satellite. Our numerical simulations show that the heuristic approach based on the thesolution minimizing the residual, which is frequently used in literature, is completely unrealistic when both the aerosol model and surface albedo are unknown.

scholarly journals Model Selection in Atmospheric Remote Sensing with Application to Aerosol Retrieval from DSCOVR/EPIC. Part 2: Numerical Analysis

2020 ◽  
Vol 12 (21) ◽  
pp. 3656
Author(s):  
Sruthy Sasi ◽  
Vijay Natraj ◽  
Víctor Molina García ◽  
Dmitry S. Efremenko ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Model Selection ◽  
Aerosol Layer ◽  
Angular Variation ◽  
Aerosol Model ◽  
A Value ◽  
Aerosol Retrieval ◽  
Atmospheric Remote Sensing ◽  
The One ◽  
Aerosol Parameters

An algorithm for retrieving aerosol parameters by taking into account the uncertainty in aerosol model selection is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements from the EPIC sensor onboard the Deep Space Climate Observatory. The synthetic measurements are generated using aerosol models derived from AERONET measurements at different sites, while other commonly used aerosol models, such as OPAC, GOCART, OMI, and MODIS databases are used in the retrieval. The numerical analysis is focused on the estimation of retrieval errors when the true aerosol model is unknown. We found that the best aerosol model is the one with a value of the asymmetry parameter and an angular variation of the phase function around the viewing direction that is close to the values corresponding to the reference aerosol model.

scholarly journals Observation of absorbing aerosols above clouds over the South- East Atlantic Ocean from the geostationary satellite SEVIRI – Part 1: Method description and sensitivity

2019 ◽  
Author(s):  
Fanny Peers ◽  
Peter Francis ◽  
Cathryn Fox ◽  
Steven J. Abel ◽  
Kate Szpek ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Optical Thickness ◽  
Aerosol Size Distribution ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
The South ◽  
East Atlantic ◽  
Aerosol Model ◽  
Cloud Properties ◽  
The Impact

Abstract. High temporal resolution observations from satellites have a great potential for studying the impact of biomass burning aerosols and clouds over the South East Atlantic Ocean (SEAO). This paper presents a method developed to retrieve simultaneously aerosol and cloud properties in aerosol above cloud conditions from the geostationary instrument Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI). The above-cloud Aerosol Optical Thickness (AOT), the Cloud Optical Thickness (COT) and the Cloud droplet Effective Radius (CER) are derived from the spectral contrast and the magnitude of the signal measured in three channels in the visible to shortwave infrared region. The impact of the absorption from atmospheric gases on the satellite signal is corrected by applying transmittances calculated using the water vapour profiles from a Met Office forecast model. The sensitivity analysis shows that a 10 % error on the humidity profile leads to an 18.5 % bias on the above-cloud AOT, which highlights the importance of an accurate atmospheric correction scheme. In situ measurements from the CLARIFY-2017 airborne field campaign are used to constrain the aerosol size distribution and refractive index that is assumed for the aforementioned retrieval algorithm. The sensitivities in the retrieved AOT, COT and CER to the aerosol model assumptions are assessed. Although an uncertainty of 31.2 % is observed on the above-cloud AOT, the retrieval of the absorption AOT and both cloud properties is weakly sensitive to the aerosol model assumptions, with biases lower than 7 % and 3 % respectively. The stability of the retrieval over time is analysed. For observations outside of the backscattering glory region, the time-series of the aerosol and cloud properties are physically consistent, which confirms the ability of the retrieval to monitor the temporal evolution of aerosol above cloud events over the SEAO.

scholarly journals Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
Author(s):  
André Ehrlich ◽  
Eike Bierwirth ◽  
Larysa Istomina ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Grain Size ◽  
Sea Ice ◽  
Optical Thickness ◽  
Liquid Water ◽  
Retrieval Algorithm ◽  
Continuous Transition ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

scholarly journals Seven years of global retrieval of cloud properties using space-borne data of GOME-1

2011 ◽  
Vol 4 (4) ◽  
pp. 4991-5035 ◽  
Author(s):  
L. Lelli ◽  
A. A. Kokhanovsky ◽  
V. V. Rozanov ◽  
M. Vountas ◽  
A. M. Sayer ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Climate Modeling ◽  
Southern Oscillation ◽  
Trace Gases ◽  
Probability Density Functions ◽  
Retrieval Algorithm ◽  
Density Functions ◽  
Cloud Properties ◽  
Asymptotic Equations

Abstract. We present a global and regional multi-annual (1996–2002) analysis of cloud properties (spherical albedo, optical thickness and top height) derived using measurements from the GOME-1 instrument onboard the ESA ERS-2 space platform. We focus on cloud top height (CTH), which is obtained from top-of-atmosphere backscattered solar light measurements in the O2 A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer. The dataset has been validated against independent ground- and satellite-based retrievals and is aimed to support ozone and trace-gases studies as well as to create a robust long-term climatology together with SCIAMACHY and GOME-2 ensuing retrievals. We observed the El Niño Southern Oscillation anomaly in the 1997–1998 record through CTH values over Pacific Ocean. Analytical forms of probability density functions of seasonal CTH are proposed for parameterizations in climate modeling. The global average CTH as derived from GOME-1 is 7.0 ± 1.18 km.

scholarly journals Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A-band

2017 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Surface Albedo ◽  
High Surface ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Critical Surface ◽  
Layer Height

Abstract. Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top of atmosphere reflectance spectrum in the oxygen A-band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top of atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A-band, and discusses its implications. The underlying physics are introduced by analysing top of atmosphere reflectance spectra obtained using a radiative transfer model. Furthermore, error analysis of the aerosol layer height retrieval algorithm are conducted over dark and bright surfaces to show the dependency on surface reflectance. The analysis shows that the information on aerosol layer height from atmospheric path contribution and the surface contribution to the top of atmosphere are opposite in sign – an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these contributions are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A-band from GOME-2A instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

scholarly journals Observation of absorbing aerosols above clouds over the south-east Atlantic Ocean from the geostationary satellite SEVIRI – Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

2021 ◽  
Vol 21 (4) ◽  
pp. 3235-3254
Author(s):  
Fanny Peers ◽  
Peter Francis ◽  
Steven J. Abel ◽  
Paul A. Barrett ◽  
Keith N. Bower ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Water Vapour ◽  
Optical Thickness ◽  
Atmospheric Correction ◽  
Cloud Droplet ◽  
Aircraft Measurements ◽  
East Atlantic ◽  
Aerosol Model ◽  
Cloud Properties

Abstract. To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

scholarly journals Capability of multi-viewing-angle photo-polarimetric measurements for the simultaneous retrieval of aerosol and cloud properties

2010 ◽  
Vol 3 (4) ◽  
pp. 839-851 ◽  
Author(s):  
O. P. Hasekamp
Keyword(s):  
Satellite Remote Sensing ◽  
Essential Role ◽  
High Accuracy ◽  
Aerosol Layer ◽  
Viewing Angle ◽  
Clear Sky ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Land Surfaces ◽  
Sky Conditions

Abstract. An important new challenge in the field of multi-angle photo-polarimetric satellite remote sensing is the retrieval of aerosol properties under cloudy conditions. In this paper the possibility has been explored to perform a simultaneous retrieval of aerosol and cloud properties for partly cloudy scenes and for fully cloudy scenes where the aerosol layer is located above the cloud, using multi-angle photo-polarimetric measurements. Also, for clear sky conditions a review is given of the capabilities of multi-angle photo-polarimetric measurements in comparison with other measurement types. It is shown that already for clear sky conditions polarization measurements are highly important for the retrieval of aerosol optical and microphysical properties over land surfaces with unknown reflection properties. Furthermore, it is shown that multi-angle photo-polarimetric measurements have the capability to distinguish between aerosols and clouds, and thus facilitate a simultaneous retrieval of aerosol and cloud properties. High accuracy (0.002–0.004) of the polarimetric measurements plays an essential role here.

scholarly journals The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI near-UV Retrievals over the Ocean

2016 ◽  
Author(s):  
Santiago Gassó ◽  
Omar Torres
Keyword(s):  
Particle Shape ◽  
Spherical Shape ◽  
Detailed Examination ◽  
Index Of Refraction ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Aerosol Model ◽  
Modis Aod ◽  
Absorbing Aerosols

Abstract. Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODIS AOD comparisons) and over coastal and island sites (AERONET and OMI). Also, a research version of the retrieval algorithm (using MODIS and CALIPSO information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals. Using examples from case studies with outliers, the reasons that lead to the observed differences are examined with specific purpose to determine if they are related to instrument (i.e., pixel size, calibration) limitations or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm) resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ~< 0.5). For higher aerosol loadings, the bias remains within OMI’s AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and AODs from MODIS along with sensitivity tests was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. Also, it is shown with an example how an incorrect assumption of the aerosol height can lead to an underestimate but this is not as large as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

scholarly journals Capability of multi-viewing-angle photo-polarimetric measurements for the simultaneous retrieval of aerosol and cloud properties

2010 ◽  
Vol 3 (2) ◽  
pp. 1229-1262 ◽  
Author(s):  
O. P. Hasekamp
Keyword(s):  
Satellite Remote Sensing ◽  
Essential Role ◽  
High Accuracy ◽  
Aerosol Layer ◽  
Viewing Angle ◽  
Clear Sky ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Land Surfaces ◽  
Sky Conditions

Abstract. An important new challenge in the field of multi-angle photopolarimetric satellite remote sensing is the retrieval of aerosol properties under cloudy conditions. In this paper the possibility has been explored to perform a simultaneous retrieval of aerosol and cloud properties for partly cloudy scenes and for fully cloudy scenes where the aerosol layer is located above the cloud, using multi-angle photo-polarimetric measurements. Also, for clear sky conditions a review is given of the capabilities of multi-angle photo-polarimetric measurements in comparison with other measurement types. It is shown that already for clear sky conditions polarization measurements are highly important for the retrieval of aerosol optical and microphysical properties over land surfaces with unknown reflection properties. Furthermore, it is shown that multi-angle photo-polarimetric measurements have the capability to distinguish between aerosols and clouds, and thus facilitate a simultaneous retrieval of aerosol and cloud properties. High accuracy (0.002–0.004) of the polarimetric measurements plays an essential role here.

scholarly journals Observation of absorbing aerosols above clouds over the South-East Atlantic Ocean from the geostationary satellite SEVIRI – Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

2020 ◽  
Author(s):  
Fanny Peers ◽  
Peter Francis ◽  
Steven J. Abel ◽  
Paul A. Barrett ◽  
Keith N. Bower ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Water Vapour ◽  
Optical Thickness ◽  
Atmospheric Correction ◽  
Cloud Droplet ◽  
Aircraft Measurements ◽  
East Atlantic ◽  
Aerosol Model ◽  
Cloud Properties

Abstract. To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the South East Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud Aerosol Optical Thickness (AOT) is good (R = 0.75), the AOT retrieved by SEVIRI is 16.5 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying Cloud Optical Thickness (COT) derived from the two satellites are in good agreement (R = 0.90). The Cloud droplet Effective Radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by ~2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

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