scholarly journals Multi-angular thermal infrared emission characteristics of Bohai Sea ice based on in situ measurements

2015 ◽  
Vol 61 (229) ◽  
pp. 864-874 ◽  
Author(s):  
Jinlong Chao ◽  
Chengyu Liu ◽  
Yingjun Xu ◽  
Wei Gu ◽  
Ying Li ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Bohai Sea ◽  
Robust Regression ◽  
Thermal Infrared ◽  
In Situ Measurements ◽  
Transfer Model ◽  
Emission Characteristics ◽  
Relative Emissivity

AbstractWe report on the radiative transfer process and optical properties of sea ice in the thermal infrared (TIR) band, presenting two new linear kernel driver models (Relative Emissivity Distribution Function, REDF) that describe TIR emission characteristics of smooth and rough ice. In order to test the models and determine the necessary coefficients, in situ measurements from the Bohai Sea were carried out during the 2011/12 and 2012/13 boreal winters. The results show that the relative emissivity of smooth sea ice decreases along with increasing viewing zenith angle, and the shape of the relative emissivity curve is similar to that of an ideal plane. Affected by parameters such as roughness and surface temperature distribution, the anisotropy of relative emissivity of sea ice with a high degree of roughness is stronger relative to the cosine emitter. The model coefficients were also obtained using a robust regression method based on the measured data. The presented models are more practical than the numerical radiative transfer model and can be used for multi-angular TIR remote sensing.

scholarly journals Primary production calculations for sea ice from bio-optical observations in the Baltic Sea

Elem Sci Anth ◽  
2016 ◽  
Vol 4 ◽  
Author(s):  
Susann Müller ◽  
Anssi V. Vähätalo ◽  
Jari Uusikivi ◽  
Markus Majaneva ◽  
Sanna Majaneva ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Primary Production ◽  
Baltic Sea ◽  
Gulf Of Finland ◽  
Radiative Transfer Model ◽  
Quantum Yields ◽  
Transfer Model ◽  
The Gulf Of Finland

Abstract Bio-optics is a powerful approach for estimating photosynthesis rates, but has seldom been applied to sea ice, where measuring photosynthesis is a challenge. We measured absorption coefficients of chromophoric dissolved organic matter (CDOM), algae, and non-algal particles along with solar radiation, albedo and transmittance at four sea-ice stations in the Gulf of Finland, Baltic Sea. This unique compilation of optical and biological data for Baltic Sea ice was used to build a radiative transfer model describing the light field and the light absorption by algae in 1-cm increments. The maximum quantum yields and photoadaptation of photosynthesis were determined from 14C-incorporation in photosynthetic-irradiance experiments using melted ice. The quantum yields were applied to the radiative transfer model estimating the rate of photosynthesis based on incident solar irradiance measured at 1-min intervals. The calculated depth-integrated mean primary production was 5 mg C m–2 d–1 for the surface layer (0–20 cm ice depth) at Station 3 (fast ice) and 0.5 mg C m–2 d–1 for the bottom layer (20–57 cm ice depth). Additional calculations were performed for typical sea ice in the area in March using all ice types and a typical light spectrum, resulting in depth-integrated mean primary production rates of 34 and 5.6 mg C m–2 d–1 in surface ice and bottom ice, respectively. These calculated rates were compared to rates determined from 14C incorporation experiments with melted ice incubated in situ. The rate of the calculated photosynthesis and the rates measured in situ at Station 3 were lower than those calculated by the bio-optical algorithm for typical conditions in March in the Gulf of Finland by the bio-optical algorithm. Nevertheless, our study shows the applicability of bio-optics for estimating the photosynthesis of sea-ice algae.

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals SEVIRI Hyper-Fast Forward Model with Application to Emissivity Retrieval

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1532 ◽  
Author(s):  
Guido Masiello ◽  
Carmine Serio ◽  
Sara Venafra ◽  
Laurent Poutier ◽  
Frank-M. Göttsche
Keyword(s):  
Radiative Transfer ◽  
Real Time ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Computational Time ◽  
Transfer Model ◽  
Real Time Processing ◽  
In Situ Observations ◽  
Infrared Radiances

Timely processing of observations from multi-spectral imagers, such as SEVIRI (Spinning Enhanced Visible and Infrared Imager), largely depends on fast radiative transfer calculations. This paper mostly concerns the development and implementation of a new forward model for SEVIRI to be applied to real time processing of infrared radiances. The new radiative transfer model improves computational time by a factor of ≈7 compared to the previous versions and makes it possible to process SEVIRI data at nearly real time. The new forward model has been applied for the retrieval of surface parameters. Although the scheme can be applied for the simultaneous retrieval of temperature and emissivity, the paper mostly focuses on emissivity. The inverse scheme relies on a Kalman filter approach, which allows us to exploit a sequential processing of SEVIRI observations. Based on the new forward model, the paper also presents a validation retrieval performed with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. Furthermore, a comparison with IASI (Infrared Atmospheric Sounder Interferometer) emissivity retrievals has been performed as well. It has been found that the retrieved emissivities are in good agreement with each other and with in situ observations, i.e., average differences are generally well below 0.01.

scholarly journals Efficient radiative transfer model for thermal infrared brightness temperature simulation in cloudy atmospheres

2020 ◽  
Vol 28 (18) ◽  
pp. 25730
Author(s):  
Wenwen Li ◽  
Feng Zhang ◽  
Yi-Ning Shi ◽  
Hironobu Iwabuchi ◽  
Mingwei Zhu ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Brightness Temperature ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Infrared Brightness

scholarly journals A High-Accuracy Multiwavelength Radiometer for In Situ Measurements in the Thermal Infrared. Part II: Behavior in Field Experiments

2003 ◽  
Vol 20 (7) ◽  
pp. 1023-1033 ◽  
Author(s):  
Gérard Brogniez ◽  
Christophe Pietras ◽  
Michel Legrand ◽  
Philippe Dubuisson ◽  
Martial Haeffelin
Keyword(s):  
Field Experiments ◽  
Thermal Infrared ◽  
High Accuracy ◽  
In Situ Measurements

Volcanic ash detection and retrievals using SLSTR. Test case: 2019 Raikoke  eruption

2021 ◽  
Author(s):  
Ilaria Petracca ◽  
Davide De Santis ◽  
Stefano Corradini ◽  
Lorenzo Guerrieri ◽  
Matteo Picchiani ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Volcanic Ash ◽  
Thermal Infrared ◽  
Integrated Approach ◽  
Effective Radius ◽  
Volcanic Plume ◽  
Transfer Model ◽  
Volcanic Cloud

<p>When an eruption event occurs it is necessary to accurately and rapidly determine the position and evolution during time of the volcanic cloud and its parameters (such as Aerosol Optical Depth-AOD, effective radius-Re and mass-Ma of the ash particles), in order to ensure the aviation security and the prompt management of the emergencies.</p><p>Here we present different procedures for volcanic ash cloud detection and retrieval using S3 SLSTR (Sentinel-3 Sea and Land Surface Temperature Radiometer) data collected the 22 June at 00:07 UTC by the Sentinel-3A platform during the Raikoke (Kuril Islands) 2019 eruption.</p><p>The volcanic ash detection is realized by applying an innovative machine learning based algorithm, which uses a MultiLayer Perceptron Neural Network (NN) to classify a SLSTR image in eight different surfaces/objects, distinguishing volcanic and weather clouds, and the underlying surfaces. The results obtained with the NN procedure have been compared with two consolidated approaches based on an RGB channels combination in the visible (VIS) spectral range and the Brightness Temperature Difference (BTD) procedure that exploits the thermal infrared (TIR) channels centred at 11 and 12 microns (S8 and S9 SLSTR channels respectively). The ash volcanic cloud is correctly identified by all the models and the results indicate a good agreement between the NN classification approach, the VIS-RGB and BTD procedures.</p><p>The ash retrieval parameters (AOD, Re and Ma) are obtained by applying three different algorithms, all exploiting the volcanic cloud “mask” obtained from the NN detection approach. The first method is the Look Up Table (LUT<sub>p</sub>) procedure, which uses a Radiative Transfer Model (RTM) to simulate the Top Of Atmosphere (TOA) radiances in the SLSTR thermal infrared channels (S8, S9), by varying the aerosol optical depth and the effective radius. The second algorithm is the Volcanic Plume Retrieval (VPR), based on a linearization of the radiative transfer equation capable to retrieve, from multispectral satellite images, the abovementioned parameters. The third approach is a NN model, which is built on a training set composed by the inputs-outputs pairs TOA radiances vs. ash parameters. The results of the three retrieval methods have been compared, considering as reference the LUT<sub>p</sub> procedure, since that it is the most consolidated approach. The comparison shown promising agreement between the different methods, leading to the development of an integrated approach for the monitoring of volcanic ash clouds using SLSTR.</p><p>The results presented in this work have been obtained in the sphere of the VISTA (Volcanic monItoring using SenTinel sensors by an integrated Approach) project, funded by ESA and developed within the EO Science for Society framework [https://eo4society.esa.int/projects/vista/].</p>

scholarly journals Reflective properties of melt ponds on sea ice

2018 ◽  
Vol 12 (6) ◽  
pp. 1921-1937 ◽  
Author(s):  
Aleksey Malinka ◽  
Eleonora Zege ◽  
Larysa Istomina ◽  
Georg Heygster ◽  
Gunnar Spreen ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Atmospheric Correction ◽  
Scattering Coefficient ◽  
Spherical Particles ◽  
The Arctic ◽  
Melt Pond ◽  
Melt Ponds ◽  
Bottom Albedo

Abstract. Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. In this study, the melt pond reflectance is considered in the framework of radiative transfer theory. The melt pond is modeled as a plane-parallel layer of pure water upon a layer of sea ice (the pond bottom). We consider pond reflection as comprising Fresnel reflection by the water surface and multiple reflections between the pond surface and its bottom, which is assumed to be Lambertian. In order to give a description of how to find the pond bottom albedo, we investigate the inherent optical properties of sea ice. Using the Wentzel–Kramers–Brillouin approximation approach to light scattering by non-spherical particles (brine inclusions) and Mie solution for spherical particles (air bubbles), we conclude that the transport scattering coefficient in sea ice is a spectrally independent value. Then, within the two-stream approximation of the radiative transfer theory, we show that the under-pond ice spectral albedo is determined by two independent scalar values: the transport scattering coefficient and ice layer thickness. Given the pond depth and bottom albedo values, the bidirectional reflectance factor (BRF) and albedo of a pond can be calculated with analytical formulas. Thus, the main reflective properties of the melt pond, including their spectral dependence, are determined by only three independent parameters: pond depth z, ice layer thickness H, and transport scattering coefficient of ice σt.The effects of the incident conditions and the atmosphere state are examined. It is clearly shown that atmospheric correction is necessary even for in situ measurements. The atmospheric correction procedure has been used in the model verification. The optical model developed is verified with data from in situ measurements made during three field campaigns performed on landfast and pack ice in the Arctic. The measured pond albedo spectra were fitted with the modeled spectra by varying the pond parameters (z, H, and σt). The coincidence of the measured and fitted spectra demonstrates good performance of the model: it is able to reproduce the albedo spectrum in the visible range with RMSD that does not exceed 1.5 % for a wide variety of melt pond types observed in the Arctic.

scholarly journals Retrieval of total column and surface NO<sub>2</sub> from Pandora zenith-sky measurements

2019 ◽  
Author(s):  
Xiaoyi Zhao ◽  
Debora Griffin ◽  
Vitali Fioletov ◽  
Chris McLinden ◽  
Jonathan Davies ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Concentration ◽  
In Situ Measurements ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Chemical Transport Model ◽  
High Quality ◽  
Vertical Column

Abstract. Pandora spectrometers can retrieve nitrogen dioxide (NO2) vertical column densities (VCDs) via two viewing geometries: direct-sun and zenith-sky. The direct-sun NO2 VCD measurements have high quality (0.1 DU accuracy in clear-sky conditions) and do not rely on any radiative transfer model to calculate air mass factors (AMFs); however, they are not available when the sun is obscured by clouds. To perform NO2 measurements in cloudy conditions, a simple but robust NO2 retrieval algorithm is developed for Pandora zenith-sky measurements. This algorithm derives empirical zenith-sky NO2 AMFs from coincident high-quality direct-sun NO2 observations. Moreover, the retrieved Pandora zenith-sky NO2 VCD data are converted to surface NO2 concentrations with a scaling algorithm that uses chemical-transport-model predictions and satellite measurements as inputs. NO2 VCDs and surface concentrations are retrieved from Pandora zenith-sky measurements made in Toronto, Canada, from 2015 to 2017. The retrieved Pandora zenith-sky NO2 data (VCD and surface concentration) show good agreement with both satellite and in situ measurements. The diurnal and seasonal variations of derived Pandora zenith-sky surface NO2 data also agree well with in situ measurements (diurnal difference within ±2 ppbv). Overall, this work shows that the new Pandora zenith-sky NO2 products have the potential to be used in various applications such as future satellite validation in moderate cloudy scenes and air quality monitoring.

scholarly journals The color of melt ponds on Arctic sea ice

2018 ◽  
Vol 12 (4) ◽  
pp. 1331-1345 ◽  
Author(s):  
Peng Lu ◽  
Matti Leppäranta ◽  
Bin Cheng ◽  
Zhijun Li ◽  
Larysa Istomina ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Radiative Transfer Model ◽  
Ice Thickness ◽  
Transfer Model ◽  
Blue Color ◽  
Validation Data ◽  
Melt Ponds ◽  
Arctic Sea

Abstract. Pond color, which creates the visual appearance of melt ponds on Arctic sea ice in summer, is quantitatively investigated using a two-stream radiative transfer model for ponded sea ice. The upwelling irradiance from the pond surface is determined and then its spectrum is transformed into RGB (red, green, blue) color space using a colorimetric method. The dependence of pond color on various factors such as water and ice properties and incident solar radiation is investigated. The results reveal that increasing underlying ice thickness Hi enhances both the green and blue intensities of pond color, whereas the red intensity is mostly sensitive to Hi for thin ice (Hi  <  1.5 m) and to pond depth Hp for thick ice (Hi  >  1.5 m), similar to the behavior of melt-pond albedo. The distribution of the incident solar spectrum F0 with wavelength affects the pond color rather than its intensity. The pond color changes from dark blue to brighter blue with increasing scattering in ice, and the influence of absorption in ice on pond color is limited. The pond color reproduced by the model agrees with field observations for Arctic sea ice in summer, which supports the validity of this study. More importantly, the pond color has been confirmed to contain information about meltwater and underlying ice, and therefore it can be used as an index to retrieve Hi and Hp. Retrievals of Hi for thin ice (Hi  <  1 m) agree better with field measurements than retrievals for thick ice, but those of Hp are not good. The analysis of pond color is a new potential method to obtain thin ice thickness in summer, although more validation data and improvements to the radiative transfer model will be needed in future.

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