scholarly journals Comparison of a coupled snow thermodynamic and radiative transfer model with in-situ active microwave signatures of snow-covered smooth first-year sea ice

2015 ◽  
Vol 9 (3) ◽  
pp. 3293-3329
Author(s):  
M. C. Fuller ◽  
T. Geldsetzer ◽  
J. Yackel ◽  
J. P. S. Gill
Keyword(s):  
Sea Ice ◽  
Longwave Radiation ◽  
Reanalysis Data ◽  
Physical Models ◽  
Radiative Transfer Model ◽  
First Year ◽  
Transfer Model ◽  
Data Inversion ◽  
Microwave Backscatter

Abstract. Within the context of developing data inversion and assimilation techniques for C-band backscatter over sea ice, snow physical models may be used to drive backscatter models for comparison and optimization with satellite observations. Such modeling has potential to enhance understanding of snow on sea ice properties required for unambiguous interpretation of active microwave imagery. An end-to-end modeling suite is introduced, incorporating regional reanalysis data (NARR), a snow model (SNTHERM), and a multi-layer snow and ice active microwave backscatter model (MSIB). This modeling suite is assessed against measured snow on sea ice geophysical properties, and against measured active microwave backscatter. NARR data was input to the SNTHERM snow thermodynamic model, in order to drive the MISB model for comparison to detailed geophysical measurements and surface-based observations of C-band backscatter of snow on first-year sea ice. The NARR data was well correlated to available in-situ measurements, with the exception of long wave incoming radiation and relative humidity, which impacted SNTHERM simulations of snow temperature. SNTHERM reasonably represented snow grain size and density when compared to observations. The application of in-situ salinity profiles to one SNTHERM snow profile resulted in simulated backscatter close to that driven by in-situ snow properties. In other test cases, the simulated backscatter remained 4 to 6 dB below observed for higher incidence angles, and when compared to an average simulated backscatter of in-situ end-member snowcovers. Development of C-band inversion and assimilation schemes employing SNTHERM89.rev4 should consider sensitivity of the model to bias in incoming longwave radiation, the effects of brine, and the inability of SNTHERM89.Rev4 to simulate water accumulation and refreezing at the bottom and mid-layers of the snowpack with regard to thermodynamic response, brine wicking and volume processes, snow dielectrics, and microwave backscatter from snow on first-year sea-ice.

scholarly journals Comparison of a coupled snow thermodynamic and radiative transfer model with in situ active microwave signatures of snow-covered smooth first-year sea ice

2015 ◽  
Vol 9 (6) ◽  
pp. 2149-2161 ◽  
Author(s):  
M. C. Fuller ◽  
T. Geldsetzer ◽  
J. Yackel ◽  
J. P. S. Gill
Keyword(s):  
Sea Ice ◽  
Reanalysis Data ◽  
Physical Models ◽  
Radiative Transfer Model ◽  
Wave Radiation ◽  
First Year ◽  
Transfer Model ◽  
Long Wave ◽  
Microwave Backscatter

Abstract. Within the context of developing data inversion and assimilation techniques for C-band backscatter over sea ice, snow physical models may be used to drive backscatter models for comparison and optimization with satellite observations. Such modeling has the potential to enhance understanding of snow on sea-ice properties required for unambiguous interpretation of active microwave imagery. An end-to-end modeling suite is introduced, incorporating regional reanalysis data (NARR), a snow model (SNTHERM89.rev4), and a multilayer snow and ice active microwave backscatter model (MSIB). This modeling suite is assessed against measured snow on sea-ice geophysical properties and against measured active microwave backscatter. NARR data were input to the SNTHERM snow thermodynamic model in order to drive the MSIB model for comparison to detailed geophysical measurements and surface-based observations of C-band backscatter of snow on first-year sea ice. The NARR variables were correlated to available in situ measurements with the exception of long-wave incoming radiation and relative humidity, which impacted SNTHERM simulations of snow temperature. SNTHERM snow grain size and density were comparable to observations. The first assessment of the forward assimilation technique developed in this work required the application of in situ salinity profiles to one SNTHERM snow profile, which resulted in simulated backscatter close to that driven by in situ snow properties. In other test cases, the simulated backscatter remained 4–6 dB below observed for higher incidence angles and when compared to an average simulated backscatter of in situ end-member snow covers. Development of C-band inversion and assimilation schemes employing SNTHERM89.rev4 should consider sensitivity of the model to bias in incoming long-wave radiation, the effects of brine, and the inability of SNTHERM89.Rev4 to simulate water accumulation and refreezing at the bottom and mid-layers of the snowpack. These impact thermodynamic response, brine wicking and volume processes, snow dielectrics, and thus microwave backscatter from snow on first-year sea ice.

scholarly journals Optical properties of sea ice doped with black carbon – an experimental and radiative-transfer modelling comparison

2017 ◽  
Vol 11 (6) ◽  
pp. 2867-2881 ◽  
Author(s):  
Amelia A. Marks ◽  
Maxim L. Lamare ◽  
Martin D. King
Keyword(s):  
Radiative Transfer ◽  
Sea Ice ◽  
Black Carbon ◽  
Cross Sections ◽  
Extinction Coefficient ◽  
Radiative Transfer Model ◽  
First Year ◽  
Transfer Model ◽  
Ice Fabrics ◽  
Scattering Cross Sections

Abstract. Radiative-transfer calculations of the light reflectivity and extinction coefficient in laboratory-generated sea ice doped with and without black carbon demonstrate that the radiative-transfer model TUV-snow can be used to predict the light reflectance and extinction coefficient as a function of wavelength. The sea ice is representative of first-year sea ice containing typical amounts of black carbon and other light-absorbing impurities. The experiments give confidence in the application of the model to predict albedo of other sea ice fabrics. Sea ices,  ∼  30 cm thick, were generated in the Royal Holloway Sea Ice Simulator ( ∼  2000 L tanks) with scattering cross sections measured between 0.012 and 0.032 m2 kg−1 for four ices. Sea ices were generated with and without  ∼  5 cm upper layers containing particulate black carbon. Nadir reflectances between 0.60 and 0.78 were measured along with extinction coefficients of 0.1 to 0.03 cm−1 (e-folding depths of 10–30 cm) at a wavelength of 500 nm. Values were measured between light wavelengths of 350 and 650 nm. The sea ices generated in the Royal Holloway Sea Ice Simulator were found to be representative of natural sea ices. Particulate black carbon at mass ratios of  ∼  75,  ∼  150 and  ∼  300 ng g−1 in a 5 cm ice layer lowers the albedo to 97, 90 and 79 % of the reflectivity of an undoped clean sea ice (at a wavelength of 500 nm).

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 The effects of additional black carbon on Arctic sea ice surface albedo: variation with sea ice type and snow cover

2013 ◽  
Vol 7 (2) ◽  
pp. 943-973
Author(s):  
A. A. Marks ◽  
M. D. King
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Black Carbon ◽  
Surface Albedo ◽  
Arctic Sea Ice ◽  
Radiative Transfer Model ◽  
First Year ◽  
Transfer Model ◽  
Ice Surface ◽  
Carbon Additions

Abstract. Black carbon in sea ice will decrease sea ice surface albedo through increased absorption of incident solar radiation, exacerbating sea ice melting. Previous literature has reported different albedo responses to additions of black carbon in sea ice and has not considered how a snow cover may mitigate the effect of black carbon in sea ice. Sea ice is predominately snow covered. Visible light absorption and light scattering coefficients are calculated for a typical first year and multi-year sea ice and "dry" and "wet" snow types that suggest black carbon is the dominating absorbing impurity. The albedo response of first year and multi-year sea ice to increasing black carbon, from 1–1024 ng g−1, in a top 5 cm layer of a 155 cm thick sea ice was calculated using the radiative transfer model: TUV-snow. Sea ice albedo is surprisingly unresponsive to black carbon additions up to 100 ng g−1 with a decrease in albedo to 98.7% of the original albedo value due to an addition of 8 ng g−1 of black carbon in first year sea ice compared to an albedo decrease to 99.6% for the same black carbon mass ratio increase in multi-year sea ice. The first year sea ice proved more responsive to black carbon additions than the multi-year ice. Comparison with previous modelling of black carbon in sea ice suggests a more scattering sea ice environment will be less responsive to black carbon additions. Snow layers on sea ice may mitigate the effects of black carbon in sea ice. "Wet" and "dry" snow layers of 0.5, 1, 2, 5 and 10 cm were added onto the sea ice surface and the snow surface albedo calculated with the same increase in black carbon in the underlying sea ice. Just a 0.5 cm layer of snow greatly diminishes the effect of black carbon on surface albedo, and a 2–5 cm layer (less than half the e-folding depth of snow) is enough to "mask" any change in surface albedo owing to additional black carbon in sea ice, but not thick enough to ignore the underlying sea ice.

scholarly journals The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

2013 ◽  
Vol 7 (4) ◽  
pp. 1193-1204 ◽  
Author(s):  
A. A. Marks ◽  
M. D. King
Keyword(s):  
Sea Ice ◽  
Black Carbon ◽  
Cross Sections ◽  
Arctic Sea Ice ◽  
Radiative Transfer Model ◽  
First Year ◽  
Transfer Model ◽  
Snow Layer ◽  
Arctic Sea ◽  
Visible Wavelengths

Abstract. The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g−1, in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g−1 of black carbon causes a decrease to 98.7% of the original albedo for first-year sea ice compared to a decrease to 99.7% for the albedo of multi-year sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g−1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2–5 cm snow layer (less than the e-folding depth of snow) is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

scholarly journals Snow Depth Retrieval on Arctic Sea Ice Using Under-Ice Hyperspectral Radiation Measurements

2021 ◽  
Vol 9 ◽  
Author(s):  
Philipp Anhaus ◽  
Christian Katlein ◽  
Marcel Nicolaus ◽  
Stefanie Arndt ◽  
Arttu Jutila ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
Radiative Transfer Model ◽  
Ice Thickness ◽  
First Year ◽  
Transfer Model ◽  
Remotely Operated Vehicle ◽  
Transmitted Radiation ◽  
Extinction Coefficients

Radiation transmitted through sea ice and snow has an important impact on the energy partitioning at the atmosphere-ice-ocean interface. Snow depth and ice thickness are crucial in determining its temporal and spatial variations. Under-ice surveys using autonomous robotic vehicles to measure transmitted radiation often lack coincident snow depth and ice thickness measurements so that direct relationships cannot be investigated. Snow and ice imprint distinct features on the spectral shape of transmitted radiation. Here, we use those features to retrieve snow depth. Transmitted radiance was measured underneath landfast level first-year ice using a remotely operated vehicle in the Lincoln Sea in spring 2018. Colocated measurements of snow depth and ice thickness were acquired. Constant ice thickness, clear water conditions, and low in-ice biomass allowed us to separate the spectral features of snow. We successfully retrieved snow depth using two inverse methods based on under-ice optical spectra with 1) normalized difference indices and 2) an idealized two-layer radiative transfer model including spectral snow and sea ice extinction coefficients. The retrieved extinction coefficients were in agreement with previous studies. We then applied the methods to continuous time series of transmittance and snow depth from the landfast first-year ice and from drifting, melt-pond covered multiyear ice in the Central Arctic in autumn 2018. Both methods allow snow depth retrieval accuracies of approximately 5 cm. Our results show that atmospheric variations and absolute light levels have an influence on the snow depth retrieval.

scholarly journals Level 2 processing for the imaging Fourier transform spectrometer GLORIA: derivation and validation of temperature and trace gas volume mixing ratios from calibrated dynamics mode spectra

2015 ◽  
Vol 8 (6) ◽  
pp. 2473-2489 ◽  
Author(s):  
J. Ungermann ◽  
J. Blank ◽  
M. Dick ◽  
A. Ebersoldt ◽  
F. Friedl-Vallon ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Horizontal Resolution ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ionization Mass ◽  
Fourier Transform Spectrometer ◽  
Upper Troposphere ◽  
Mixing Ratios

Abstract. The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an airborne infrared limb imager combining a two-dimensional infrared detector with a Fourier transform spectrometer. It was operated aboard the new German Gulfstream G550 High Altitude LOng Range (HALO) research aircraft during the Transport And Composition in the upper Troposphere/lowermost Stratosphere (TACTS) and Earth System Model Validation (ESMVAL) campaigns in summer 2012. This paper describes the retrieval of temperature and trace gas (H2O, O3, HNO3) volume mixing ratios from GLORIA dynamics mode spectra that are spectrally sampled every 0.625 cm−1. A total of 26 integrated spectral windows are employed in a joint fit to retrieve seven targets using consecutively a fast and an accurate tabulated radiative transfer model. Typical diagnostic quantities are provided including effects of uncertainties in the calibration and horizontal resolution along the line of sight. Simultaneous in situ observations by the Basic Halo Measurement and Sensor System (BAHAMAS), the Fast In-situ Stratospheric Hygrometer (FISH), an ozone detector named Fairo, and the Atmospheric chemical Ionization Mass Spectrometer (AIMS) allow a validation of retrieved values for three flights in the upper troposphere/lowermost stratosphere region spanning polar and sub-tropical latitudes. A high correlation is achieved between the remote sensing and the in situ trace gas data, and discrepancies can to a large extent be attributed to differences in the probed air masses caused by different sampling characteristics of the instruments. This 1-D processing of GLORIA dynamics mode spectra provides the basis for future tomographic inversions from circular and linear flight paths to better understand selected dynamical processes of the upper troposphere and lowermost stratosphere.

scholarly journals Simulation of Thermodynamic Features of a Thunderstorm Event over Dhaka using WRF-ARW Model

2018 ◽  
Vol 37 ◽  
pp. 131-145
Author(s):  
Md Mijanur Rahman ◽  
Md Abdus Samad ◽  
SM Quamrul Hassan
Keyword(s):  
Convective Available Potential Energy ◽  
Model Performance ◽  
Vertical Wind Shear ◽  
Longwave Radiation ◽  
Final Analysis ◽  
Horizontal Resolution ◽  
Cumulus Parameterization ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model

An attempt has been made to simulate the thermodynamic features of the thunderstorm (TS) event over Dhaka (23.81°N, 90.41°E) occurred from 1300 UTC to 1320 UTC of 4 April 2015 using Advanced Research dynamics solver of Weather Research and Forecasting model (WRF-ARW). The model was run to conduct a simulation for 48 hours on a single domain of 5 km horizontal resolution utilizing six hourly Global Final Analysis (FNL) datasets from 0600 UTC of 3 April 2015 to 0600 UTC of 5 April 2015 as initial and lateral boundary conditions. Kessler schemes for microphysics, Yonsei University (YSU) scheme for planetary boundary layer (PBL) parametrization, Revised MM5 scheme for surface layer physics, Rapid Radiative Transfer Model (RRTM) for longwave radiation, Dudhia scheme for shortwave radiation and Kain–Fritsch (KF) scheme for cumulus parameterization were used. Hourly outputs produced by the model have been analyzed numerically and graphically using Grid Analysis and Display System (GrADS). Deep analyses were carried out by examining several thermodynamic parameters such as mean sea level pressure (MSLP), wind pattern, vertical wind shear, vorticity, temperature, convective available potential energy (CAPE), relative humidity (RH) and rainfall. To validate the model performance, simulated values of MSLP, maximum and minimum temperature and RH were compared with observational data obtained from Bangladesh Meteorological Department (BMD). Rainfall values were compared with that of BMD and Tropical Rainfall Measuring Mission (TRMM) of National Aeronautics and Space Administration (NASA). Based on the comparisons and validations, the present study advocates that the model captured the TS event reasonably well.GANIT J. Bangladesh Math. Soc.Vol. 37 (2017) 131-145

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.

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