Retrieving the refractive index, emissivity, and surface temperature of polar sea ice from 6.9 GHz microwave measurements: A theoretical development

Lee, Sang-Moo; Sohn, Byung-Ju

doi:10.1002/2014jd022481

Cited by 25 publications

(43 citation statements)

References 44 publications

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“…It is because n r (in the range of 1.0–1.8) is nearly invariant for snow and sea ice over that frequency range and n i is very small (in the range of 10 −1 to 10 −4 ; Sadiku, ; Ulaby et al, ; Vant et al, ; Warren & Brandt, ; Warren, ). Because of that N r obtained from 6.9 GHz AMSR‐E measurements (Lee & Sohn, ) can be used for other channels as well (here 10.65, 18.7, 23.8, and 36.5 GHz channels). Once N r is prescribed in equation , specular emissivity and roughness factor at given σ values are determined, and therefore, τ sca can be determined.…”

Section: Theoretical Background and Methodologymentioning

confidence: 99%

“…It is because n r (in the range of 1.0-1.8) is nearly invariant for snow and sea ice over that frequency range and n i is very small (in the range of 10 À1 to 10 À4 ; Sadiku, 1985;Ulaby et al, 1986;Vant et al, 1978;Warren & Brandt, 2008;Warren, 1984). Because of that N r obtained from 6.9 GHz AMSR-E measurements (Lee & Sohn, 2015) can be used for other channels as well (here 10. 65,18.7,23.8,and 36.5 GHz channels).…”

Section: Solving the Roughness And Volume Scattering Effectsmentioning

confidence: 99%

“…But, at 36.5 GHz where the mean σ value exceeds 0.3, result suggests a relatively large roughness effect on the emissivity, especially when N r is large. However, considering that most of the Arctic area shows N r smaller than 1.6 (as shown in Figure 1a of Lee & Sohn, 2015), the roughness effect is thought to be minor even for 36.5 GHz, as depicted in Figure 2. This result is consistent with Mätzler (2005), which showed that the difference in radiance between the Lambertian surface and specular surface disappears at a 55°viewing angle, implying that the roughness effect is negligible especially for conically scanning observations as in AMSR measurements.…”

Section: 1029/2018jd028688mentioning

confidence: 99%

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Impact of Ice Surface and Volume Scatterings on the Microwave Sea Ice Apparent Emissivity

2018

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Emissivity retrieval for sea ice from passive microwave measurements has been an important problem in climate/environmental research because of its link to various snow/ice variables. However, so far, it has been a difficult task because of the influences of surface and snow/ice induced volume scatterings. Here we examine the influences of scatterings on the ice emissivity from 10.65, 18.7, 23.8, and 36.5 GHz Advanced Microwave Scanning Radiometer (AMSR)‐E brightness temperatures over the Arctic Ocean. In doing so, we use a two‐dimensional roughness parameterization, modified with surface facet orientations with an assumption that the facet emission follows the Fresnel relationship. Emitting layer temperature and refractive index retrieved from AMSR‐E 6.9 GHz brightness temperature measurements were used in this study and applied to other channels of interest. We demonstrated that the obtained roughness index has a strong linear relationship with the root‐mean‐square height measured by Atmospheric Terrain Mapper on the National Aeronautics and Space Administration (NASA) P‐3 aircraft. The obtained roughness index showed that surface scattering on the emissivity is generally insignificant except for some first‐year ice regions in particular at higher frequencies. This fact implies that Fresnel relations can be applicable for most of sea ice at the low‐frequency microwave spectrum. By contrast, volume scattering is found to be significant in emissivity retrieval in case of multiyear ice. Nonetheless, volume scattering influence over first‐year ice appears to be minor. We suggest that Fresnel‐type emissivity can be estimated once a correction factor is used for removing surface scattering and volume scattering contributions from the apparent emissivity.

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Section: Theoretical Background and Methodologymentioning

confidence: 99%

Section: Solving the Roughness And Volume Scattering Effectsmentioning

confidence: 99%

Section: 1029/2018jd028688mentioning

confidence: 99%

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Impact of Ice Surface and Volume Scatterings on the Microwave Sea Ice Apparent Emissivity

2018

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“…Even though Lee and Sohn [2015] method allows to determine T s from satellite-measured brightness temperatures, it is difficult to use the method for higher frequencies. It is because the sea ice roughness effect becomes substantial at higher frequencies to apply the combined Fresnel relationship [Sohn and Lee, 2013].…”

Section: Algorithmmentioning

confidence: 99%

Differentiating between first‐year and multiyear sea ice in the Arctic using microwave‐retrieved ice emissivities

2017

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Polarized emissivities of the sea ice over the Arctic were retrieved at Advanced Microwave Scanning Radiometer–EOS 10.65, 18.7, 23.8, and 36.5 GHz channel frequencies. Results indicate that retrieved emissivities are consistent with other emissivity estimates. However, errors in the retrieved emissivity for multiyear sea ice at 23.8 and 36.5 GHz can be large up to 8% and 20%, respectively, because of ignoring the freeboard ice scattering and the use of the same emission layer as in 6.925 GHz. It is shown that the emissivity slope for first‐year ice between 10.65 and 18.7 GHz is opposite to that for multiyear sea ice, enabling a distinction between first‐year ice and multiyear ice. Using these differences in spectral features with ice types, an emissivity difference (vertically polarized emissivity difference between 10.65 and 18.7 GHz) was devised to differentiate between first‐year sea ice and multiyear sea ice. A comparison with the ice status information obtained from Cold Regions Research and Engineering Laboratory buoy measurements demonstrates that the method can separate first‐year ice from multiyear ice, implying that this technique enables us to obtain instantaneous and pixel‐level ice‐type information from space‐based passive microwave measurements.

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“…Over sea ice, a pronounced cold bias is observed in the IASI data, with a mean bias of −3.45°C (i.e., colder than the dropsonde observations). This cold bias is due to the difficulty with satellite surface emissivity retrieval over sea ice [ Lee and Sohn , ]. ERA‐Interim T a observations over sea ice were only slightly colder than the dropsonde, with a mean bias of −0.28°C.…”

Section: Evaluation Of Iasi and Era‐interim Temperaturementioning

confidence: 99%

Identification and intercomparison of surface‐based inversions over Antarctica from IASI, ERA‐Interim, and Concordiasi dropsonde data

et al. 2016

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Surface-based temperature inversions (SBIs) occur frequently over Antarctica and play an important role in climate and weather. Antarctic SBIs are examined during the austral spring of 2010 using measurements from dropsondes, ERA-Interim Atmospheric Reanalysis Model, and the recently released version 6 of the Infrared Atmospheric Sounding Interferometer (IASI) level 2 product. A SBI detection algorithm is applied to temperature profiles from these data sets. The results will be used to determine if satellite and reanalysis products can accurately characterize SBIs, and if so, then they may be used to study SBIs outside of the spring 2010 study period. From the dropsonde data, SBIs occur in 20% of profiles over sea ice and 54% of profiles over land. IASI and ERA-Interim surface air temperatures are found to be significantly warmer than dropsonde observations at high plateau regions, while IASI surface air temperatures are colder over sea ice. IASI and ERA-Interim have a cold bias at nearly all levels above the surface when compared to the dropsonde. SBIs are characterized by their frequency, depth, and intensity. It is found that SBIs are more prevalent, deeper, and more intense over the continent than over sea ice, especially at higher surface elevations. Using IASI and ERA-Interim data the detection algorithm has a high probability of detection of SBIs but is found to severely overestimate the depth and underestimate the intensity for both data sets. These overestimation and underestimation are primarily due to the existence of extremely shallow inversion layers that neither satellite nor reanalysis products can resolve.The scientific objective of the Concordiasi field campaign was to combine innovative measurements and modeling for better analysis and prediction of weather over Antarctica [Rabier et al., 2010;Wang et al., 2013]. Dropsondes deployed from the driftsonde system provided temperature profiles during the Austral BOYLAN ET AL.SURFACE-BASED INVERSIONS OVER ANTARCTICA 9089

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Retrieving the refractive index, emissivity, and surface temperature of polar sea ice from 6.9 GHz microwave measurements: A theoretical development

Cited by 25 publications

References 44 publications

Impact of Ice Surface and Volume Scatterings on the Microwave Sea Ice Apparent Emissivity

Impact of Ice Surface and Volume Scatterings on the Microwave Sea Ice Apparent Emissivity

Differentiating between first‐year and multiyear sea ice in the Arctic using microwave‐retrieved ice emissivities

Identification and intercomparison of surface‐based inversions over Antarctica from IASI, ERA‐Interim, and Concordiasi dropsonde data

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