Detection of small-scale roughness and refractive index of sea ice in passive satellite microwave remote sensing

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Abstract

Polar ice masses and sheets are sensitive indicators of climate change. Small-scale surface roughness significantly impacts the microwave emission of the sea ice/snow surface; however, published results of surface roughness measurements of sea ice are rare. Knowing the refractive index is important to discriminate between objects. In this study, the small-scale roughness and refractive index over sea ice are estimated with AMSR-E observations and a unique method. Consequently, the small-scale surface roughness of 0.25 cm to 0.5 cm at AMSR-E 6.9 GHz shows reasonable agreement with the results of known observations, ranging from 0.2 cm to 0.6 cm for the sea ice in the Antarctic and Arctic regions. The refractive indexes are retrieved from 1.6 to 1.8 for winter, from 1.2 to 1.4 for summer in the Arctic and the Antarctic, which are similar to those of the sea ice and results from previous studies. This research shows the physical characteristics of the sea ice edges and melting process. Accordingly, this investigation provides an effective procedure for retrieving the small-scale roughness and refractive index of sea ice and snow. Another advantage of this study is the ability to distinguish sea ice from the sea surface by their relative small-scale roughness.

Introduction

Sea ice covers a significant fraction of the global oceans (5% to 8%) and is one of the most important parameters in the global climate system (Comiso et al., 2003). Quantitative information on the annual variability of the sea ice is vital in understanding the surface energy budget (Gorodetskaya et al., 2008), atmospheric circulation (Tjernström & Mauritsen, 2009), precipitation and moisture fluxes (Gutowski et al., 2007), clouds (Abbot & Tziperman, 2009), the Earth's fresh water (Salminen et al., 2009), and global temperature (Qu & Hall, 2005).

Aircraft observations have showed that the emissivity of bare soil, dense vegetation, wet snow, and new ice is sufficiently uniform on a scale of kilometers to allow retrievals of surface information from satellite microwave instruments (Hewison, 2001). However, dry snow and older ice types have highly variable emissivity. The spectrum of new ice is similar to that of land surfaces. The emissivity is relatively high and little changes with frequency, although emissions are more strongly polarized. Generally, the sea ice derived with a microwave imager has lower concentration than the actual sea ice (Walsh & Chapman, 2001).

A large contrast in emissivity exists between sea ice and water measured at microwave frequency. Polarization is used as a sensitive indicator of sea ice concentration (IC). However, complications arise because of other geophysical factors that influence the radiometric brightness of both the sea surface and sea ice, due to the wind-roughened seas, cloud droplets, and atmospheric water vapor. These create errors of < 10% in estimates of IC and extent (Steffen & Schweiger, 1991).

Surface roughness is known to significantly impact the microwave emission of the sea ice/snow surface. In general, surface roughness has been modeled by the geometric optics for large-scale roughness and the physical optics for small-scale roughness relative to the wavelength (Ulaby and Elachi, 1990). Large-scale roughness gives geometric specular reflection, and its effects are not modeled except for the ocean surface (English & Hewison, 1998). Meanwhile, small-scale roughness is important in determining the surface reflectivity. In this study, a semiempirical model based on the incoherent approach is used for small-scale surface roughness, which corresponds to identifying the height probability density function with a Gaussian distribution of zero mean and variance as follows (Wu and Fung, 1972, Choudhury et al., 1979):RR=RSexp[(4πσcosθλ)2]where R is the reflectivity, σ is the small-scale roughness height (Ulaby et al., 1982), λ is the wavelength, θ is the incidence angle. Subscripts R and S mean ‘rough’ and ‘specular’, respectively.

In general, the effect of roughness on emissivity is determined by sensitivity tests using forward models, by modeling the brightness temperature TB as a function of incidence angle, or by polarization ratios. Published results of surface roughness measurements of sea ice are rare (Manninen, 1997). Surface roughening of first-year ice has been suggested as a source for the increased backscatter which has been noted but not tabulated-again due to the limited data available (Carsey, 1989). Onstott and Gogineni (1985) observed a separate, distinct, and sharp change in surface roughness due to melt processes. The exact surface roughness changes over the winter and spring have not been observed or modeled.

In addition, the refractive index is crucial to determine the characteristics of objects and discriminate between them (Kramer, 2002). Many surface forward models require a priori information on the refractive index. However, this is problematic due to the heterogeneity and variation of surface in the field of view.

The scientific objective of this study is to determine the characteristics and distributions of the small-scale surface roughness and the refractive index of the sea ice and snow surface in the Polar Regions from the passive microwave satellite data. In addition, this study also validates the findings, and seeks a systematic procedure for estimating the roughness and refractive index.

Section snippets

Data and rough surface reflectivity

In this study, the Advanced Microwave Scanning Radiometer-Earth (AMSR-E) daily level-3 (L3) 25-km data are used for TB. The AMSR-E sensor measures vertically (V) and horizontally (H) polarized radiances at 6.925, 10.65, 18.7, 23.8, 36.5, and 89.0 GHz. The dates are 1 February and 1 August, 2007.

Basically, the ice temperature Ts is determined at AMSR-E 6.925 GHz as follows (Comiso et al., 2003):Ts=TB,V(6.9)/[1RR,V(6.9)].

In this investigation, the V and H reflectivities are assumed to be estimated

Polarization and specular surface reflectivity

Fig. 1 shows one result of the validation of the Hong approximation for ice, dry snow, and water at microwave frequencies. The refractive indexes of ice, snow, and water at 0 °C (Sadiku, 1985) are assumed to be 1.782 + 3.334 × 10 3i, 1.016 + 6.339 × 10 5i, and 8.227 + 2.341i at 6 GHz, 1.78 + 2.4 × 10 3i, 1.016 + 7.066 × 10 5i, and 5.234 + 2.933i at 20 GHz, respectively. The bias of RS,H from the Hong approximation is negligible for ice and snow. The bias for water is within 0.005. However, the relative bias is very

Summary and discussion

The small-scale roughness and refractive index of sea ice in the Arctic and Antarctic are retrieved using AMSR-E observations. A unique technique based on dielectric properties, polarization ratios, and surface emissivity is used. The effective rough emissivity and reflectivity at AMSR-E 6.9 GHz are estimated for V and H polarizations. Next, the specular reflectivity for the V polarization is estimated using the Hong approximation and the angular property of the roughness effect on each

Acknowledgements

The authors thank anonymous reviewers for constructive comments on the manuscript. This work is supported by the National Meteorological Satellite Center (Project No. 153-3100-3137-302-210-13).

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