Abstract. The accurate knowledge of sea ice parameters, including sea ice thickness and
snow depth over the sea ice cover, is key to both climate studies and data
assimilation in operational forecasts. Large-scale active and passive remote
sensing is the basis for the estimation of these parameters. In traditional
altimetry or the retrieval of snow depth with passive microwave remote
sensing, although the sea ice thickness and the snow depth are closely
related, the retrieval of one parameter is usually carried out under
assumptions over the other. For example, climatological snow depth data or as
derived from reanalyses contain large or unconstrained uncertainty, which
result in large uncertainty in the derived sea ice thickness and volume. In
this study, we explore the potential of combined retrieval of both sea ice
thickness and snow depth using the concurrent active altimetry and passive
microwave remote sensing of the sea ice cover. Specifically, laser altimetry
and L-band passive remote sensing data are combined using two forward models:
the L-band radiation model and the isostatic relationship based on buoyancy
model. Since the laser altimetry usually features much higher spatial
resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS)
satellite, there is potentially covariability between the observed snow
freeboard by altimetry and the retrieval target of snow depth on the spatial
scale of altimetry samples. Statistically significant correlation is
discovered based on high-resolution observations from Operation IceBridge
(OIB), and with a nonlinear fitting the covariability is incorporated in the
retrieval algorithm. By using fitting parameters derived from large-scale
surveys, the retrievability is greatly improved compared with the
retrieval that assumes flat snow cover (i.e., no covariability).
Verifications with OIB data show good match between the observed and the
retrieved parameters, including both sea ice thickness and snow depth. With
detailed analysis, we show that the error of the retrieval mainly arises from
the difference between the modeled and the observed (SMOS) L-band brightness
temperature (TB). The narrow swath and the limited coverage of the sea ice
cover by altimetry is the potential source of error associated with the
modeling of L-band TB and retrieval. The proposed retrieval methodology can
be applied to the basin-scale retrieval of sea ice thickness and snow depth,
using concurrent passive remote sensing and active laser altimetry based on
satellites such as ICESat-2 and WCOM.
On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data