Abstract
The Canadian Arctic Archipelago (CAA) presents unique challenges to the determination of melt onset (MO) using remote sensing data. High spatial resolution data is required to discern melt onset among the islands and narrow waterways of the region. Current passive microwave retrievals use daily averaged 19 GHz and 37 GHz data from the multi-channel microwave radiometer (SMMR) and/or the special sensor microwave/imager (SSM/I). The development of a new passive microwave melt onset method capable of using higher resolution data is desirable. The new passive microwave melt onset method described here, named the Dynamic Threshold Variability Method (DTVM), uses higher resolution data from the 37 GHz vertically-polarized channel from the advanced microwave scanning radiometers (AMSR-E and AMSR-2). The DTVM MO detection methodology differs from previously presented passive microwave Arctic MO methods in that it does not use a fixed threshold of a brightness temperature parameter. Instead, the DTVM determines MO dates based on the distribution of dates corresponding to the exceedance of a range of brightness temperature variability thresholds. The method also uses swath data instead of daily averaged brightness temperatures, which is found to lead to improved melt detection. Two current passive microwave MO methods are compared and evaluated for applicability in the CAA alongside the DTVM. The DTVM provides MO dates at a higher spatial resolution than earlier methods in addition to higher correlation with MO dates from surface air temperature (SAT) reanalyses. It is found that, for some years, MO dates in the CAA exhibit a latitudinal dependence, while in other years the MO dates in the CAA are relatively uniform across the domain.
Highlights
Melt onset (MO) indicates a transition from winter to spring and is an important component of the Arctic sea ice energy balance [1,2]
Comparison of Passive Microwave MO Methods The three passive microwave methods described in Section 3, advanced horizontal range algorithm (AHRA), passive microwave algorithm (PMW) and Dynamic Threshold Variability Method (DTVM), are compared and evaluated for their applicability to MO estimation in the Canadian Arctic Archipelago (CAA)
To investigate the possibility that weather effects could be impacting MO dates, we examined the values of the polarization and gradient ratios that are used as weather filters in passive microwave ice concentration retrieval algorithms [19]
Summary
Melt onset (MO) indicates a transition from winter to spring and is an important component of the Arctic sea ice energy balance [1,2]. The sea-ice or snow surface becomes wet, causing a reduction of surface albedo. The reduced albedo allows for greater absorption of shortwave solar radiation, which can lead to increased surface melt [3]. As the ice begins to break-up, the appearance of open water leads to increased absorption of solar radiation into the ocean, which can both accelerate bottom melt and delay freeze-up [4,5]. Melt onset dates are correlated with melt season length [6], and the September minimum sea ice extent, making long term MO information of value for climate studies [7]
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