Greenland , Canadian and Icelandic land-ice albedo grids ( 2000 – 2016 )

Albedo, Latin for ‘whiteness’, is a term used to describe the amount of sunlight reflected by the ground. Fresh snow albedo can exceed 85%, making it among the most reflective natural substances. Warm conditions promote snow crystal metamorphosis that, like the presence of liquid water, bring snow albedo down below 65%. With the darkening, caused by the metamorphosis, absorbed solar energy thus increases by roughly a factor of two. Seasonal snow melts over the lower reaches of a glacier leading to the exposure of bare ice with albedo below 55%. Impurities such as dust, black carbon or microbes can bring glacier-ice albedo below 30%, meaning that snow ablation gives way to impurity-rich, bare glacier ice which increases absorbed sunlight by more than a factor of three. The thickness of the winter snow layer and the intensity of spring melt are important determinants of the annual glacier-ice melt, as the amount of snow cover governs the timing of darker ice exposure; the earlier the exposure, the more ice can melt. Because snow and ice albedo properties make it an amplifier of climate change, surface albedo has been designated as an Essential Climate Variable and a Target Requirement for climate monitoring (WMO 2011). Polar orbiting satellites facilitate albedo mapping with Arctic coverage multiple times per day in clear-sky conditions. Satellite-based retrievals of surface albedo depend on accurate compensation of the intervening atmosphere. Thus, without ground truth, the satellite retrievals are uncertain. In Greenland, snow and ice albedo is monitored by automatic weather stations (AWSs) from The Greenland Climate Network (GC-Net; Steffen et al. 1996) since 1995 and after 2007 from The Programme for Monitoring of the Greenland Ice Sheet (PROMICE; van As et al. 2013). Using the GC-Net data, satellite-derived albedo values are compared with ground data (e.g. Stroeve et al. 2013). Here, we present comparisons of daily GC-Net and PROMICE albedo data to satellite-derived albedo from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A1 product (Hall et al. 1995). MOD10A1 data have been available since May 2000 and are here de-noised, gap-filled and calibrated into a daily 500 × 500 m grid covering Greenland, Iceland and the Canadian Arctic glaciers (Fig. 1).

Albedo, Latin for 'whiteness', is a term used to describe the amount of sunlight reflected by the ground. Fresh snow albedo can exceed 85%, making it among the most reflective natural substances. Warm conditions promote snow crystal metamorphosis that, like the presence of liquid water, bring snow albedo down below 65%. With the darkening, caused by the metamorphosis, absorbed solar energy thus increases by roughly a factor of two. Seasonal snow melts over the lower reaches of a glacier leading to the exposure of bare ice with albedo below 55%. Impurities such as dust, black carbon or microbes can bring glacier-ice albedo below 30%, meaning that snow ablation gives way to impurity-rich, bare glacier ice which increases absorbed sunlight by more than a factor of three.
The thickness of the winter snow layer and the intensity of spring melt are important determinants of the annual glacier-ice melt, as the amount of snow cover governs the timing of darker ice exposure; the earlier the exposure, the more ice can melt. Because snow and ice albedo properties make it an amplifier of climate change, surface albedo has been designated as an Essential Climate Variable and a Target Requirement for climate monitoring (WMO 2011).
Polar orbiting satellites facilitate albedo mapping with Arctic coverage multiple times per day in clear-sky conditions. Satellite-based retrievals of surface albedo depend on accurate compensation of the intervening atmosphere. Thus, without ground truth, the satellite retrievals are uncertain. In Greenland, snow and ice albedo is monitored by automatic weather stations (AWSs) from The Greenland Climate Network (GC-Net; Steffen et al. 1996) since 1995 and after 2007 from The Programme for Monitoring of the Greenland Ice Sheet (PROMICE; van As et al. 2013). Using the GC-Net data, satellite-derived albedo values are compared with ground data (e.g. Stroeve et al. 2013).
Here, we present comparisons of daily GC-Net and PROMICE albedo data to satellite-derived albedo from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A1 product (Hall et al. 1995). MOD10A1 data have been available since May 2000 and are here de-noised, gap-filled and calibrated into a daily 500 × 500 m grid covering Greenland, Iceland and the Canadian Arctic glaciers (Fig. 1).

Daily albedo from MODIS
The MOD10A1 product contains daily snow extent, snow albedo, fractional snow cover and a data quality assessment at 500 × 500 m resolution (Hall et al. 1995). Both NASA Terra and Aqua satellites are equipped with MODIS sensors. Here, Terra data are chosen over Aqua data as they

MOD10A1 de-noising, smoothing and gap-filling
Inspection of the C5 and C6 albedo imagery reveals that, despite some cases when pixel quality is coded 'best' or 'good', cloud artifacts resembling shadows, aircraft condensation trails, thin clouds, and cloud edges can persist, often over the brightest areas presumably where there is less distinction between clouds and clean snow.
Fortunately, because the artifacts introduce abrupt temporal departures in the albedo (α) time series, it is possible to reject them on a pixel by pixel basis using temporal statistics from multi-day albedo (α N-days ) samples. Here, an 11 day α N-days sample size is selected; five days before and after each day i. On a pixel-by-pixel basis, statistics are computed from α N-days . The number of days N does not always represent 11 albedo values because some days a pixel may already be dismissed as cloudy, missing or of inadequate quality. Only cases with at least four samples per 11-day window are considered sufficient for an albedo estimate for that day and pixel. The final pixel by pixel daily albedo values are taken as the 11-day average of available values below a fractional noise threshold (D) value of 0.4, with D computed as:

D i = | (α N-days -median(α N-days )) / median(α N-days ) |
For low albedo variability areas, for example the dry snow area, when the standard deviation α N-days is under 0.03, then a more strict D threshold of 0.1 is used. The procedure has both a smoothing and a gap filling effect on the albedo time series. The resulting data product can be viewed at https://tinyurl.com/PROMICE-albedo-Greenland.

MODIS validation using ground-truth albedo
Daily PROMICE and GC-Net AWS albedo values are compared with the nearest 500 × 500 m resolution MOD10A1 C5 and C6 values for all stations in each of 9 or 16 years that span 2007 to 2016 or 2000 to 2015, respectively. Figure 2 provides an example for C6 data illustrating a typical result of the de-noising procedure, yielding an increased number of MODIS values, increased correlation, reduced root mean squared difference (RMSD) shifting regression slope closer to unity and no real change in bias. Table 1 lists summary statistics for the multi-year, multistation comparison with MOD10A1 C5 and C6. The MOD10A1 skill either improves or is stable in the C5 to C6 update. The average bias and root mean squared difference decrease and the correlation and average count of days increase. The number of compared station-years increases. From raw to de-noised, there is also a consistent improvement in agreement between the satellite and ground data ( Table 2). In the de-noised product, the RMSDs are 0.08 for PROMICE stations that are concentrated in the ablation area or 0.05 for GC-Net stations that are concentrated in the accumulation area. e lower GC-Net correlation and RMSD values result from the mostly dry snow areas where albedo variability is small. For PROMICE stations which are concentrated in the ablation area (and for the GC-Net Jakobshavn Ablation Region (JAR) stations), the larger MOD10A1 pixel footprint includes a complex contribution from some combination of e.g., crevasses, snow patches and concentrated or distributed snow and ice impurities such as cryoconite. e root mean squared di erence is probably more attributable to the ground data because they have a c. 5-10 m 2 footprint, four orders of magnitude smaller than the MOD10A1 500 m × 500 m footprint.

MODIS validation using GC-Net albedo
GC-Net albedo data, having a time coverage longer than 10 years, are compared with C5 and C6 to evaluate accuracy in year-to-year albedo changes. MOD10A1 Collection 6 (Hall & Riggs 2016) compensates MODIS sensor degradation found in Collection 5 (Lyapustin et al. 2014). C6 is found to compensate the temporal trend bias in dry snow areas (Fig. 3A). e trend bias is usually smaller or nonexistent for darker targets such as the ablation area (Fig.  3B). e 0.02 albedo o set at the Summit site is partly attributable to the bias described in the following.

MOD10A1 sun angle bias
Whereas the adjustments to Collection 6 eliminate a spurious darkening trend concentrated over snow and in the northern part of Greenland (Polashenski et al. 2015), both Collections 5 and 6 MOD10A1 albedo products have a residual bias based on the angle of the sun above the horizon. e bias is evident over nearly 20° of latitude range of the PROMICE and GC-Net data. In April (days 91-120), there is no bias in southern Greenland but a c. 4% bright bias in the northern 2/3 of Greenland (Fig. 4A). By June (days 152-181), the pattern of the bias has shifted to a more uniform dark bias strongest in the south (Fig. 4B). e bias varies over time and latitude (see the animation: https://ti nyurl.com/bias-vs-lat). We correct the Collection 6 bias according to the daily variation in the regression line (blue dashed line in Fig. 4A, trends in Fig. 4B). e calibration   assumes there is no sun-angle-dependent bias in the PRO-MICE and GC-Net data.

MODIS albedo for Iceland and the Canadian Arctic
The regional product also includes albedo for glaciated areas in Iceland, Jan Mayen and the Canadian Arctic. The occurrence of clouds reduces the coverage of the product, in the case of land ice, especially at the lowest elevations often near oceans. Iceland has data coverage less than half of that of most areas of Greenland. Areas of the Canadian Arctic such as the Devon Ice Cap also have reduced time coverage compared to Greenland, which has a stronger cloud clearing effect from its high pressure areas often centered over the ice sheet.

A new PROMICE data product
The methodology developed here for de-noising, gap filling, and bias correction for the MOD10A1 albedo product yields an enhanced MODIS MOD10A1 Climate Data Record available for download through the PROMICE database via the webpage www.promice.dk