## 4 Applications  
Air temperature measurements at meteorological stations are the foremost ground data source for the assessment of snow melt related QuikSCAT products. A temperature increase relates to melt events during the winter [40] as well as during spring (e.g., [11, 15]). The mid-winter backscatter change is often a result of rain-on-snow events. A general increase of air temperature above zero degree Celsius corresponds to backscatter changes in spring. Backscatter drops as soon as the daily maximum air temperature exceeds zero degrees Celsius and increases to summer level when minimum daily air temperatures rise above freezing [12]. Snowdepth records can be also suitable for the assessment of the end of snowmelt [11, 12, 24]. Snow distribution can however vary within the large footprint and station point data are less representative. [24] found an agreement of the end of snowmelt with snow depth records within \(\pm\)7 days for more than 90% of analyzed meteorological station measurements. The relatively large sensor footprint size becomes more of a constraint in mountainous areas. The timing of snowmelt is related to CO\({}_{2}\) fluxes [41]. QuikSCAT products have therefore been compared to eddy flux tower [12] and xylum sap flow measurements [16], and (Gross Primary Production) GPP estimates [33]. A flux increase above winter levels (release of carbon) starts as soon as the snow starts melting. The following switch from CO\({}_{2}\) source to sink is close to the end of seasonal snowmelt [36]. Mid-winter short term melt events have severe impact on wild life. Unguilates such as reindeer and caribou need to dig through the snow layer to reach their winter forage beneath. Ice crusts form when the snow refreezes after rain-on-snow events. This snow grain metamorphosis after thawing and refreezing [2, 42] results in a significant increase of Ku-band backscatter as discussed in the previous section. SeaWinds has been used to assess the temporal frequency and extent of such events under the view point of reindeer herding over Northern Eurasia from 2000 to 2008 [40]. In this case also human communities which depend on reindeer herding are affected. Midwinter events over 60 \({}^{\circ}\)N are most common in western Siberia, Scandinavia and parts of Alaska (see Figure 3). They are less frequent in the Canadian Arctic and central to east Siberia. They are however predicted to increase over central Siberia [43]. Snow cover information is also required for permafrost distribution modeling (e.g., [44, 45]). Its dynamics impact albedo and it insulates the ground. The timing of steady snow cover destruction also coincides with the rise of land surface temperature above zero degree Celsius and thus the initiation of seasonal active layer thawing. [PERSON] _et al._[34] used the threshold based method of [16, 33] to detect the incipient thaw timing with SeaWinds. Results have been compared to modelled snow water increase over a number of North American basins. Almost 50% of the Pan-Arctic area shows a difference of less than a week between primary than from QuikScat and modelled snow water increase. Spring flooding has been also related to melt patterns detected with Ku-band scatterometry [17]. Figure 4: Ten years (2000–2009) of spring snow melt dynamics based on diurnal thawing and refreeze detection [12]: (a) mean day of snowmelt start, (b) mean day of snowmelt end, (c) standard deviation of start of snowmelt in days, (d) standard deviation of end of snowmelt in days, (e) mean duration of spring snowmelt period, (f) standard deviation of spring snowmelt duration. To date no extensive direct comparisons between different SeaWinds snowmelt products have been made. Snowmelt dates have also been compared to ground measurements of onset of xylem sap flow in pine trees at five sites in Alaska for the years 2000 and 2001 [16]. Those results have been compared to the beginning and end of diurnal thaw and refreeze cycling [12]. The end of diurnal cycling gave best agreement with the onset of xylum sap flow.