Verification Against Ice Extent from NOAA

The ice concentration analysis is compared with the sea ice extent from NOAA Interactive Multisensor Snow and Ice Mapping System(IMS) (Chen et al., 2012). The ice/no ice based IMS product is manually created by trained analysts using available satellite imagery, sev-eral automated snow mapping algorithms, and other ancillary data. The spatial resolution of the IMS data is 16 km². The IMS product is resampled into the SSM/I grid. The valida-tion using IMS data follows Scott et al. (2013), Buehner et al. (2013) and uses a threshold of 40% to transform the ice analysis and the SSM/I ice concentration into ice/no ice. 40%

is used because IMS ice extent product uses 40% to correlate with National Ice Center (NIC) ice chart. The total proportion correct (PC) is defined as the percentage of pixels that are correctly labeled as ice or water compared to the IMS product. The proportion correct for ice is defined as the number of pixels that are correctly labeled as ice compared to the IMS product divided by the total number of ice pixels in the IMS product. The proportion correct for water is defined as the number of pixels that are correctly labeled as water compared to the IMS product divided by the total number of water pixels in the IMS product.

The verification is done over three subregions: the CAA, the Arctic Ocean and Baffin Bay. Verification scores for these three regions are plotted in Figure 5.6 for each day of the experiment from June 1 to August 31. Note that IMS data for July 23 is missing and not included in the verification. For the CAA region, the ice extent calculated using the IC from SSM/I agrees with the IMS product very well until mid July. After that, the SSM/I data quality degrades greatly, which corresponds to the ice melt period in the CAA. The assimilation of MODIS data is shown to improve the total proportion correct by 5% to 10%

in the CAA region during the melt. For the Arctic Ocean and Baffin Bay, the differences between the analysis and SSM/I ice concentration were largest in late August and middle July, respectively. These periods correspond to the timing of sea ice melt in these regions.

The proportion correct for ice and water for each day in the CAA are shown in Fig-ure 5.7. It can be seen that more ice has been correctly identified in the analysis than

when the original SSM/I data is used. However, it also seems less water has been correctly identified in the analysis than when the original SSM/I data is used. To understand this, the number of pixels that are correctly and falsely classified for both analysis and SSM/I for water and ice, respectively, are shown in Figure 5.8. The number of pixels that are cor-rectly identified as ice in the analysis is larger than that of the SSM/I, with the number of pixels that are falsely identified as ice smaller than the SSM/I during the melt. Meanwhile, the number of pixels that are correctly/falsely identified as water does not change much between the analysis and the SSM/I. Thus, it can be concluded that the analysis improves the ice estimation by identifying more ice pixels during melt, while the estimation of water does not change much.

The background ice concentration state used by the assimilation is the analysis from the previous day projected forward in time. The analysis increment is defined as the difference between ice concentration analysis and background ice concentration. The ice concentra-tion (IC) data increment is defined here as the difference between the ice concentraconcentra-tion analysis and the original SSM/I data. The distribution of analysis increments and IC data increments for all the days in the study period are shown in Figure 5.9a. It can be seen that the analysis increments generally follow the normal distribution. The IC data incre-ments are also of interest to known how the data assimilation results improve the original SSM/I sea ice concentration data. The distribution of the IC data increments for the study period is shown in Figure 5.9b. The distribution of IC data increments has a positive bias.

This agrees with the fact that SSM/I sea ice concentration tends to underestimate the ice concentration. Thus, the analysis has improved the overall accuracy of the original ice concentration data by increasing the ice concentration.

For the CAA region, the daily sea ice extent and daily sea ice extent change based on the SSM/I ice concentration and the ice analysis for the three month study period in 2007 were calculated (Figure 5.10). It can be seen that both the daily sea ice extent and daily sea ice extent change are smoother for the ice analysis than when using only SSM/I data.

Based on the daily ice extent change curve, it can be seen that the ice retreat in the CAA region follows a pattern, with a large daily sea ice loss phase in late June, then a daily ice increase phase in early July, and then gradual daily ice loss until the end of August.

(a) Canadian Arctic Archipelago (b) Arctic Ocean (AO)

(c) Baffin Bay (BB)

Figure 5.6: Total proportion correct for each day from June 1 to August 31 2007 for (a) Canadian Arctic Archipelago (CAA), (b) the Arctic Ocean (AO) and (c) Baffin Bay (BB).

(a) Proportion correct for Ice (b) Proportion correct for Ice

Figure 5.7: Proportion correct for (a) Ice and (b) water, for each day from June 1 to August 31 2007 for the CAA.

(a) # of ice pixels correctly/falsely classified (b) # of water pixel correctly/falsely classified Figure 5.8: Number of pixel correctly/falsely classified for (a) Ice and (b) water, for each day from June 1 to August 31 2007 for the CAA.

(a) Model increment (b) Ice data increment

Figure 5.9: Distribution of the increments (a) Model increment and (b) IC data increment.

(a) (b)

Figure 5.10: (a) the daily ice extent and (b) the daily ice extent change for the CAA from June 1st to August 31th.