Status of the Current SSMI/S Algorithm

2. Status of the Current SSMI/S Algorithm • A-priori fixed reference emissivity spectra • 100% First-Year (FY) Ice – from observations • 100 % Multi-Year (MY) Ice - from observations • 100 Ocean Water (W) - from FASTEM-3 EM model for calm seas and Tskin = 272 K • A-priori emissivity spectra for a range of fractions • Generated using the following expression at each imaging frequency/polarization ελp = εwλpCw + εfyλpCfy + εmyλpCmy and Ct = Cw + Cmy + Cfy where εwλp εfyλp εmyλp are 100% W, FY and MY emissivities • Posteriori retrievals of sea ice concentration • Minimization of Euclidian distance between a-priori (stored in library) and posteriori (retrieved from MIRS) emissivities

3. Status of the Current SSMI/S Algorithm (con’t) • MIRS EDRs used • Retrieved emissivities at 19, 22, 37 and 92 GHz (V+H) compared with those in the library to find closest match • Retrieved Tskin used as constraint • Results • Statistical inter-comparisons against AMSR-E are under way (Chris Grassotti) – underestimation along edges & closed ice • Underestimation of high sea ice concentration compared to AMSU-MHS – persisted for the entire summer period of 2008 (June – October 2008) • Geophysical noise along coastal pixels due to land influences

4. More pronounced underestimations observed during mid-Summer (Arctic) SSMI/S AMSU-MHS

5. Negative bias persists in early Fall 2008 over new ice (not as large, but extensive) SSM/IS Figure 3. Flow diagram of the AMSU-based, new snow-cover extent algorithm. Condition (1) filters out non-scatterers. Conditions (2), (3) and (4) filter out other scattering surfaces such as rain and deserts. Condition (5) represents a new addition to the current operational scheme, and identifies snow-cover surfaces underlying an above-freezing atmosphere that otherwise could be misclassified as rain. In the diagram, TB180 refers to the brightness temperature at 183±3 GHz water vapor absorption channel (Table1, channel 19), and TB54L refers to limb-corrected TB at 53.6 GHz oxygen absorption channel (Table 1, channel 5). Unlike snow-cover, rain signatures that scatter in the 23-150 GHz range often scatter at frequencies in the water vapor band. Here, TB54L is used only as a reference. Figure 3. Flow diagram of the AMSU-based, new snow-cover extent algorithm. Condition (1) filters out non-scatterers. Conditions (2), (3) and (4) filter out other scattering surfaces such as rain and deserts. Condition (5) represents a new addition to the current operational scheme, and identifies snow-cover surfaces underlying an above-freezing atmosphere that otherwise could be misclassified as rain. In the diagram, TB180 refers to the brightness temperature at 183±3 GHz water vapor absorption channel (Table1, channel 19), and TB54L refers to limb-corrected TB at 53.6 GHz oxygen absorption channel (Table 1, channel 5). Unlike snow-cover, rain signatures that scatter in the 23-150 GHz range often scatter at frequencies in the water vapor band. Here, TB54L is used only as a reference. Figure 3. Flow diagram of the AMSU-based, new snow-cover extent algorithm. Condition (1) filters out non-scatterers. Conditions (2), (3) and (4) filter out other scattering surfaces such as rain and deserts. Condition (5) represents a new addition to the current operational scheme, and identifies snow-cover surfaces underlying an above-freezing atmosphere that otherwise could be misclassified as rain. In the diagram, TB180 refers to the brightness temperature at 183±3 GHz water vapor absorption channel (Table1, channel 19), and TB54L refers to limb-corrected TB at 53.6 GHz oxygen absorption channel (Table 1, channel 5). Unlike snow-cover, rain signatures that scatter in the 23-150 GHz range often scatter at frequencies in the water vapor band. Here, TB54L is used only as a reference.

6. New SSMI/S Retrieval Strategy • Use hybrid technique • Over multi-year ice (predominant in summer), do not use 89 GHz due to increased variability & surface effects • Over multi-year ice, use emissivity and polarization gradients up to 37 GHz as more “stable” radiometric parameters • Over first-year ice, use absolute emissivities in the 19-92 GHz window range as more stable radiometric parameters • Preliminary Results (not final) • Much improved retrievals in Fall 2008 over both closed ice & ice edges • More consistent to AMSU-MHS, superior over peripheral & first-year ice • Geophysical noise along coastlines remains

7. Inter-comparisons between the current SSMI/S, N18 & Metop-A AMSU-MHS and new SSMI/S – very encouraging results New SSMI/S Current SSMI/S Current Metop-A Current AMSU-MHS Current Metop-A

8. New SSMI/S Inter-comparison Examples for October 26, 2008 with the Operational North European Analysis Sea Ice Product Analysis (SSMI + NWP + manual intervention) New SSMI/S (microwave only)

9. Much improved, consistent retrievals over Antartica as well. Appears less noisy than AMSU-MHS New SSMI/S Current SSMI/S Current Metop-A Current NOAA 18

10. Pending SSMI/S Work and expected remedies • Sea Ice • Improve geophysical noise over coastlines • Use geographical and geophysical constrains to reduce it as much as possible • Make refinements to the algorithm for optimal accuracy based on feed-back from on-going evaluation work • SWE • Improve current algorithm • Use strategies applied to AMSU-MHS • Flag tough SWE areas such as Greenland and Antarctica using geographical constrains