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Snow and Ice Products Status. C. Grassotti, C. Kongoli, and S.-A. Boukabara. Geophysical Performance Assessment Tools. Daily comparisons versus AMSR-E snow and ice products (ice: NASA Team 2, Bootstrap) Sorted by sensor, region, asc/des Assessment graphics: Maps, scatterplots
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Snow and Ice Products Status C. Grassotti, C. Kongoli, and S.-A. Boukabara
Geophysical Performance Assessment Tools • Daily comparisons versus AMSR-E snow and ice products (ice: NASA Team 2, Bootstrap) • Sorted by sensor, region, asc/des • Assessment graphics: • Maps, scatterplots • Skill scores and statistics time series • Histograms • Available on MIRS web site
Maps: Sea Ice MIRS N19 NASA Team 2 (NT2) Bootstrap (BTP) MIRS-BTP MIRS-NT2 NT2-BTP 2009-04-05
Maps/scatterplots: Sea Ice NASA Team 2 (NT2) MIRS-NT2 MIRS N18 Excluding MIRS SIC=0: r=0.63 stdev=7.3 Bias=-0.09 Including SIC=0: r=0.98 stdev=8.6 Bias=-0.07 2009-03-30
Maps/scatterplots: Snow Water MIRS N19 AMSRE Excl MIRS SWE=0: r=0.32 stdev=5.1 Bias=1.9 MIRS-AMSRE 2009-04-05
Time Series: Sea Ice Global Performance 1 Mar – 12 Apr 2009 CORR BIAS STDEV n19 bias correction change n19 bias correction change HEIDKE FAR POD
Time Series: Sea Ice NH/SH Performance 1 Mar – 12 Apr 2009 N. Hemisphere BTP-NT2 ~ -0.5 BTP-NT2 ~ 5.0 BIAS POD STDEV Improved detection with autumn ice development S. Hemisphere
Time Series: SWE N. Hemisphere 1 Mar – 12 Apr 2009 CORR BIAS STDEV n19 bias correction change HEIDKE FAR POD Snowmelt: Metop detection degrades for descending (2130 UTC)
Time Series: Snow Water Asc/Des 1 Mar – 12 Apr 2009 Descending (ECT: n18=0140, n19=0150,metop=2130,f16=0800) Snowmelt: Metop detection degrades for descending (2130 UTC) BIAS CORR POD Snowmelt: n18/n19 detection degrades for ascending (1340 UTC) Ascending (ECT: n18=1340, n19=1350,metop=0930,f16=2000)
Histograms: Sea Ice NH 1 Apr 2009 F16 N19 NH 2009-04-01 SH
Histograms: Snow Water N19 N18 2009-03-01 2009-04-01
Summary Daily assessment of snow and ice products, using AMSR-E as reference: maps, time series of scores/stats, histograms Results stratified by region, asc/des, sensor Assessment graphics complementary; provide more complete view of performance (e.g. correlations vs. histograms; skill scores for params w/non-gaussian dist) Allow better evaluation of impacts due to algorithm updates, calibration and bias correction changes.