1. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 The Influences of Changes in Sea Ice and Cloud Cover on Arctic Surface Temperature Trends Presented by Jeff Key Presented by Jeff Key

2. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 2 Requirement, Science, and Benefit Requirement/Objective Research area: Document and understand changes in climate forcings and feedbacks, thereby reducing uncertainty in climate projections Priority research activity: Monitor changes in the Arctic and impacts on ecosystems Science How are trends in one climate variable influenced by trends in other variables? Specifically, how do changes in Arctic sea ice extent and cloud cover influence changes in surface temperature? Benefits This work most directly benefits the science community: new information on climate interactions and feedback processes. quantifying the importance of changes in various parts of the climate system

3. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Challenges and Path Forward Science challenges –What other parts of the climate system contribute to changes in surface temperature; i.e., what is causing the residual trends? Next steps –Expand the analysis to other climate variables, e.g., snow cover. Transition Path –As part of the NOAA Scientific Data Stewardship program, the APP-x product should be archived at NCDC. The end users are the climate assessment community and modelers (for verification). The work was recently published. 3

4. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Data Daily surface temperature and cloud cover from the extended AVHRR Polar Pathfinder (APP-x) product. Daily sea ice concentration (SIC), 1982 to 2004, from SSM/I. Method A linear model is developed and applied to study the effect of changes in sea ice concentration (SIC) and cloud cover on surface temperature trends. The change in surface temperature is partitioned into three components: 1.the surface temperature trend caused by cloud cover changes, 2.the surface temperature trend caused by sea ice concentration changes, 3.the surface temperature trend not explained by #1 or #2, i.e., the residual. 4 Data and Method

5. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 5 Trends in Clouds, Sea Ice, and Surface Temperature, 1982-2004 Seasonal cloud amount trend (%/decade) Seasonal SIC trend (%/decade) All-sky surface temperature trend (K/decade) The satellite data analysis has revealed that The Arctic surface temperature has been increasing in spring and summer, but decreasing in winter (central Arctic Ocean). Cloud cover has been increasing in spring but decreasing in winter. Sea ice concentration has been decreasing.

6. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 6 Influence of Cloud Cover and Sea Ice Trend caused by cloud cover (K/decade) In winter, cloud cover trends explain −0.91 out of −1.2 K decade −1 of the surface temperature cooling. In spring, 0.55 K decade −1 of the total 1.0 K decade −1 warming can be attributed to cloud cover changes. Sea ice loss accounts for most of the observed surface warming in the western Arctic Ocean, over 0.9 K decade −1 out of an observed 1.1 K decade −1 temperature trend. Trend caused by sea ice (K/decade)

7. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 7 Residual: Other Influences Changes in cloud and sea ice cover explain most of the temperature trend. The residual trend may allow for a more robust diagnosis of causes for surface warming or cooling in the Arctic by eliminating the effects of SIC and cloud amount changes. Residual trend (K/decade) Potentially significant processes in the residual trend are changes in the heat convergence due to shifting atmospheric circulation, changes in Atlantic and Pacific Ocean inflow, changes in atmospheric composition other than cloud amount.

8. Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Challenges and Path Forward Science challenges –What other parts of the climate system contribute to changes in surface temperature; i.e., what is causing the residual trends? Next steps –Expand the analysis to other climate variables, e.g., snow cover. Transition Path –As part of the NOAA Scientific Data Stewardship program, the APP-x product should be archived at NCDC. The end users are the climate assessment community and modelers (for verification). The work was recently published. 8