BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:High-resolution Remote Sensing Summer Arctic Sea Ice Observations 
 for Improved Prediction - Ellen Buckley (Brown University)
DTSTART:20220921T090000Z
DTEND:20220921T093000Z
UID:TALK178301@talks.cam.ac.uk
DESCRIPTION:\nObservations of Arctic sea ice reveal a negative and acceler
 ating trend of end-of-summer extent\, outpacing model projections\, which 
 suggests some sea ice processes are not well represented in models. In sum
 mer\, snow atop the sea ice melts into ponds\, decreasing surface albedo a
 nd contributing to the ice albedo feedback.&nbsp\; Sea ice model predictio
 ns are sensitive to melt pond inclusion\, and inclusion of ponds in models
  reduces the surface albedo and enhances the ice-albedo feedback. Incorpor
 ating melt pond formation and evolution processes in models has a signific
 ant effect on the predicted sea ice thickness and extent.\nFor these reaso
 ns\, it is important to understand the melt pond evolution throughout the 
 summer. Remote sensing observations of melt ponds are limited due to atmos
 pheric conditions. In the summer\, there is abundant moisture provided by 
 extensive areas of ice-free water\, resulting in the formation of low lyin
 g clouds. The presence of clouds can obstruct remote sensing measurements 
 of the surface. Furthermore\, melt ponds on sea ice appear radiometrically
  similar to open water and leads\, making disambiguation of these surfaces
  in remotely sensed observations difficult. Thus\, our understanding of me
 lt pond processes is lacking at an Arctic-wide level. Scientists rely on p
 redictive models to supplement the limited summer observations.&nbsp\;\nHe
 re\, we present new observational data from the ICESat-2 satellite that ma
 y be of interest to the modeling community. ICESat-2\, launched by NASA in
  2018\, has demonstrated the ability to precisely (~2 cm) measure sea ice 
 height with along-track sampling of 0.7m. We develop and apply sea ice sur
 face recovery algorithms to track ponds in ICESat-2 photon cloud data and 
 derive their depth. These findings\, in conjunction with observations of m
 elt pond area and size distribution from Sentinel-2 imagery\, provide a th
 ree-dimensional view of the evolution of summer melt. With widespread data
  coverage\, we are able to gain insight on the regional patterns and tempo
 ral evolution of melt on summer sea ice. Our findings may be used to impro
 ve parameterization of melt processes in models\, quantify freshwater stor
 age\, and study the partitioning of under ice light.\n\n&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR