Sea ice as a key climate indicator in the Arctic

Transcription

1 Sea ice as a key climate indicator in the Arctic Leif Toudal Pedersen, DMI Natalia Ivanova, NERSC Eero Rinne, FMI Roberto Saldo, DTU Georg Heygster, U-Bremen Rasmus Tonboe, DMI Thomas Lavergne, Met Norway Marko Mäkynen, FMI Stefan Kern, U-Hamburg Anja Roesel, U-Hamburg Vera Djepa, UCAM Henriette Skourup, DTU Kirill Khvorostovsky, NERSC Contributions from Ludovic Brucker, NASA Mohammed Shokr, Environment Canada

2 What are the most pronounced changed observed in Arctic sea ice in the last decades? Sea ice variable Change Observed trend Role of CCI Ice extent Decrease % per decade improve algorithms and determine error bars Multiyear extent Decrease % per decade as above, Phase 2 Ice thickness Decrease - 15 % per decade reduce uncertainty, merge data from different sources Ice drift Increase cm/s per decade develop ECV in Phase 2 Melt season Increase days per decade improve retrieval of melt onset and refreeze Ref. IPCC AR5

3 Arctic sea ice extent summer minimum When can the Arctic expected to be ice- free in the summer? Sept 2007 Sept 2012

4 Ice thickness changes from 1988 to 2004 NAME model + submarine obs NAME model + IceSat obs Oct-Dec 1988 Oct-Dec 2004 Maslowski et al., 2012

5 Transpolar ice drift: Fram drift: 3 years Tara drift: 1. 5 years Ref. Jean-Claude Gascard

6 How do models project sea ice extent in the 21 st century? Results of CMIP5 models (IPCC 2013) Changes are relative to reference period !

7 The Algorithms A total of 25+ algorithms were implemented and tested! Most were algorithms published over the last 30 years! Some were very simple! Some were combinations (such as averages) of others! Algorithm! Channels! N90 Linear Dyn! 90HV! N90! 90HV! P90! 90HV! ASI nowf! 90HV! combo1! (CF+NT)/2 combo2! (CF+NT+N90)/3 combo3! (NRL+N90)/2 combo4! (NRL+N90+CF)/3 combo5! (CF+N90*CF 2 )/(1+CF 2 ) combo6! (CF+N90*CF 3 )/(1+CF 3 ) combo7! (CF+N90)/2 combo8! (CF+N90*CF)/(1+CF) OSISAF! 37HV+19V! SICCI! 37HV+19V! TUD! 90HV+37V+19V Bootstrap P! 37HV P37/NRL! 37HV PR! 37HV+19HV NASA Team! 37V+19HV Bristol! 37HV+19V Bootstrap F! 37V+19V Cal Val! 37V+19V UMass-AES! 37V+19V NORSEX! 37V+19V P18/P10! 19HV/10HV 6H! 6H NASA Team 2! 37V+19HV+90HV! ECICE! 37VH+19VH

8 Algorithm inter-comparison and validation % 85% STD, % Selected algorithm: combination of Bootstrap F and Bristol! SICCI algorithm! 5 0 N90 N90LD ASI P90 combo3 Combo7 combo4 Bootstrap P P37 combo2 ECICE P18 PR Bristol NASA Team2 combo8 NASA Team OSISAF OSISAF2 combo1 P10 combo5 combo6 OSISAF3 NORSEX CalVal UMass-AES TUD Bootstrap F 6H *75% for NASA Team2

9 Atmospheric correction Num No correction RTM correction Improvement of standard deviations 200 for a selection of algorithms after 0 RTM correction SIC, % SIC, % SICCI algorithm before and after RTM correction with ERA INTERIM No correction RTM correction 30 Improvement of standard deviations for a selection of algorithms after RTM correction STD, % Near90 SICCI

10 Agreement between the algorithms Arctic annual sea ice area Trends million km Million km 2 /dec Bristol CalVal NASA Team NORSEX UMass-AES

11 Trends in sea ice concentration Average September trend a b %/dec

12 Arctic and Antarctic dataset with uncertainties SIC, % uncertainty, % SIC, % uncertainty, %

13 Sea ice thickness from radar Goal: create monthly sea ice thickness estimates from three different ESA satellite altimeters: l ERS-1 RA ( ) l ERS-2 RA ( ) ENVISAT RA-2 ( ) altimetry Laxon et al, Nature 2003

14 Ice thickness distribution (probability density function pdf) Thin ice observations (SMOS, IR) Thick ice observations (CryoSat, IceSat)

15 SIT Radar Altimeter Prototype Processor Goal: create monthly sea ice thickness estimates from three different ESA satellite altimeters:ers-1 RA ( ), ERS-2 RA ( ), ENVISAT RA-2 ( ) Preliminary results from March 2008

16 Uncertainty in ice thickness estimation February-March Oct. - Nov Analysis of IceSat thickness retrieval uncertainty due to ice density and snow cover uncertainty (Zygmuntowska et al. 2014)

17 Sensitivity of ice thickness retrieval

18 SMOS thin sea ice thickness

19 Arctic Climate System Warming ice/snow melting Increase run-off Wildcard - Greenland Ice Sheet Deep water formation conveyour belt Strong natural variablity Warm surface waters Cold Arctic waters Cold deep waters River runoff