Why is it difficult to resolve future projections of Arctic-midlatitude linkages?
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Virtual presentation for Colorado State University (Atmospheric Dynamics Seminar)
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Why is it difficult to resolve future projections of Arctic-midlatitude linkages?
- 1. Why is it difficult to resolve future projections of Arctic-midlatitude linkages? Zachary Labe (Currently - postdoc with Libby) Yannick Peings & Gudrun Magnusdottir (PhD work - UC Irvine) 2 December 2020 Colorado State University BMRRTH Group Meeting
- 2. INPUT LAYER HIDDEN LAYERS OUTPUT LAYER Layer-wise Relevance Propagation2-m Temperature “2000-2009”Decade: Labe and Barnes, in prep REVEALING CLIMATE SIGNAL WITH XAI
- 4. 7 Feb. 2010
- 6. Vihma, 2014
- 7. Cohen et al. 2014
- 8. Barnes and Screen, 2015
- 9. Overland et al. 2016
- 10. Francis, 2017
- 11. Francis et al. 2017
- 12. Screen et al. 2018
- 13. CLIVAR Working Group, 2018
- 14. Screen et al. 2018
- 15. Vavrus, 2018
- 16. Coumou et al. 2018
- 17. Smith et al. 2019
- 18. Cohen et al. 2019
- 19. [Newson, 1973; Nature] “…great warming of the lower layers of the troposphere over the Arctic basin... In fact, there is a lowering of mid-latitude continental temperatures near the surface”
- 24. Why? What is the perturbation?
- 25. [ SIT ] Sea Ice Thickness Depth between sea surface and ice/snow layer [ SIC ] Sea Ice Concentration Fraction (%) of seawater covered by ice Snow Ice [ SIE ] Sea Ice Extent Area of seawater covered by any amount of ice (>15%)
- 26. [ SIT ] Sea Ice Thickness Depth between sea surface and ice/snow layer [ SIC ] Sea Ice Concentration Fraction (%) of seawater covered by ice Snow Ice [ SIE ] Sea Ice Extent Area of seawater covered by any amount of ice (>15%)
- 27. [ SIT ] Sea Ice Thickness Depth between sea surface and ice/snow layer [ SIC ] Sea Ice Concentration Fraction (%) of seawater covered by ice Snow Ice [ SIE ] Sea Ice Extent Area of seawater covered by any amount of ice (>15%)
- 28. R/V Lance – Greenland Sea – May 2017
- 29. R/V Lance – Greenland Sea – May 2017 Turbulent heat fluxes [ SIC ]
- 30. R/V Lance – Greenland Sea – May 2017 Turbulent heat fluxes [ SIC + SIT ]
- 31. WACCM4 Whole Atmosphere Community Climate Model version 4 – Specified Chemistry “high top” chemistry-climate atmosphere model Physical parameterizations from CAM4 • 66 vertical levels – extending to 5 x 10-6 hPa (140 km) • 1.9° latitude x 2.5° longitude • QBO prescribed from radiosonde observations • Improved representation of sudden stratospheric warming (SSW) events • fixed radiative forcings from year 2000
- 32. Future Arctic How does sea-ice thickness decline influence the large- scale atmospheric response? Significant thermodynamic response over Arctic Ocean Poleward weakening of jet LABE ET AL. 2018, GRL
- 33. Future Arctic Significant thermodynamic response over Arctic Ocean Poleward weakening of jet LABE ET AL. 2018, GRL How does sea-ice thickness decline influence the large- scale atmospheric response?
- 34. LABE ET AL. 2018, GRL
- 35. Loss of sea-ice thickness reinforces large-scale response LABE ET AL. 2018, GRL + =
- 37. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss (Non)linearity in the polar stratosphere?
- 38. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Composite response by QBO phase (~67 years) Modulation by QBO Sea ice experiments
- 39. Modulation by QBO Sea ice experiments Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss
- 40. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Composite response by QBO phase (~67 years) Modulation by QBO Sea ice experiments Future (2051-2080) Historical (1975-2005)
- 41. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Composite response by QBO phase (~67 years) Modulation by QBO Sea ice experiments Future (2051-2080) Historical (1975-2005)
- 42. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Modulation by QBO Sea ice experiments Composite response by QBO phase (~67 years) Easterly (QBO-E) Westerly (QBO-W)
- 43. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Modulation by QBO Sea ice experiments Composite response by QBO phase (~67 years) Easterly (QBO-E) Westerly (QBO-W)
- 44. Assess the role of the Quasi-biennial Oscillation (QBO) on the atmospheric response to Arctic sea-ice loss Sea ice experiments Composite response by QBO phase (~67 years) Modulation by QBO Surface (thermodynamic) Troposphere/Stratosphere
- 47. PLUMBFLUX LABE ET AL. 2019, GRL
- 48. PLUMBFLUX LABE ET AL. 2019, GRL
- 49. PLUMB FLUX QBO-E at 150 hPa Anomalous WAFz over Siberia LABE ET AL. 2019, GRL
- 50. COLDEXTREMES LABE ET AL. 2019, GRL
- 51. MOTIVATION ARCTIC SEA ICE MID-LATITUDE WEATHER Sea-ice thickness variability is important for reinforcing the atmospheric response Strength of Siberian High closely related to Eurasia cold spells QBO can modulate teleconnections due to Arctic sea-ice loss
- 52. MOTIVATION ARCTIC SEA ICE MID-LATITUDE WEATHER Sea-ice thickness variability is important for reinforcing the atmospheric response Strength of Siberian High closely related to Eurasia cold spells QBO can modulate teleconnections due to Arctic sea-ice loss
- 53. MOTIVATION ARCTIC SEA ICE MID-LATITUDE WEATHER Sea-ice thickness variability is important for reinforcing the atmospheric response Strength of Siberian High closely related to Eurasia cold spells QBO can modulate teleconnections due to Arctic sea-ice loss
- 57. WHAT IS THE EFFECT OF SEA-ICE LOSS RELATIVE TO ARCTIC AMPLIFICATION?
- 58. Polar Amplification Model Intercomparison Project Model: SC-WACCM4 Model: E3SM Setup: Constant SST Setup: Sea ice change Forcing(s): 2°C Forcing(s): Present Forcing(s): Pre-indust. Ensembles: 300 “Response to sea ice” [SMITH ET AL. 2018; GCMD]
- 59. Polar Amplification Model Intercomparison Project Model: SC-WACCM4 Model: E3SM Setup: Constant SST Setup: Sea ice change Forcing(s): 2°C Forcing(s): Present Forcing(s): Pre-indust. Ensembles: 300 “Response to sea ice” [SMITH ET AL. 2018; GCMD]
- 60. Polar Amplification Model Intercomparison Project [SMITH ET AL. 2018; GCMD] Model: SC-WACCM4 Model: E3SM Setup: Constant SST Setup: Sea ice change Forcing(s): 2°C Forcing(s): Present Forcing(s): Pre-indust. Ensembles: 300 “Response to sea ice”
- 61. AA-2030 AA-2060 AA-2090 • 2020-2039 Arctic Amplification Arctic Amplification Experiments RCP8.5 Forcing – LENS Peings et al. 2019, GRL • 2050-2069 Arctic Amplification • 2080-2099 Arctic Amplification
- 62. AA-2030 AA-2060 AA-2090 • 2020-2039 Arctic Amplification Arctic Amplification Experiments • 2050-2069 Arctic Amplification • 2080-2099 Arctic Amplification
- 63. Arctic45°N Arctic45°N Arctic45°N Sea-ice loss Arctic amplification LABE ET AL. 2020, GRL
- 66. Arctic amplification > sea-ice loss LABE ET AL. 2020, GRL
- 67. Arctic amplification > sea-ice loss What about internal variability?
- 72. Atmospheric response sensitive to changes in Arctic sea-ice thickness variability and background state (QBO) Role of sea ice is small relative to Arctic amplification (and internal variability) Zachary Labe zmlabe@rams.colostate.edu @ZLabe
- 73. Atmospheric response sensitive to changes in Arctic sea-ice thickness variability and background state (QBO) Role of sea ice is small relative to Arctic amplification (and internal variability) QUESTIONS… Zachary Labe zmlabe@rams.colostate.edu @ZLabe
- 79. Arctic45°N Arctic45°N Arctic45°N Nudging to ~2030 Arctic Amplification [AGCM]
- 81. Arctic45°N Arctic45°N Arctic45°N Nudging to ~2060 Arctic Amplification [AGCM]
- 83. Arctic45°N Arctic45°N Arctic45°N Nudging to ~2090 Arctic Amplification [AGCM]
- 85. Arctic45°N Arctic45°N Arctic45°N 2°C Warming SIC-forcing [AGCM]
- 87. Arctic45°N Arctic45°N Arctic45°N 2°C Warming SIC-forcing [AOGCM]
- 89. Arctic45°N Arctic45°N Arctic45°N 2°C Warming SIC/SIT-forcing [AGCM]
- 95. EDDY-DRIVENJET
- 97. Dependence of the Siberian High response on polar mid-tropospheric warming Gray bar shows the uncertainty range between NCEP/NCAR R1 and ERA5 for 10-year epochs
- 98. 1. Climate models forced only by sea-ice anomalies do not capture the vertical extent of Arctic warming 2. Increase in 1000-500 hPa layer is linked to a strengthening of the Siberian High and cold anomalies in eastern Asia 3. Role of the stratosphere is unclear due to large internal variability at future global warming levels of 2°C Arctic amplification >> sea-ice loss
- 99. 1. Climate models forced only by sea-ice anomalies do not capture the vertical extent of Arctic warming 2. Increase in 1000-500 hPa layer is linked to a strengthening of the Siberian High and cold anomalies in eastern Asia 3. Role of the stratosphere is unclear due to large internal variability at future global warming levels of 2°C Arctic amplification >> sea-ice loss
- 100. LABEETAL.2020,inprep
- 101. LABEETAL.2020,inprep
- 102. LABEETAL.2020,inprep
- 103. LABEETAL.2020,inprep
- 104. LABEETAL.2020,inprep
- 105. LABEETAL.2020,inprep
- 106. LABEETAL.2020,inprep
- 107. two-sided Student's t test 𝜶 = 0.05 LABEETAL.2020,inprep
- 108. LABEETAL.2020,inprep False Discovery Rate 𝜶 𝑭𝑫𝑹 = 0.05
- 109. EDDY-DRIVEN JET NONE SIGNAL! LABE ET AL. 2020, in prep
- 110. SURFACE AIR TEMPERATURE NONE SIGNAL! LABE ET AL. 2020, in prep
- 112. Surface Troposphere Stratosphere Pre-Industrial December-March Zonal Wind Labe et al. 2018, GRL
- 114. 1. Small signal in dynamical response to sea ice decline relative to internal variability and climatology 2. Strong surface warming and increase in precipitation mostly confined to Arctic Ocean 3. AGCM experiments need even larger ensembles (>200 members) to address the noise Is the circulation response to Arctic sea ice loss actually robust in the context of internal variability?
- 119. NAME SEA ICE FORCING DURATION Historical Average 1976-2005 LENS SIT Average 1976-2005 LENS SIC ONDJFM; 200 members Future Future 2051-2080 LENS SIT Future 2051-2080 LENS SIC ONDJFM; 200 members All experiments have average 1976-2005 LENS SST* Atmospheric General Circulation Model Experiments
- 120. SEAICE
- 121. HEATFLUX
- 123. MECHANISMS