Changes, variability, and seasonality of sea ice energy budgets
24 Sep 2014
Marcel Nicolaus, Stefanie Arndt, Christian Katlein
Sunlight and Transmittance
Snow Rules
• Physical proper.es
• Thermal
• Op.cal
• Surface characteris.cs
• Melt ponds
• Satellite signatures
• Mass balance
• Snow depth
• Snow density / mass
• Fresh water
Changes: The Ice Age Proxy
• Surface proper.es
• Physical proper.es: Dri@ and Dynamics
• Thickness distribu.ons
• Habitat changes
Albedo Changes
• Decrease in surface albedo
• Increase of solar heat input (1-‐2 %/year)
=> Develop maps and trends for in-‐ and under-‐ice fluxes
Perovich et al. (2011, AOG)
Seasonality
6
85%
15%
85%
15%
65%
35%
50%
50%
70%
30%
20%
80%
Nicolaus et al. (2010, JGR and CRST)
• Results from the dri@ of Tara
• At one dri@ing MYI site
• Great .me series, no spa.al variability
Seasonality at Tara
Nicolaus et al. (2010, JGR and CRST) 7
15 Aug 23 June
01 July 11 June
Albedo Transmittance
16 Jul – 12 Aug
Under-Ice Investigations
View from Below: Level Ice
View from Below: Ridged Ice
Transmittance through Sea Ice
Nicolaus et al. (2012 & 2013, GRL)
10 m
20%
0%
• 40% ponds on FYI: 11%
• 23% ponds on MYI: 4%
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
0 5 10 15 20 25 30 35
FYI white
FYI ponds MYI white
MYI ponds
Transmittance
Frequency (%)
1%
14%
4%
20%
Observed Changes in Summer
Nicolaus et al. (2012 & 2013, GRL)
Transmission: + 200%
Albedo: - 50%
Absorption + 50%
August 2011 – Upscaling
Nicolaus et al. (2012 & 2013, GRL)
Concentration Pond Fraction Age Irradiance
August 2011 – Fluxes into the ocean
Nicolaus et al. (2012 & 2013, GRL)
Sea ice only Ice + Ocean
Seasonality of Transmittance
New up-scaling method for calculation of under-ice radiation
01#
Jan# EMO# MO# MO+14d# EFO# FO# FO+60d#Dec#31#
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
Transmittance
FYI
melting FYI new FYI new MYI melting MYI MYI
I" II" III" IV" V" VI" I"
Pond"
covered"
sea"ice"
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
Transmittance
FYI
melting FYI new FYI new MYI melting MYI MYI
I Winter II Early melt
III Continuous melt IV Summer
V Fall freeze-up
VI Continuous freeze
Total transmittance of pond covered sea ice.
Parameterization
Arndt & Nicolaus (2014, TCD)
Seasonality of Transmitted Fluxes
Apr May Jun
Jul Aug Sep
§ Surface flux is same order of magnitude as ocean heat flux
§ 96 % of the annual under-ice radiation are transmitted in only 4 months (May to August)
§ Highest fluxes
(= melt rate) in June
Monthly mean of transmitted heat fluxes through Arctic sea ice in 2011.
§ Add parameterization of transmittance for the entire year 2011
Monthly mean of 20×105 Jm-2
≙ 20 cm sea-ice melt/month
Arndt & Nicolaus (2014, TCD)
Annual Trend (Sea Ice Only)
(a)$ (b)$
Trend in annual total solar heat input through Arctic sea ice from 1979 to 2011.
§ Light transmission
increases by 1.5% per year Arctic-wide since 1979
§ Over 32 years: 1.6 times more warming and melt
§ Apply to all years 1979-2011
Arndt & Nicolaus (2014, TCD)
Recent AUV mission
Photo: Chris.an Katlein
Optical Properties - Scattering
Irradiance
(180°)
Radiance
(7°)
Katlein et al. (2014, JGR)
Irradiance / Radiance
𝝈↓𝑯 >𝝈↓𝑽
Katlein et al. (2014, JGR)
§ Isotropy C=π=3.14
§ Mostly used, but overestimation of irradiance by >50%
§ Anisotropy C<2.5
§ More realistic fluxes
Irradiance / Radiance
Katlein et al. (2014, JGR)
§ Isotropy C=π=3.14
§ Mostly used, but overestimation of irradiance by >50%
§ Anisotropy C<2.5
§ More realistic fluxes 𝑪=𝝅
Parameterization of C=Irrad/Rad
Katlein et al. (2014, JGR)
§ Best fit of anisotropy
§ Error < 5%
§ For isotropic case C=2.5
§ Boundary effect
§ Correct conversion of radiance to irradiance is possible: anisotropy needed
C( γ )=2.5-2 γ
Spectral Radiation Buoy
Wang et al. (2014, JGR)
§ Fully autonomous measurements
Spectral Radiation Buoy
Wang et al. (2014, JGR)
Bio-Physical Observatory (drifting)
• Instrumenta.on
• 1 Thermistor Buoy
• 2 Spectral Radia.on Buoy
• 3-‐5 Data
Transmission
• 6 CTD
• 7 ADCP
• Deployment 2014/15
Figure: H. Flores
Autonomous Stations (Buoys)
Snow Depth Sea-Ice Thickness
Energy budgets
Summary
• Snow rules and we need beber snow data sets
• Seasonality of light transmission
• Highest fluxes in June
• 96% in 4 summer months only (May-‐Aug)
• Trends in light transmission
• Increase of 1.5% / year
• Strongly related to the loss of mul.-‐year sea ice
• Op.cal proper.es of sea ice
• Scabering is anisotropic
• Conversion of radiance to irradiance is possible (use C<2.5)
• Future direc.ons
• Similar studies for Antarc.c sea ice
• Towards AUV measurements
• More connec.on to biological studies (primary produc.on)
• Applica.ons in GCMs
