Utilization of Observations at the Russian Drifting Stations “North Pole” for Improved Description of Air–Sea-Ice-Ocean Interactions

in the Arctic Ocean

A. Makshtas, Sokolov V., S. Shutilin, V. Kustov, N. Zinoviev,

Arctic and Antarctic Research Institute, Saint Petersburg, Russia,

Presented byOla Persson

CIRES/NOAA/ESRLBoulder, Colorado USA

Russian drifting stations “North Pole” in 2003-2012

Barents Sea

Greenland

Spitsbergen

Wrangell Is.

Chukchi Sea

Canada Basin

Tiksi

Barrow

Pevek

Science Issues Being Studied with “North Pole” station data

AtmosphericCryospheric

OceanicGreenhouse Gas

Lidar

Radiation

MAWS-420

Unmanned plane

Radiosound

aerostat

Inlets of ozone,carbon dioxide, methane and radioactivity analyzers

Precipitation gauge

Weather shed

Carbon dioxide flux measurements

GPS and GLONAS systems for ice drift calculations

Polygon 80x100 m for mass balance and dynamic studies

Ice thickness measurements

Snow height

Total ozone

Spectrometer “Ramses”IMB buoy Transmitter IMB

Thermo chain IMB

Ice thickness submersible vehicleLong ranger ADCP

WH LP 757ADCP WHS 300

Echo-sounder

Echo-sounder emitter

2 SBE 37SM MicroCat 3 SBE 19 profilers Current meter RCM Grid Juday

Overview of observations, organized at drifting station “North Pole – 39” and future “North Pole” stations

Atmospheric Science Issues

1) characterizing low-level inversions

2) cloud characteristics (cloud fraction, height; measurement technique variability)

3) atmospheric boundary layer thermal structure – variability processes

4) atmospheric O3

- surface-layer/boundary layer- stratosphere – Arctic “ozone holes”

5) measurement techniques (e.g., clouds, skin temperature)

6) validation of models: mesoscale (WRF), RCMs and reanalyses - T, Td, cloud fraction, BL thermal & kinematic structure- surface characteristics

7) parameterization validations- downwelling SW and LW radiation, incl. impact of clouds- turbulent fluxes in stable boundary layer- atmospheric boundary layer, for forcing sea-ice models

W ithout c louds.

-32 -30 -28 -26 -24 -22 -20 -18 -16

T , 0C

0

500

1000

1500

2000

2500

3000

z, m

M e as ure m e nts Hirham Ecmwf

W ith clouds.

-32 -30 -28 -26 -24 -22 -20 -18 -16

T , 0C

0

500

1000

1500

2000

2500

3000

z, m

M e as ure m e nts Hirham Ecmwf

Monthly mean profiles (April 2008; NP-36) of air temperature from radiosoundings and calculated by HIRHAM4 (AWI Regional Climate Model) and ECMWF (ERA-Interim Reanalysis?)

Clear skies

Cloudy Skies

He

igh

t (m

)

He

igh

t (m

)

T (deg C)

T (deg C)

radiosondes

HIRHAM

ECMWF

radiosondes

ECMWF

HIRHAM

Clear SkiesObservations: surface-based inversionModels: shallow mixed layers, too warm Ts

Cloudy SkiesObservations: surface mixed layerModels: surface mixed layers, too warm ML,

inversions too weak & too deep

Detailed atmospheric boundary-layer processes: New approach with microwave 56.7 GHz temperature profiler at “North Pole 39”

(April 2012)

Hei

ght

(m)

Hour surface-based inversionmixed layer to 300 m

Descent of inversion top

Case 1Case 5

Case 9Case 13

Case 17Case 21

Case 25Case 29

Case 33Case 37

Case 41Case 45

Case 49Case 53

Case 57

Day of observations

0

10

20

30

40

50

60

70

Conce

ntr

atio

n o

f ozo

ne,

mkg

/ì3

Ozone sound Ozonometer

Ozone studies at “North Pole” drifting stations (March 2011, NP-38)

Evidence of “Ozone hole” in the Central Arctic (March 2011)Ozone concentration in atmospheric surface layer in spring

Total cloudiness (in tenths), from ceilometer data and visual observations (Nov. 2008, NP-36)

visualNOAAceilometer

Season T mean NP Т mean NCEP Correlation NCEP-NP

NP-35 (2007-2008)

Winter -29.4 -30.9 0.84 -1.5

Spring -15.3 -13.2 0.97 2.1

Summer -1.2 0.5 0.60 1.7

Autumn -15.3 -18.1 0.89 -2.8

NP-36 (2008)

Autumn -17.7 -19.6 0.89 -1.9

Season N mean NP N mean NCEP Correlation NCEP-NP

NP-35 (2007-2008)

Winter 4.2 4.0 0.48 -0.2

Spring 7.5 2.7 0.15 -4.8

Summer 9.4 4.2 0.30 -5.2

Autumn 7.9 5.0 0.34 -2.9

NP-36 (2008)

Autumn 4.6 5.1 0.24 0.5

Comparison air surface temperature (T) and total cloudiness (N) between NP and NCEP/NCAR Reanalysis data for 2007-2008

Cryospheric Science Issues

1)spatial and temporal variability of spectral albedo of snow/ice – transects of snow depth, density, morphology, spectral albedo (e.g., every 2nd day)

2)spatial and temporal variability of sea-ice surface characteristics (e.g., leads, meltponds, etc)

3)spatial and temporal variability of ice thickness

4)sub-surface ice structure

5)validation of modeled snow depth and ice thickness distributions

100 110 120 130 140 150 160 170 180 190 200 210

Julian Day (NP-36)

400

600

800

Wa

ve le

ng

th, n

m

0.4

0.5

0.6

0.7

0.8

0.9

120 130 140 150 160 170 180 190

Julian Day (NP-35)

400

600

800

Wa

ve le

ng

th, n

m

Transect average spectral albedo for day 98 to 215 (NP-36)and day 115 – 191 (NP 35)

Ice floe characteristics near drifting station “North Pole 38” in winter

October

DecemberApril

UAS – the new instrument for study of sea ice cover

Weight – 3.5 kg, wingspan – 1.4 m, range of flight speed 60 - 100 km/h, altitudes - 50 - 3000 m.

June 19 June 29

July 16 August 30

Ice floe characterization of summer melt - “North Pole 38”

Manual ice thickness measurements (NP-36)

-40 -20 0 20 40

р ас сто я н и е , м

0

20

40

60

80

100

-40 -20 0 20 40

р ассто я н и е , м

0

20

40

60

80

100

расс

тоян

ие, м

л ед о м ер н ая съ ем к а 3 0 .0 9 .2 0 0 8 г . л ед о м ер н ая съ ем к а 2 7 .0 5 .2 0 0 9 г .

0,00

0,50

1,00

1,50

2,00

2,50

3,00

05.09.0

8

30.09.0

8

13.10.0

8

22.10.0

8

02.11.

08

12.11.

08

25.11.

08

05.12.0

8

16.12.0

8

23.12.0

8

31.12.0

8

09.01.0

9

19.01.0

9

28.01.0

9

09.02.0

9

25.02.0

9

10.03.0

9

17.03.0

9

25.03.0

9

07.04.0

9

12.04.0

9

29.04.0

9

12.05.0

9

27.05.0

9

10.06.0

9

21.06.0

9

30.06.0

9

08.07.0

9

19.07.0

9

30.07.0

9

08.08.0

9

17.08.0

9

дата

толщ

ин

а ль

да, с

м

средняя толщина льда минимальная толщина льда максимальная толщина льда

Distance (m) Distance (m)

Dis

tan

ce (

m)

80 x 100 m grid of 35 pointsSeptember 30, 2008 May 27, 2009

max ~ 131 cm

min ~ 78 cm

min ~ 195 cm

max ~ 236 cm

Ice

th

ickn

ess

(m

)

Mean thickness Minimum thickness Maximum thicknessDate

- mean growth of 1.3 m - thickness range decreased during winter from 63 cm to 41 cm (thinner ice regions grew faster)

Comparison of measured and modeled snow and ice thickness evolutions- AARI dynamic-thermodynamic sea-ice model (Makshtas et al., 2003; JGR) with observational

external forcing

NP-35

NP-36

SnowIce

Sn

ow

de

pth

(m

)S

no

w d

ep

th (

m)

Ice

th

ickn

ess

(m

)Ic

e t

hic

kne

ss (

m)

model

model

model

model

measurements

measurements

measurements

measurements

Year Day Year Day

Year Day Year Day

Oceanic Science Issues

1)Temporal variability of solar radiation penetration of sea ice

2)Spectral and depth redistribution of solar radiation

-20

-10

0

Ap

ril

0.1

-40

-20

0

De

pth

, m

Ma

y

0.1

0.1

0.5

400 500 600 700 800 900

Wave length, nm

-40

-20

0

Jun

e

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

400 500 600 700 800 900

Wave length, nm

-40

-20

0

Depth

, m

0

2

4

6

8

Solar energy penetration of sea-ice and redistribution in upper ocean as function of wavelength and month

mW/(m2 nm)

mW/(m2 nm)

April

May

June

July

Dep

th (

m)

Dep

th (

m)

Wavelength (nm)

.02-.09 W m-2

2.2 - 7.2 W m-2

Greenhouse Gas Science Issues

1) Understanding greenhouse gas concentrations and fluxes – CO2

9 10 11 12 1 2 3 4 5 6 7

Months 2007 - 2008 and 2008 - 2009

350

360

370

380

390

400

410

420

430

Con

cent

ratio

n C

O2, p

pm

NP35 NP36 Barrow Alert

9 10 11 12 1 2 3 4 5 6 7

Months 2007 - 2008 and 2008 - 2009

0,00

0,01

0,02

0,03

0,04

0,05

0,06

0,07

0,08

0,09

Sea

sona

l rel

ativ

e va

riabi

lity

CO

2 (m

sd/m

ean)

NP35 NP36 Barrow Alert

Comparison of seasonal variability of CO2 concentration at drifting stations NP-35, NP-36 and Observatories in Barrow and Alert

Direct measurements of CO2 flux with automatic chamber

Monthly relative CO2 variability ()

Monthly mean CO2 concentration

Question: what is the net role of sea ice in modulating or otherwise affecting this CO2 exchange?

(Makshtas et al 2011; AMS Conf. on Polar Meteor. & Ocean.)

a) during summer and early autumn, ice-free Arctic shelf seas serve as a sink for atmospheric CO2. b) in late autumn and winter, cooling seawater is CO2 source to atmosphere.

Scope of Future Work at Russian North Pole Stations

1. Study of polar cloudiness

2. Detailed investigations of atmospheric surface and boundary layers- studies of stable boundary layers- improve/validate parameterizations of BL for forcing sea-ice models- improve/validate mesoscale models, esp. surface characteristics

3. Investigate spatial characteristics and radiative properties of sea ice cover

4. Comprehensive study of atmospheric ozone (from surface to stratosphere)

5. Study of greenhouse gas concentrations and ice/ocean fluxes