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

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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 by Ola Persson CIRES/NOAA/ESRL Boulder, Colorado USA

Russian drifting stations “North Pole” in Barents Sea Greenland Spitsbergen Wrangell Is. Chukchi Sea Canada Basin Tiksi Barrow Pevek

Science Issues Being Studied with “North Pole” station data Atmospheric Cryospheric Oceanic Greenhouse 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 vehicle Long ranger ADCP WH LP 757 ADCP WHS 300 Echo-sounder Echo-sounder emitter 2 SBE 37SM MicroCat3 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 O 3 - 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, T d, 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

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 Height (m) T (deg C) radiosondes HIRHAM ECMWF radiosondes ECMWF HIRHAM Clear Skies Observations: surface-based inversion Models: shallow mixed layers, too warm T s Cloudy Skies Observations: surface mixed layer Models: 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) Height (m) Hour surface-based inversionmixed layer to 300 m Descent of inversion top

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) visual NOAA ceilometer

SeasonT mean NPТ mean NCEPCorrelationNCEP-NP NP-35 ( ) Winter Spring Summer Autumn NP-36 (2008) Autumn SeasonN mean NPN mean NCEPCorrelationNCEP-NP NP-35 ( ) Winter Spring Summer Autumn NP-36 (2008) Autumn Comparison air surface temperature (T) and total cloudiness (N) between NP and NCEP/NCAR Reanalysis data for

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 2 nd 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

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 December April UAS – the new instrument for study of sea ice cover Weight – 3.5 kg, wingspan – 1.4 m, range of flight speed km/h, altitudes m.

June 19 June 29 July 16 August 30 Ice floe characterization of summer melt - “North Pole 38”

Manual ice thickness measurements (NP-36) Distance (m) 80 x 100 m grid of 35 points September 30, 2008 May 27, 2009 max ~ 131 cm min ~ 78 cm min ~ 195 cm max ~ 236 cm Ice thickness (m) Mean thickness Minimum thickness Maximum thickness Date - 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 Snow Ice Snow depth (m) Ice thickness (m) model measurements Year Day

Oceanic Science Issues 1)Temporal variability of solar radiation penetration of sea ice 2)Spectral and depth redistribution of solar radiation

Solar energy penetration of sea-ice and redistribution in upper ocean as function of wavelength and month mW/(m 2 nm) April May June July Depth (m) Wavelength (nm) W m W m -2

Greenhouse Gas Science Issues 1) Understanding greenhouse gas concentrations and fluxes – CO 2

Comparison of seasonal variability of CO 2 concentration at drifting stations NP-35, NP-36 and Observatories in Barrow and Alert Direct measurements of CO 2 flux with automatic chamber Monthly relative CO 2 variability (  ) Monthly mean CO 2 concentration Question: what is the net role of sea ice in modulating or otherwise affecting this CO 2 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 CO 2. b) in late autumn and winter, cooling seawater is CO 2 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