Das MOSAiC Driftexperiment DWD Offenbach 18.09.2019

Markus Rex, Klaus Dethloff, Matthew Shupe, Anja Sommerfeld, Uwe Nixdorf, Vladimir Sokolov, Alexander Makarov & the MOSAiC Team Multidisciplinary drifting Observatory for the Study of Climate International Arctic research expedition

• First time a research close to the north pole for a full year, including winter season • 5 (Polarstern, Fedorov, Makarov, Oden, Xue Long) • Polar 5 + other research aircraft  support by helicopters  support by aircraft Antonov 74 • More than 60 institutions • 16 nations & 600 people will work in the central Arctic • 120 Mio € budget ; 1 Day per www.mosaic-expedition.org person 3000 € Annual list of 10 most important developments in science expected in each year:

2019 MOSAiC on first place One in a lifetime chance Golden opportunity Outline

MOSAiC Motivation Earlier attempts Logistics Coupled system Atmosphere -Sea Biogeochemistry and Ecosystem Geographic Latitude Reference period:1951 Near - SurfaceWinter (DJF) Temperature Arctic AmplificationArctic - 1980, data1980, provided by NASA Amplification Arctic Updatedfrom Wendischetal - Anomaly Anomaly Year Δ T s Arctic Equator Antarctica (K) ., ., 2017, E : OS 2 Kwarmer Winter warming is most severe in the Atlantic sector of the Arctic

5 Temperature change 4 in o C per decade 3 2m air temperature based 2 on data from the ECMWF 1 1996-2017 (ERA-interim)

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-2 AWIPEV research station -3

Maturilli et al., 2017 Arctic Retreat from satellite data

40 % Loss

https://seaice.uni-bremen.de Interplay of local, regional & global scales for Arctic Amplification

How are individual Arctic feedbacks . Atmospheric vertical stability . Surface heat fluxes . Low response . Horizontal heat transports . Ocean heat uptake processes . Planetary waves & tropo-stratospheric coupling quantitatively linked to hemispheric changes in  Teleconnection patterns  Weather regimes & extremes  Storm paths? Science: The pathways for Arctic-mid-latitude linkages

Late autumn (ON) Early winter (DJ) Late winter (FM)

How does an improved representation of Arctic climate processes in global climate and NWP models impact simulated Arctic-mid-latitude linkages? Dethloff et al., NYAS, 2019 Outline

MOSAiC Motivation Earlier attempts Logistics Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem Earlier attempts

Previous experiences within the Arctic ice

 Russian NP drifting stations since 1937 Russian drifting station  SHEBA 1987-88  DAMOCLES, TARA, ACSYS, PANARCMiP, PASCAL 2017,  N-ICE with Lance 2015  Shorter-term campaigns NP35  Many disciplinary obs.  Some inter-disciplinary obs. Each of these has key limitations: . Length of time . Comprehensiveness . Spatial resolution . Not in the “new” Arctic SHEBA Drift-Station NP 35  Sept. 2007- April 2008 as part of the International Polar Year 2007-2008 Record minimum (Sep. 2007) NP 35 Route Arctic sea ice cover Jürgen Graeser on russian drift station NP 35, (September 2007- April 2008)

Measurements are needed for improved model description and reduction of model biases:

1. Energy balance at the surface 2. Structure of Arctic PBL 3. Temperature and humidity inversions 4. Aerosols and 5. Sea ice  Integrator for atmos. und ocean. changes 6. Stratospheric ozone Need for Improved Models Weather, Climate, Sea-ice, Biogeochemistry & Ecosystems Require physical representation of the changing new Arctic

 Lack of data in the Arctic atmosphere over the ocean  Major deficiencies in Arctic process understanding  Clouds, boundary layer turbulence, winds, surface fluxes …  Need to focus on “processes, feedbacks and coupling”

SHEBA 1997-1998 in the old Arctic: Surface Heat Budget of the SHEBA trajectory  Beaufort Sea Validation and improvement of RCMs: NP 35 Sept. 2007-July 2008 IPY ARCMIP Arctic Regional Intercomparison RCM biases 10-25 W/m2 against SHEBA radiative fluxes especially under clouds. Implications for sea-ice concentrations. Bias of 10 W/m2 equivalent to energy of melting about 1 m of ice. Outline

MOSAiC Motivation Earlier attempts Logistics Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem MOSAiC Drift: Start September 20 from Tromsö Polarstern and Akademik Fedorov, Ice floe search

Drift September 2019 September 2020 Fuel depots for emergency operations

Drift September 2019 September 2020

Fuel depots (200 tons) for emergency helicopter Helicopter base operations on Severnaya Longyearbyen Zemlya (August 2019) AK Treshnikov Expedition timeline

Start: 20 September 2019 Tromsoe End: 14 October2020

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Until mid Oct Mid December Mid February Mid April Mid June – mid July Mid August Akademik Kapitan Dranitzyn Kapitan Dranitzyn Antonov AN-74 2 x Oden Xuelong or Fedorov Ice runway Xuelong II 3x AN-74 MOSAiC International expedition and example for cooperation in the Arctic Timeline first phase all dates will change based on ice conditions

• 20 Sep 20:00 CET: Polarstern departs Tromso 21:00 CET: Akademik Fedorov departs Tromso Ships travel together ~14kn (in open water) • 1 Oct: At target area ~120-130 E, ~85 N. Start searching floe • 6 Oct: At floe, transfer of equipment and personel between Polarstern and Fedorov • 7-12 Oct: Fedorov sets up Distributed Network of buoys, • Polarstern starts to set up central observatory • 13-15 Oct: Transfer of fuel Fedorov-Polarstern • 16-30 Oct: Fedorov goes back to Tromso • latest 20 Oct: Start of standard observations at central obs. Sea ice conditions & Distributed buoys network

• Perfect floe 9. September 2019 • 2nd year floe in AARI identified 5 ice floes of ca 5 km diameter marginal ice zone • Match with drift PS Polarstern forecasts S Super Buoys of Distributed Network • Origin from Laptev Sea • Selection process • On Polarstern: Science board Sea ice observatory with runway

Met, Ocean, ECO, BGC, ICE sites - close to RV Polarstern, depends on and ice conditions

Runway specification: • UTAir (length-width-thick): 1400 m / 35 m / 1 m (reduced payload) • KBAL (length-width-thick): 1200 m / 28 m / 1 m • Distance from ship at least 1 – 2 km

© Marcel Nicolaus, AWI Daily schedule

Weather forecast by DWD

Peter Gege PASCAL June 2017 Weather forecast by DWD Product examples

Flight weather report Maritime weather report

German Meteorological Service – Marine Met Office MOSAiC Workshop, Potsdam 2019 Outline

MOSAiC Motivation Earlier attempts Logistics Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem Examples of Processes and Feedback Mechanisms

Near-Surface Meridional Transports Global Air-Temperature (Atmosphere/Ocean/Sea Ice) Warming Increases

Terrestrial Radiation Atmos. Energy Increases Fluxes Increase

Lapse Rate Changes, Oceanic Mixed More Water Vapour Layer Warms and Clouds

Sea Ice and Trace Gases and Surface Decreases, Snow Melt Aerosols Change Solar Absorption Increases

Change in Oceanic Biogeochemistry and Energy Exchange with Ocean Interior Fill the gap between observations and models

Observations of the 5 climate relevant subsystems ModellingModelling Improving the understanding of coupled atmosphere-ice-ocean-bio- geochemistry-ecosystem processes in the Central Arctic Improve sea ice forecasting, regional and climate projections in Remote Sensing, Aircraft Operations the coupled system Modelling is cross-cutting and very difficult Nested multiscale observations

Central Observatory • Ship based • Sea ice stations  Process scale observations LES Ground-based < 5 km

Distributed Network • Sea ice stations visited by helicopter • UAV, gliders • Process & regional model  Model grid cell < 50 km RCM Airborne

Large-scale linkages • Collaborating research vessels (Kapitan Dranitzyn, Xue Long, Oden) • Aircraft (Polar 5,6) • Arctic buoys, satellites • Data assimilation studies GCM /CCM Satellite  Arctic regional & global models > 1000 km Modelling hierarchy and data assimilation for upscaling

• Operational weather forecasts: DWD, ECMWF

• Operational sea ice forecasts: AARI Radiosondes over land and ships • Large-eddy simulations • Single column models • Regional models Atmosphere Ocean-Sea Ice Coupled A-O-I • Data assimilation in regional BGC models • Data assimilation in global models • Improving sub-grid scale parameterizations • Intensive Observing Period February-March 2020 for YOPP ICON strategy for upscaling Improved sub-gridscale parameterisations and data assimilation

Large-and meso-scale forcing as function of model complexity

GCM RCM LES

Process understanding, sub-grid scale parameterisation development for different synoptical conditions

llustration of the ICON model family used within (AC)3 representing the model strategy and the coverage from global to local scales. Global modelling includes ICON: Icosahedral non–hydrostatic atmospheric general circulation model, ICON–HAM: Coupled climate–aerosol model, ICON–SWIFT: Coupled climate–ozone model, and ICON–O: Icosahedral global ocean model. Regional modelling applies ICON as a nested Limited Area Model (LAM), while on the process level simulations with the ICON-LEM (Large-Eddy Model) will be performed. These ICON family members will be for the irst time extensively tested and utilised in the Arctic region. ARCROSE: Arctic Research Collaboration for Radiosonde Observing System Experiment Ongoing Japan-Germany Arctic Predictability study Extra Arctic radiosonde observations with RV Mirai and Polarstern Improvements of weather and sea-ice forecasts over Northern Sea Route  high waves, strong winds, icing due Arctic cyclones Better understanding of Arctic-mid latitudes linkage  extreme events over Eurasia (e.g. severe winter)

Extra Data Data sparse area Observations assimilation

Better predictions YOPP Pilot Studies for MOSAiC & YOPP  Inoue • Great cyclone case in August 2012 (RV Polarstern) • Case study September 2013 (RV Mirai, Ny-Ålesund, Alert & Eureka) • Current September 2014 (RVs Polarstern, Mirai, Oden; Ny-Ålesund, Alert & Eureka)

JAMSTEC ALERA2 Global Extra Observations Observing system experiments observations (radiosondes)

Control Atmospheric Sea-ice Reanalysis forecast forecast

Reanalysis Atmospheric Sea-ice w/o extra obs forecast forecast

Data assimilation Predictability of Predictability of extreme events sea ice over NSR Outline

Logistical preparations Earlier attempts MOSAiC motivation Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem Focus areas MOSAiC Ozone Layer Stratosphere

Troposphere Mixed Phase Clouds & Water Vapour Dynamical coupling Radiation Aerosol interaction with clouds Atmospheric Chemistry Energy & momentum fluxes & tracers vertical & meridional Arctic Boundary layer Biogeochemical fluxes Sea ice Ocean mixed layer Ecosystem Cold halocline salinity gradient Vertical mixing Atlantic Ocean water inflow and currents Focus areas Atmosphere

Ozone Layer Stratosphere

Troposphere Mixed Phase Clouds & Water Vapour Dynamical coupling Radiation Aerosol interaction with clouds Atmospheric Chemistry Energy & momentum fluxes & tracers vertical & meridional Arctic Boundary layer Biogeochemical fluxes Sea ice Ocean mixed layer Ecosystem Cold halocline  salinity gradient Vertical mixing Atlantic Ocean water inflow and currents Science Goals Atmosphere

• Surface Energy Budget • Turbulence (momentum-, moisture- and heat transfer) • Arctic Boundary Layer structure & cyclones • Airmass transformation (humidity, chemical composition) • Mixed phase cloud processes & aerosols • Aerosol sources & cloud activity (link to BGC) • Water vapour and precipitation (link to snow) • Cyclone-ice-ocean feedbacks • Vertical fluxes through boundaries between atmosphere, ocean, ice • Meridional energy fluxes in atmosphere and ocean • Impact of sea ice loss on atmospheric circulation and tropo- stratospheric planetary wave propagation

Graham et al., Sci. Rep. 2019 Arctic sea ice anomalies “Low-High” Seasonal sea ice concentration (%) maps – Difference betw. Low and High ice conditions AFES Atmos GCM SON DJF Isolated sea ice impact

NICE-CNTL Differences CNTL: High ice conditions as observed from 1979-1983 NICE: Low ice conditions as observed from 2005-2009

ERA-Interim LOW-HIGH

HIGH ice (1979/80-1999/00) Low ice (2000/01-2013/14)

• Very similar distribution of concentration anomalies Arctic climatology change Polar cap mean 65°N-85°N Low ice minus High ice conditions 2 m air temperature anomalies (K) for negative AO pattern in February Zonal wind Temperature AFES AFES

DEC FEB DEC FEB ERA-Interim ERA-Interim

• Very good agreement between model and reanalysis in winter • ERA-Interim shows global warming; AFES surface warming due to sea ice • Significance on 95 % level (black dashed lines) and 99 % level (solid lines) • Sea ice loss triggers a negative AO phase in late winter, Jaiser et al. JGR 2016 Structure DFG Transregio TR 172, AC3 Arctic Amplification, Wendisch et al. 2019

A: Fluxes in the Arctic Boundary Layer

A01: Surface radiation fluxes A02: Local energy budget profiles A03: Areal energy flux profiles D: Atmospheric B: Clouds, Aerosols & Circulation & Transport E: Integration & Water Vapour Synthesis D01: Atmospheric large-scale B01: Changes of TOA reflectance & clouds dynamics E01: Lapse rate feedback D02: Aerosol-cloud interactions B02: Aerosol & surface spectral E02: Ny-Ålesund column reflectance D03: Atmosphere-ice-ocean E03: Mixed-phase cloud interactions B03: Mixed-phase cloud processess observations D04: Ocean heat transport & E04: Precipitation & snowfall regional processes B04: Aerosols & cloud formation B05: Water vapour trends B07: Sea ice leads & clouds UNI Leipzig, C: Ocean, Atmosphere & UNI Bremen, Sea Ice Interaction UNI Köln, C01: Surface heterogeniety & flux observations AWI Bremerhaven, C03: Atmospheric composition & ocean colour feedback AWI Potsdam, C04: Ocean-sea ice processes TROPOS Leipzig Outline

Logistical preparations Earlier attempts MOSAiC motivation Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem Focus areas Ice Ozone Layer Stratosphere

Troposphere Mixed Phase Clouds & Water Vapour Dynamical coupling Radiation Aerosol interaction with clouds Atmospheric Chemistry Energy & momentum fluxes & tracers vertical & meridional Arctic Boundary layer Biogeochemical fluxes Sea ice Ocean mixed layer Ecosystem Cold halocline salinity gradient Vertical mixing Atlantic Ocean water inflow and currents Focus on different processes during the year

Freeze-up & Sea ice dynamics Sea ice optics & Ice Growth Snow properties Melt processes

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep • Formation of young ice • Ice Drift pattern • Deformation processes • Melting from above and below • Snow on ice and chemistry • Melt ponds and polynyas • Vertical fluxes through the ice • Coupling to ecosystem Focus areas Ocean Ozone Layer Stratosphere

Troposphere Mixed Phase Clouds & Water Vapour Dynamical coupling Radiation Aerosol interaction with clouds Atmospheric Chemistry Energy & momentum fluxes & tracers vertical & meridional Arctic Boundary layer Biogeochemical fluxes Sea ice Ocean mixed layer Ecosystem Cold halocline  salinity Vertical mixing Atlantic Ocean water inflow and currents Ocean

CanESM2 at 125.7°E 81.1°N (Future climate from CMIP5)  Influence of surface properties on energy transfer in atmosphere- ice-ocean column?  Ocean boundary layer stratification and structure with season?  Role of transient processes in vertical ocean mixing?

 Vertical fluxes between Metzner et al., under revision, JGR atmosphere, mixed layer and the Possibility of Cold Halocline breakdown halocline during storm events Warmer Atlantic water reaches the surface and opening of leads Enhanced ocean surface heat fluxes would enhance Arctic warming Drifting Buoys

Multidisciplinary Ice-based Distributed Observatory (MIDO)

Lüdeling Institute// Sabine

Buoy- „array systems“ Distributed network Wegener • - Array: instruments on central floe and 25 km • : Alfred Multi-disciplinary observations • Graphic Critical element of YOPP Outline

Logistical preparations Earlier attempts MOSAiC motivation Coupled system Atmosphere Ocean-Sea Ice Biogeochemistry and Ecosystem Focus areas BGC and ECO Ozone Layer Stratosphere

Troposphere Mixed Phase Clouds & Water Vapour Dynamical coupling Radiation Aerosol interaction with clouds Atmospheric Chemistry Energy & momentum Fluxes & tracers vertical & meridional Arctic Boundary layer Biogeochemical fluxes Sea ice Ocean mixed layer Ecosystem Cold halocline  salinity Vertical mixing Atlantic Ocean water inflow and currents Biogeochemical processes

• What are main biogeochemical processes controlling  Mercury Hg  Volatile Organic Compounds (VOC)  Dimethylsulphide (DMS) cycling in Arctic Ocean?  Annual cycle over the Arctic Ocean

• How are cycles of Mercury, halogens (bromine and iodine), Ozone, VOCs, and Dimethylsulphide connected in ocean, ice, and atmosphere?

• Impact of DMS on Ice nucleation and Cloud condensation particles?

• Connection to ocean ? Ecosystem

Seasonality in bloom development and downward carbon export Wassmann & Reigstad 2011 Anja Sommerfeld Pascal

Effects of melting sea ice on carbon & nutrient cycles & marine ecosystem responses  Nutrients and primary production  Phytoplancton growth and population dynamics  Which factor (light or nutrients) controls present-day Arctic productivity?  Upwelling and mixing in all seasons Looking foreward for a successfull expedition with unique data sets and safe return of all participants