multidisciplinary drifting observatory for the study of ... · eval sea-ice fore-casts assim....
TRANSCRIPT
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Matthew Shupe – Univ. of Colorado/CIRES
On behalf of many…..US DOE MOSAiC TeamM. Shupe, G. de Boer, K. Dethloff, E. Hunke, W. Maslowski, A. McComiskey, O. Persson, D. Randall, M. Tjernström, D. Turner, J. Verlinde
International Coordination TeamM. Rex, M. Shupe, M. Nicolaus, D. Perovich, B. Rabe, C. Provost, E. Damm, B. Loose, A. Waite, M.Reigstad, A. Rinke, W. Maslowski, U. Nixdorf
International Science Plan TeamD. Barber, K. Dethloff, S. Gerland, J. Inoue, C. Lee, B. Loose, A. Makshtas, W. Maslowski, M. Nicolaus, D. Notz, I. Peeken, D. Perovich, O. Persson, J. Schmale, M. Shupe, M. Tjernström , T. Vihma, J. Zhao
US Science Development TeamM. Alkire, C. Ashjian, J. Bowman, J. Creamean, G. de Boer, C. Fairall, D. Helmig, E. Hunke, J. Hutchings, J. Intrieri, J. Kay, J. Key, R. Kwok, C. Lee, B. Loose, W. Maslowski, D. Noone, D. Perovich, O. Persson, C. Polashenski, A. Roberts, M. Shupe, T. Stanton, M. Steele, M.-L. Timmermans, J. Toole
Multidisciplinary drifting Observatory for the Study of Arctic Climate
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Francis et al. 2009
Dukhovskoy et al. 2006
www.iarc.uaf.edu
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The central Arctic is changing dramatically,characterized by major sea-ice decline & more younger ice.
Do we know why? and (importantly) how?
Courtesy J. Stroeve
Arctic in Transition
Sept. 2012
nsidc.org
1979-2000
median
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Incoming solar radiation
200 W m2
Reflected by
clouds, aerosol
& atmosphere45
26
70
Reflected
by surface
Absorbed by
atmosphere
59
Turbulence
3
3Evapo-transpiration
3
3 257 231
231237
20
20
133
Surface radiation Absorbed by surface
reflected solar
radiation
115 W m2
back radiation
emitted by
atmosphere
30
Outgoing longwave
radiation 183 W m2
Absorbed by surface
+98
+2
-100
2
ARCTIC ENERGY BUDGET (f > 65°N)
Sea ice Sea ice
96
Sea-Ice Energy Budget
Persson et al. 2013
Decadal decline can be explained by ~1 W/m2 excess. Kwok and Untersteiner 2011
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Challenge of Sea-Ice Prediction
• Physics matter
• Thermodynamics & Dynamics
• Coupled processes matter
• Interseasonal coupling
• The ice is changing
2006
2012
2010
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Mixed-phase cloud events
accompany warm moist
advection aloft;
Impacts BL structure.
Enhanced Surface Radiation
Coupling
Liquid clouds increase
LWdown by 40-70 W/m2
>>
Significant change in
surface energy budget.
Thermal structure of
snow and ice responds
Persson et al. 2013
Liquid Clouds
ice bottom
ice top
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Coupling
Jackson et al. 2010
>>Fall:
• Solar diminishes;
• Surface cools;
• ML deepens
(buoyancy, wind);
• Heat mixed up;
• Ice production
Spring >> Summer:
• Ice melts;
• ML freshens, shoals;
• Solar heating at
surface/sub-surface.
• Some heat trapped
below ML
T a
bo
ve
fre
ezin
g [
C]
Winter:
Remnant heat
modulates ice
growth
Sun
Sea ice
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2019-2020, annual cycle Central Arctic Basin ice pack
Drifting, interdisciplinary process study in central Arctic sea ice:
1) Central observatory: intensive atmos-ice-ocean-ecosystem observations
2) Distributed Network: Heterogeneity on model grid-box scale
3) Coordinated, multi-scale analysis & modeling activities, Links with YOPP
MOSAiC Plan
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Leading Science Question:“What are the causes and consequences of an evolving and diminished Arctic sea ice cover?”
MOSAiC Science Drivers
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• Energy Budgets• Radiation• Upper Ocean Heat
Storage• Mixing Processes• Turbulence• Stratification• Boundary Layers
Sea-Ice Energy Budgets
Incoming solar radiation
Reflected
solar
Reflected
surface
Absorbed by
atmosphere
Emitted-Absorbed by ice
back
radiation
emitted by
atmosphere
Outgoing LW
Absorbed
by iceSea ice L
arg
e-sc
ale
ad
vec
tio
n
Turbulence
Transmitted
Turbulence
Sea ice
Ocean
Atm
osp
here
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Ice Motion / Deformation
Rigor et al
• Ice Age• Ice Thickness Dist’n• Floe Size Dist’n• Ridging / Leads• FYI Roughness / Drag• Momentum Fluxes• Dynamics / Velocity• Ice –Wave Interactions
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Clouds/Precip/Aerosols
• Phase Partitioning / Mixed-phase
• Radiative Processes• Cloud dynamics /
Turbulence• Spatial Organization• Cyclogenesis• Aerosol Conc. /
Source attribution• Precipitation
Morrison et al
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Biological/Chemical Cycles
• Ecosystems and Communities
• Primary Productivity• Elemental Cycles• Vertical Export and
Mixing• Surface Gas Exchange• Photochemistry• DMS and Aerosol
Precursors
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MOSAiC Operational Drivers
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Interfacing with Satellites
• Operational strategies• Ground validation• Method development• Upscaling
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Data Assimilation
• Impact of additional observations
• Operational forecasts
• Re-analyses
Extra Observations
(radiosondes)
Data
assimilation
Reanalysis
w/o extra
obs
Control
Reanalysis
Global
observations
Atmospheric
forecast
Sea-ice
forecast
Atmospheric
forecast
Sea-ice
forecast
Predictability of
extreme events
Predictability of
sea ice over NSR
JAMSTEC ALERA2
Observing system experiments
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Multiscale Modeling• LES & process modeling• SCM for evaluating parameterizations• CORDEX: Regional model
intercomparison• Experimental, operational sea-ice
forecasting• YOPP: Global coupled system
modelingNOAA-ESRL
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Large-Scale Implications
Jaiser et al.
• Large-scale Transport• Linking local processes
& hemispheric patterns• Upscaling• Implications of regional
change
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Services for stakeholders and
society
Stakeholder Services
Climate services
Operational products,
Monitoring
Process studies
UpscalingCoupling
Evaluation, Development
Ass
essm
ent
Improved process models of Arctic sub-
systems
Improved Weather & Sea-Ice forecasting
Enhanced observing system
and satellites
Year round observations in the Central Arctic
Parameterizations for Earch System Models
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Implementation
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Central Observatory
• Atmospheric remote
sensing
• Radiosondes
• Air sampling
• Ocean profiling/ADCP
• Laboratories for
analysis (biological,
chemical, etc.)
• Base of operations
• Safety
• Data/sample storage
Polarstern IcebreakerFrom Alfred Wegener Institute, Germany
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Met tower
Limited access zone
90o Contaminated turbulence zone
ICE COREFARM
Power line(~500m)
+ ice sites at different ice types
IMB
ARMRadiation
ITPOcean flux
Snow surveys / ice optics / mass balance
Snow surveys / ice optics / mass balance
Met CityTurbulence
OceanSmall CTD
TurbulenceNet sampling
ROV
Ice Hutsnow
Ice Camp
Buoy NodeSEBS
• Low atmosphere
• Surface energy budget
• Snow / precip
• Sea-ice properties
• Gas exchange
• Ocean profiling
• Ocean heat fluxes
• Ocean/ice samples
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Distributed Network• Enhanced coupled-system: >5
nodes, 15km, (ocean profiling, ice mass balance, ocean and atmos heat fluxes)
• Coupled-system: 5-40 km (upper ocean, ice mass, met)
• Ice deformation: 1-40 km (gps)• Spatial mapping: UAS, glider,
AUV, helicopter, scanning• Periodic visits for ocean/ice
sampling & maintenance• Larger-scale network: pan-
Arctic network of surface pressure buoys
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Central Station:
RV Polarstern
Distributed network
of satellite stations
Supply by rendevous with
icebreakers from MOSAiC partners
Additional science on
supply cruises
2019-2020
Drift Concept
Objective:
• Full year drift = full
sea-ice lifecycle
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Drift ConceptModel+satellitedrift trajectories over 2001-2014.
Full year drift
Consider range for access
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96 total = 43 crew + 4 heli + 2 weather + 47 “science”
47 science includes: • cruise leader (1), chief scientist (1), safety/guards (2),
data manager (1), media/outreach (2)• 40 scientists: Atmosphere (8), Sea ice / snow (8),
Ocean (5), Biogeochemistry (4), Ecosystem (6), Flexible (9)
• 26 “International” berths
Funding for resupply logistics: “International” berth fee of 1400 Euro/day
Personnel/Funding
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Team CoordinationRole AWI International
Project LeaderAssistance
M. RexA. Sommerfeld
M. Shupe (CU/NOAA)V. Rachold (IASC)
Atmosphere M. Rex M. Shupe (CU/NOAA)
Sea ice / snow M. Nicolaus D. Perovich (CRREL)
Ocean B. Rabe C. Provost (UPMC)
Biogeochem E. Damm B. Loose (URI)
Ecosystem A. Waite M. Reigstad (UiT)
Model Integration A. Rinke W. Maslowski (NPS)
Data Management A. Macario TBD
Media/Outreach F. Mertens TBD
Remote Sensing G. Spreen (UHB) TBD
Logistics M. HirsekornU. Nixdorf
TBD
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CommitmentsAWI: Polarstern for 13 months
AWI: Ice, Ocean, Bio, Eco science contributions
US DOE ARM: AMF2 + MAOS
TROPOS: RL + MWR + BBrad + sky imager
German Universities: HALO campaign, 2xDL
China/PRIC: Xuelong for resupply
Russia/AARI: Akademik Federov for install
NOAA-PSD/CIRES: Planning support
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Momentum transfer
UAS: Atmos/SfcMapping
Marine methane
cycle
OML interactions
with ice
Plankton, light &
carbon cycle
Satellite cal/val
Ocean mixing and
stratification
Aircraft: radiation,
surface
Cloud-aerosol-precip Reanalysis
Eval
Sea-ice fore-casts
Assim. studies
ABL dynamics
Sfcgas
fluxes
Snow accum. & dist.
Coupled model
Ice-BGC
model
AtmosChem
Regional Model
Ice model
ONR2-3
NSF7-10
NASA0-1
NOAA2-3
DOE2-3
Ice morphology and opticsIce dynamic-
thermodynamic interactions
Ice Energy Budgets Large-
scale model
US Interagency Concept
12-15 berths total
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Key Milestones
Science Plan released: March 2016
Implementation Planning Workshop: July 2015
Implementation plans (online): March 2016
Polarstern site visit: May 2016
Science-based Proposals: 2016-2018
www.mosaicobservatory.org
Thanks!
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Science Input
Aerosol operations: what are the specific priorities? (list instruments). How do we get IN?
Radar operations. Scan strategies.
What specific data sets are needed to support different modeling interests?
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Instrument Measurement Science Justification
Balloon-Borne Sounding System (radiosonde) Twice-daily profiles of P, T, RH, winds Thermodynamic profiles, ABL structure, link with clouds and surface
Microwave Radiometer, 3 channel (MWR3C) Liquid water path, Water vapor path Thermodynamic and cloud property characterization.
Microwave Radiometer (MWR) Liquid water path, Water vapor path Thermodynamic and cloud property characterization
High Spectral Resolution Lidar (HSRL) Backscatter, depol ratio, cloud micro properties Cloud property characterization; aerosol profile info
Micropulse Lidar (MPL) Backscatter, depol ratio, cloud micro properties (May not be needed if HSRL is present)
Doppler Lidar Air motions, turbulence Wind, turbulence in ABL, cloud-atmosphere interactions
Total Sky Image (TSI) Visible hemispheric sky pictures Visual documentation of cloud/sky coverage
Scanning W-band ARM Cloud Radar (SWACR) Radar moments;
Scanning; Cloud micro/dynamical properties
(Similar to Ka-SACR; not needed)
Marine W-band ARM Cloud Radar (M-WACR) Vertical radar moments and spectra; motion stabilized Cloud/precip characterization; Cloud-ABL dynamics; Dual-frequency
synergy with KAZR
Ka-band Scanning ARM Cloud Radar (Ka-SACR) Scanning radar moments; Joint with X-SACR; Cloud/precip characterization and spatial organization.
X-band Scanning ARM Cloud Radar (X-SACR) Scanning radar moments; Joint with Ka-SACR;
Polarimetry.
Cloud/precip characterization and spatial organization.
Ka-band ARM Zenith Radar (KAZR) Vertical radar moments and spectra Cloud/precip characterization; Cloud-ABL dynamics; Dual frequency synergy
with M-WACR
Vaisala Ceilometer Cloud base, backscatter Robust cloud presence and height
Radar Wind Profiler, 915 MHz (1290-MHz) Wind profiles BL wind structure (sub-optimal system for Arctic operations)
Infrared Sounder Spectrometer for IR Spectral
Technology (ASSIST)
IR spectral radiance at zenith or other angles Cloud property characterization; cloud radiative properties
Atmospheric Emitted Radiance Interferometer
(AERI)
IR spectral radiance at zenith or other angles Cloud property characterization; cloud radiative properties
IR All-sky Camera IR radiation, spatial Sky radiative heterogeneity
Multifilter Rotating Shadowband Radiometer
(MFRSR)*
Solar irradiance at multiple wavelengths Atmospheric / aerosol optical depth
Upwelling Radiation (GNDRAD)* Upwelling broadband LW, SW fluxes Surface radiation/energy budget, albedo characterization
Downwelling Radiation (SKYRAD)* Downwelling broadband LW, SW fluxes Surface radiation/energy budget, cloud radiative properties
Eddy Correlation System (ECOR)* Surface turbulent fluxes, carbon dioxide. Surface energy balance; turbulent momentum, heat, CO2 fluxes
Surface Energy Balance System (SEBS)* Up/down SW/LW radiation, soil moisture (little added value beyond GNDRAD, SKYRAD)
Video Disdrometer (VDIS), 2D* Precip DSD and fall speed Precipitation mass/rate
Rain Gauge, weighing bucket* Precipitation rate Precipitation mass/rate (Difficult to operate in cold temperatures)
Met. Instrumentation* Near-sfc P, T, RH, winds Meteorological state for context
Inertial Nav. System Platform pitch, roll, heave Informational, context
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Instrument Measurement Science Justification
CCN200 (dual col.) CCN concentration Baseline characterization of CCN
Condensation Particle Counter (CPC) Aerosol number concentration > 10nm Baseline characterization of total aerosol concentrations
Ultrafine Condensation Particle Counter
(UCPC)
Aerosol number concentration > 2.5 nm Small particle concentration, new particle formation, & source
attribution
Hygroscopic Tandem Differential Mobility
Analyzer (HTDMA)
Aerosol mass, size, and # distribution as
g(RH), particle growth factor
Baseline characterization of aerosol size dist’n; aerosol
hygroscopicity
Ultra High Sensitivity Aerosol Spectrometer
(UHSAS)
Aerosol size dist’n,
50–1000 nm
Baseline characterization of size dist’n
Scanning Mobility Particle Sizer (SMPS) Aerosol size dist’n,
15-450 nm
Baseline characterization of size dist’n
Nephelometer Aerosol light scattering coeff at dry RH, 3
wavelengths
Aerosol scattering, radiative effects
Wet Nephelometer Aerosol light scattering coeff as f(RH), 3
wavelengths
Aerosol scattering, radiative effects
Humidigraph Aerosol light scattering coeff as f(RH) Aerosol scattering, radiative effects
Particle Soot Absorption Photometer
(PSAP)
Aerosol light absorption at 3 wavelengths Aerosol absorption, radiative effects
Photo-Acoustic Soot Spectrometer Aerosol light absorption at 3 wavelengths Aerosol absorption, radiative effects (Low sensitivity in the Arctic)
Aethelometer Aerosol light absorption at 7 wavelengths Aerosol absorption, radiative effects (Redundant with PSAP)
Aerosol Chemical Speciation Monitor
(ACSM)
Aerosol mass spectrum measurements Characterization of aerosol composition
Single Particle Soot Photomoter (SP2) Black carbon mass concentration Role of black carbon
Photon Transfer Reaction Mass
Spectrometer
Volatile organic compounds Characterization of aerosol composition (some similar info to
ACSM)
PILS-IC-WSOC Water soluble organic carbon Characterization of aerosol composition (labor intensive, similar
info to ACSM)
NOx, NOy, CO, O3 Gas concentrations Airmass source, age, transport
Vaisala WXT520 P, T, RH, winds Context
Sodar Vertical wind Context
Cimel Sunphotometer Aerosol optical depth (Similar info to MFRSR)
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German Contributions
TROPOSRaman lidar (Polly-XT): T / q profilesMicrowave radiometer (HATPRO): PWV, LWP, T/q profSky imagerPyranometer/pyrgeometerStandard meteorology
OTHERS1-2 more Doppler lidars
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Atmospheric Needs
• Wind profiler (449 MHz)• Flux tower (20m) with multi-level sonic/met• Distributed surface energy budget stations• Ice nuclei measurements• Surface energy flux over diverse surfaces (UAS?)• Aerosol profiling (UAS?)