Transcript Improving forecasts in polar regions: programmatic activities (research & operations) in Canada Ayrton Zadra Recherche en prévision numérique atmosphérique (RPN-A) Meteorological Research Division Environment Canada WWRP, THORPEX, WCRP.

Improving forecasts in polar regions:
programmatic activities (research & operations)
in Canada
Ayrton Zadra
Recherche en prévision
numérique atmosphérique (RPN-A)
Meteorological Research Division
Environment Canada
WWRP, THORPEX, WCRP Polar Prediction Workshop
“A THORPEX Contribution to the Improvement of Polar Predictions on Weather-to-Seasonal Timescales”
6 to 8 October 2010, Oslo, Norway
Contents
• Research
– THORPEX-IPY
– Sea-ice analysis
• Operations
– NWP
– Coupled models
• Ongoing and planned projects
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THORPEX Arctic Weather
and Environmental
Prediction Initiative
(TAWEPI)
Primary objective: develop & validate
Polar- GEM, an experimental regional
NWP model over the Arctic
Modelling sub-projects
(1) polar clouds
(2) sea-ice
(3) snow over sea-ice
Data assimilation sub-projects
(4) validation/assimilation of polar
orbiting satellite data;
(5) stratospheric analyses;
(6) singular vector sensitivity
studies
http://collaboration.cmc.ec.gc.ca/science/rpn/tawepi/en/index.html
Member of IPY-THORPEX cluster
www.ipy-thorpex.no
Project: Snow over sea-ice
Investigators: Y.-C. Chung, S. Bélair, J. Mailhot
Goals
1-D, blowing snow model,
PIEKTUK (Déry, 2001)
• better represent the interactions
between snow pack and sea ice
• to examine the effect of blowing snow
on the simulation of snow and sea ice
snow
Sea ice
ocean
Methodology
1-D, multi-layer
snow model
SNTHERM
(Jordan, 1991)
 coupling of 3 schemes/models:
- RPN/MSC thermodynamic sea-ice model
- SNTHERM multi-layer snow model
(Jordan,1991)
- PIEKTUK blowing snow model (Dery, 2001)
 verification against SHEBA data
Multi-layer, thermodynamic sea ice model from
Meteorological Service of Canada (MSC) operational
forecasting system run 1-D, offline model
sublimation
Conclusions
suspension
Coupled scheme improved simulation of:
- timing of snow depletion
- ice thickness / growth
wind
- formation of ice slabs at bottom of ice pack
- sublimation due to blowing snow, which
improves snow depth, duration of snow cover,
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and underlying sea ice properties
saltation
Project: Polar clouds
Investigators: F. Chosson, P. Vaillancourt, J. Milbrandt
Objective
Improve representation of
clouds & precipitation and
surface radiative energy budget
in GEM, specially over the Arctic.
Methodology
Study the sensibility of Polar-GEM
forecasts to the choice of
microphysics scheme:
• single-moment Sundqist (1989)
• multi-moment Milbrandt & Yau (2005)
cloud
fraction
height (km)
• cloud fraction, condensate
and precipitation are highly
sensitive to microphysics
scheme
• schemes are very sensitive
to choice of time step
• sub-grid cloud fraction is
needed
%
height (km)
Conclusions
total
condensate
g/m^2
Fig: Vertical profiles of cloud fraction and total condensate,
averaged
over space (Arctic) and time (48h), from three simulations
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of Polar-GEM using the Sundqist (black), single-moment M&Y
(blue) and double-moment M&Y (red) schemes.
Project: Sea-ice modelling
Investigators: N. Steiner, G. Flato, Y. Lu
Objectives
• Implement & expand latest version of Los Alamos CICE model (used in
•
•
several GCMs and US Navy's ice-ocean forecast model)
Apply & test model in various settings (operational sea-ice, ocean &
atmosphere forecasting – coupled to Polar-GEM/GEM-LAM, coupled
climate studies)
Develop a Canadian community sea-ice model to be used in climate mode
(GCM, RCM) and forecast mode (weather, sea-ice)
Initial tests


Global CICE4.0 was installed on Canadian Centre for Climate modelling
and analysis (CCCma) as standalone sea-ice model
Initially tested with climatological daily forcing from a 20 year GCM run
(atmosphere) and monthly Polar Science Center
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Project: Assimilation of polar orbiting satellite data
Investigators: O. Pancrati, L. Garand, S. Heilliette
Background
• AIRS radiances
(Atmosp. IR Sounder)
- 87 channels
assimilated since Jun 2008
- radiances not sensitive to lower
clouds assimilated
• Validation of cloud height/cover retrieval
- for data quality control
- to infer model deficiencies
• Specific problems found in Arctic & Antarctic
regions linked to cloud parameter
determination. Validation with independent data
needed (MODIS, Calipso, MISR datasets)
- CO2-slicing technique (retrieval of cloud
parameters) was reexamined and applied to
both real AIRS radiances and simulated ones
6-h and 12-h forecasts), then compared to
model output of cloud parameters
- allows separating systematic biases
associated with the retrieval technique from
those of forecast errors.
- cloud parameter fields are compared to
equivalent products available from
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MODIS and AIRS standard processing -- good
overall agreement is found
Project: Stratospheric analyses
Investigators: M. Reszka, J. DeGrandpré, A. Robichaud, C.
Charette, M. Roch, S. Polavarapu
• Dynamics and chemistry analyses for
March 1, 2007 – Feb 28, 2009 have been
generated and provided to SPARC IPY
database
O3
• Dynamics fields were produced using
Canadian Meteorological Centre's 3D-Var
global assimilation scheme and GEM forecast
model
• Chemistry fields were produced using an
online stratospheric chemistry package
(Belgian Institute for Space Aeronomy)
OBS
GEM-BACH analysis
Comparison of trace-gas measurements from
a Fourier transform spectrometer with GEMBACH IPY analyses at Eureka, Nunavut – Mar
- fine structure of polar temperatures during
01 to Oct 30, 2007: Total (and partial) columns
2007/2008 stratospheric sudden warming
derived from spectrometer data (blue) and
- trace gas distribution as compared with
analyses (red) are in very good agreement for
spectrometer measurements
most gases measured (e.g. O3, N2O, HCl,
- deep stratospheric intrusions as revealed by the
HNO3). Figure provided by R. Batchelor (U. of
ozone field
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Toronto)
• Data set is being used to study several
processes, including
Project: Singular vector sensitivity studies
Investigators: A. Mahidjiba, M. Buehner, A. Zadra
Singular vector analysis of 80N
48h forecast sensitivity for
the summer of 2007.
Target region is outlined
60N
with a dashed black line.
Warmer colours denote
stronger response.
40N
0°
90°E
180°E
90°W
• The sensitivity of Arctic forecast errors to initial analysis
•
•
error is quantified using singular vectors.
SV analysis was performed daily during the IPY period.
The combination of SVs that best reproduces the
observed forecast error is used to evaluate Arctic –
midlatitude interactions.
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0°
Project: Improved sea-ice analyses
(Lead: Mark Buehner, MRD/EC)
• collaboration between Environment Canada
(EC) and Canadian Ice Service (CIS)
• 3DVar FGAT analysis (sea-ice fraction only,
for now)
• assimilates AMSR-E, SSMI, CIS ice charts
and image analyses (RadarSat, EnviSat)
• 3 domains: Global, N. America and Gulf of StLawrence
N. America (~5km)
Global (~10km)
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GSL (~5km)
Operations: The Canadian Regional
Deterministic Prediction System (RDPS)
• March 2009: core grid of the regional model (15-km resolution) was
extended over the Arctic regions + new radiative transfer scheme
• June 2009: implementation of 0600 UTC and 1800 UTC runs
• June 2009: extension into the stratosphere (model top went from
10 hPa to 0.1 hPa)
northward
extension
of the core
of the Canadian
regional model
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Operations: The Canadian Regional Deterministic
Prediction System (RDPS) and Regional Ensemble
Prediction System (REPS)
Fall 2010: New RDPS will
become operational, using
• limited-area model (red line in
figure)
• 3D-Var assimilation system
independent from the global
system
Project lead: L. Fillion
2011: A 20-member regional
ensemble prediction system
will become operational:
• 33km resolution
• same grid (red line)
Project lead: M. Charron
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Operations: The Canadian High Resolution
Deterministic Prediction System (HRDPS)
high resolution (2.5 km)
limited-area models:
EXPERIMENTAL
(USER ACCOUNT)
OPERATIONAL
(CMC OPERATIONS)
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Source: J. Milbrandt
Operations: The Canadian High Resolution
Deterministic Prediction System (HRDPS) –
The Arctic Model
Material provided by forecasters
from the National Laboratory for
Hydrometeorology and Arctic
Meteorology – Environment Canada
Mission:
• provide improved understanding
and prediction high-impact weather
• focus on hydro-meteorological and
northern latitude weather processes
and phenomena
Fig: Domain covered by the CMC
2.5km Arctic LAM.
Relevant processes:
Relevant forecasts *:
- winter:
wind / blizzards
“all boundary layer
processes (turbulence,
- summer: low cloud / fog
cloud microphysics, etc.)
that feed into low-level
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*Source: R. Goodson (HAL/EC)
winds and/or visibility”
Operations: Coupled Atmosphere-Ice-Ocean
Forecast System for the Gulf of St. Lawrence
• A fully-interactive coupled atmosphere-ice-ocean
forecasting system for the Gulf of St. Lawrence
(GSL) is now running operationally at the Canadian
Meteorological Centre (CMC)
– Produces daily 48hr forecasts (weather, ice, ocean)
• Results during the past year have demonstrated that
the coupled system produces improved weather
forecasts in and around the GSL during all seasons
– Shows that atmosphere-ice-ocean interactions are indeed
important even for short-term Canadian weather forecasts
– Great potential for improved ice-ocean components and
global systems
• Forecasts used by:
– Canadian Coast Guard (Marine safety and routine
operations)
– Canadian Ice Service (Ice products)
– Fisheries and Oceans Canada (Search and Rescue, Oil
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Spill)
Slide kindly provided by G. Smith (MRD/EC)
Operations: The Gulf of St. Lawrence (GSL)
Coupled System (forecast season, 2008)
• A dynamic representation of sea
surface conditions improves the
meteorological forecast locally
–
Operational regional forecasting
system (GEM-Ops) has tendency
to overestimate cold events in
winter.
▪ Due to overly high ice
concentration and thickness
–
Dynamic ice cover in coupled
model allows vast stretches of
ice-free water to open up,
buffering atmospheric
temperatures
-5°C
• Use of coupled model results in
•
-15°C
significantly improved forecasts all
around the GSL
Further discussion of this system
and physical ice-ocean processes
involved provided tomorrow by
Greg Smith
-25°C
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Slide kindly provided by G. Smith (MRD/EC)
Operations: The Canadian Global Deterministic
Prediction System (GDPS)
Polar Stratosphere
The major sudden stratospheric warming of January 2009
• Horizontal
resolution: 33km
• 4DVar data
assimilation
system
• June 2009:
extension into the
stratosphere (top
went from 10 hPa
to 0.1 hPa)
Sources: M. Charron,
S.-W. Son, P. Martineau
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Operations: The Canadian Extended Range Prediction
System (ERPS)
(Lead: H. Lin)
Skill of CMC monthly forecast
system:
operational vs experimental
Main changes w.r.t. operational
system:
• single model ensemble with
perturbed physics
• more accurate initial conditions
• better representation of SST
anomalies
• improved sea-ice & snow analysis
• higher resolution
Note: increased skill in polar
regions.
Figure 4: Correlation skill of time mean
surface temperature: operational 40member ensemble forecast system
(left); experimental EPS-based 20member MFS (right).
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Operations: The Canadian Extended Range Prediction
System (ERPS)
(Lead: H. Lin)
GEM forecast
persistence
-The Canadian monthly forecast
system shows skill* in predicting
the NAO index (top figure)
- Results indicate that the
predictability of the NAO index
increases in the presence of a
strong MJO (bottom figure)
* here the skill measured as the correlation
coefficient between observed and forecast
NAO index
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Plans: The Polar Communications & Weather (PCW) Mission
Source: L. Garand
Objectives
- Reliable communications in the high latitudes (North of
70º)
- Provide high temporal/spatial resolution meteorological
data above 50º N in support of NWP, environmental
monitoring, emergency response and climate monitoring
Launching: 2017
Endorsed by WMO as major contribution to Earth
Observing System (EOS)
PCW: Constellation on Molniya orbit
– 2 satellites to provide continuous
GEO-like imagery (55-90 N, 0.5-1 km
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VIS, 2 km IR, 12-h period, 63.4 deg.
Inclination; apogee: ~39,500 km; perigee:
~600 km)
Plans: Monthly, global, regional and highresolution systems
• new monthly forecast system expected to become operational in 2011
• resolution of global model to go from 33km to 25km in 2012
• horizontal resolution of regional model is expected to go from 15km to
10km in 2011
• resolution of regional EPS to go from 33km to 25km in 2011/2012
• existing high-resolution (2.5km) Arctic grids may be moved to other
locations
Plans: Sea-ice analysis
- new system expected to become operational for CIS applications in near
future
- will be used to replace “direct insertion” in current Gulf of St-Lawrence
(GSL) system
- soon to be proposed for NWP Page
applications
(regional and global
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systems)
Plans: The Canadian Global Deterministic
Prediction System (GDPS)
Development of a global forecasting Yin-Yang model:
• orthogonal coordinates (easy representation of operators such as Gradient,
Laplacian …）
• no polar singularity
• same grid structure for Yin and Yang components
• easy to nest (as a LAM)
• easy to parallelize (domain decomposition method) = 2-way coupling of 2
LAMs
Yin-Yang grid
by Abdessamad Qaddouri
(see Qaddouri et al. 2008 Appl. Num. Math.)
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Coupled systems: Future directions
• Several new coupled systems
under development as part of
CONCEPTS
CONCEPTS
– Canadian Operational Network of
Coupled Environmental Prediction
Systems
• Tri-departmental collaboration
– To develop coupled atmosphereice-ocean forecasting systems:
▪ Global: Monthly-seasonal
▪ Regional: short-to-medium for
Canadian east coast and
Arctic
• Collaboration with Mercator
– French operational oceanographic
group
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Slide kindly provided by G. Smith (MRD/EC)
Future Canadian Regional System
• Gulf of St. Lawrence
coupled system to be
replaced by N. American
coupled system:
GEM: 10km
NEMO: 1/12° NW Atl
– Northwest Atlantic
– Arctic
– Great lakes
• System to include:
– Atmosphere-ice-ocean
coupled model
– Wave model
– Land surface and blowing
snow
NEMO: 1/12° Arctic
NEMO: 2km Great lakes
• Analysis systems:
–
–
–
–
Atm: 4DVAR/EnKF
Ocean: SEEK (Mercator)
Ice: 3DVAR
Precipitation(snow):
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CaPa
Slide kindly provided by G. Smith (MRD/EC)
References and Links
Chung, Y.-C., S. Belair and J. Mailhot (2010): Simulation of Snow on Arctic Sea Ice Using A Coupled
Snow/Ice Model. Journal of Hydrometeorology, 11, 199-210
Chung, Y.-C., S. Belair and J. Mailhot (2010): Blowing snow on Arctic sea ice: results from an
improved sea ice/snow/blowing snow coupled system. Submitted to Journal of Hydrometeorology
Deacu, D., A. Zadra and J. Hanesiak (2009): Simulating wind channeling over Frobisher Bay and its
interaction with downslope winds during the 7-8 November 2006 wind event. Atmosphere-Ocean
48(2), 101-121
Garand, L., O. Pancrati and S. Heilliette (2010): Validation of forecast cloud parameters from
multispectral AIRS parameters. Submitted to Atmorphere-Ocean
Caya, A., M. Buehner and T. Carrieres (2010): Analysis and forecasting of sea ice conditions with
three dimensional variational data assimilation and a coupled ice-ocean model. Journal of
Atmospheric and Oceanic Technology, 27, 357-369
Fillion, L., M. Tanguay, E. Lapalme, B. Denis, M. Desgagne, V. Lee, N. Ek, Z. Liu, M. Lajoie, J.-F.
Caron, C. Page (2010): The Canadian Regional Data Assimilation and Forecasting System.
Accepted in Weather and Forecasting
Meteorological Service of Canada: http://www.msc-smc.ec.gc.ca/
Canadian Meteorology Centre: http://www.msc-smc.ec.gc.ca/cmc/index_e.html
Canadian Weather Office: http://www.weatheroffice.gc.ca/canada_e.html
Canadian Ice Service: http://www.ec.gc.ca/glaces-ice/default.asp?lang=En&n=D32C361E-1
TAWEPI: http://collaboration.cmc.ec.gc.ca/science/rpn/tawepi/en/index.html
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PCW mission: http://www.asc-csa.gc.ca/eng/satellites/pcw/default.asp
SPARC-IPY: http://www.atmosp.physics.utoronto.ca/SPARC-IPY/
THANK YOU
Acknowledgments
S. Belair, M. Buehner, A. Caya, M. Charron, F. Chosson, Y.-C.
Chung, L. Fillion, G. Flato, L. Garand, R. Goodson, S. Heilliette, V.
Lee, H. Lin, Y. Lu, A. Mahidjiba, J. Mailhot, J. Milbrandt, O.
Pancrati, S. Polavarapu, A. Qaddouri, M. Reszka, G. Smith, N.
Steiner, P. Vaillancourt
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Canada and the World Marine Weather Forecast Areas
Planned activities include:
• observational monitoring (e.g. buoys, drifters, plane campaigns)
• integrated Arctic environmental prediction
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http://weather.gmdss.org/metareas.html