Transcript Report on the WWRP, THORPEX, WCRP Workshop “Improvement of Weather and Environmental Prediction in Polar Regions” (6 to 8 October 2010, Oslo, Norway) Gilbert Brunet WWRP/JSC.

Report on the
WWRP, THORPEX, WCRP Workshop
“Improvement of Weather and
Environmental Prediction in Polar Regions”
(6 to 8 October 2010, Oslo, Norway)
Gilbert Brunet
WWRP/JSC Chair
WWRP/THORPEX, Kick off meeting of the Polar Prediction Research
Project
(Geneva, 30 November – 1 December 2011)
1. Background
• At its 15th session (November 2009), the WMO
Commission of Atmospheric Sciences (CAS)
recommended, as a legacy of the International Polar
Year (IPY) to:
• Establish a THORPEX Polar Research project to:
– improve understanding of the impact of
polar processes on polar weather;
– the assimilation of data in Polar Regions;
– and the prediction of high impact weather
over Polar Regions.
• The Executive Council Panel of Experts on Polar
Observations, Research, and Services (ECPORS) recommended that
• efforts be made to further polar prediction for
weather and climate and to extend efforts to
snow, ice, carbon, and ecosystem modelling
and analysis.
This requires involvement from:
– World Weather Research Programme (WWRP),
including THORPEX,
– the Global Atmospheric Watch (GAW),
– and the World Climate Research Programme
(WCRP) and support from WMO Members.
Improving Polar Predictions
– General Recommendations
• Verification
– formal inter-comparison of polar predictions (pole-wards of 60oN
and 60oS) using the existing WMO procedures and, if necessary,
the adoption of new metrics for these comparisons need to be
initiated;
– strengthening of verification activity utilizing operational and
research data bases such as the TIGGE data bases is needed.
• Data Assimilation and Observation
– the establishment of the utility of existing surface based and
satellite observations through data assimilation experiments (e.g.
CONCORDIASI project);
– “data mining” to catalogue existing databases and reports – this
may require the establishment (or nomination) of a few archive
centres to manage IPY data and data from past campaigns;
– there is a requirement for new observations for the Polar Regions.
General Recommendations
(ctd.)
• Predictability and Physical and Dynamical Processes
– There is an urgent need for concerted physical process studies
which will need new field campaigns;
– We need to establish well thought out numerical experiments
with coupled models in the Polar Regions in collaboration with
WCRP (CMIP5, SPARC);
– More efforts need to focus on research and development for
coupled atmosphere–hydrological–cryosphere–surface modelling
and observation.
The Gulf of St. Lawrence (GSL) Coupled
Atmosphere-Ice-Ocean Forecasting System
• A dynamic representation of sea
•
•
•
•
surface conditions improves the
meteorological forecast locally;
Time-evolving ice cover in
coupled model allows vast
stretches of ice-free water to
open up, buffering atmospheric
temperatures;
Use of coupled model results in
significantly improved forecasts
all around the GSL;
Demonstrates importance of airsea-ice coupling even for shortrange weather forecasts;
Next step: implementation in the
Canadian Arctic (METAREA).
-5°C
-15°C
-25°C
Scientific Challenges
• Assimilation must rely more on the use of satellites.
– most radiative channels used for satellite retrieval are
for the free atmosphere, while near-surface and lower
troposphere coverage is lacking;
– the satellite data is more difficult to use over land and
sea-ice than over the ocean due to snow covered (cold)
surfaces;
– when using data from microwave channels accurate
values for sea-ice emissivity, penetration depth (into
snow and ice) of microwave radiation, and a realistic
first guess of surface temperature have all to be taken
into account;
– There is a close link between the microphysical
properties of the NWP model and successful satellite
data retrieval.
Scientific Challenges (ctd.)
• The underlying surface and the need for surface–sea-ice
coupled models
– Need for an accurate and detailed description of the
underlying surface in terms of ice, snow, leads,
polynyas and tides and sea-ice characteristics and sea
surface temperature;
– There is a lack of observations and an understanding of
the physical processes in Polar regions;
– Other issues that were recognized as important for
NWP are how to initialize (snow analysis) and how to
treat blowing snow;
– There is a need for detailed process studies and careful
parameterizations supported by observations.
Scientific Challenges (ctd.)
• Planetary Boundary Layer (PBL) parameterization including PBL clouds
The Arctic offer significant challenges relative to the lower latitudes
– semi-permanent Arctic inversion ( NB: Most models have problems predicting the lowest
level temperatures over the continent; also winds at 300hPa and at the surface.);
– very frequent occurrence of clouds peaking at more than 90% in summer ;
– PBL schemes need to consider the presence of clouds, while in order to solve the polar
cloud issue, one has to work on cross-cutting issues linked to the PBL, surface,
microphysics, and radiation, as these processes are closely linked;
– to much stress (turbulence) in stable boundary layers in existing schemes;
– the lack of a spectral gap significantly complicates the parameterization problem as
stability functions may have to depend on model resolution;
–
our fundamental knowledge of cloud processes is highly limited, and we lack key
observations to constrain even highly simplified cloud parameterizations;
– it is currently not known what determines the phase and mixture of clouds.
Low Visibility and Precipitation in the Arctic
Ice fog in Yellowknife, NWT, FRAM project
Goals: Using NWP models,
surface observations, and
satellites to better detect and
predict low visibility conditions
associated with ice fog,
freezing fog, and precipitation
Ice crystals during a light snow in
Yellowknife (taken by Canon
camera)
Impacts: Aviation, weather,
marine and land transport, and
climate.
Icing, turbulence, radiation POSS prec. sensor Frost on particle sensor
sensors
due to ice fog, Barrow AL
Ice fog from PMWR at -35C
in Yellowknife
YK FRAM instrument set for fog,
precip, radiation, turbulence, vis etc.
GCIP ice sensor
Ice fog from MODIS
satellite in Yellowknife
FD12P Vis
MRR radar
GCIP ice particle spectra
Establishment of an IPY
Legacy Project
• This legacy project should be based on a few NWP internationally
coordinated polar initiatives (new or existing);
• Additionally support for the observational component would be
needed from:
(GOS/WWW),
(GAW), (GOOS),
(WHYCOS),
(GTOS – hydrological cycle parameters (GTN-H)),
GCOS Terrestrial Network for Permafrost (GTN-P)),
GCOS Terrestrial Network for Glaciers (GTN-G, – parameters of the
cryosphere.
• A new IPY legacy project should tap into the scientific and human
capacity of the National Meteorological and Hydrological Services
(NMHSs) who have an interest in scientific, societal, and economic
applications for Polar Regions and should include the participation of
the WWRP (SERA, MFRWG, JVWG, NWG), THORPEX, and the WCRP
(SPARC, CLIC, SOLAS) communities of scientists;
High Resolution Deterministic Prediction System at
Environment Canada
• GEM (Global Environmental Multiscale)
model, limited area model (LAM)
configuration;
• 1 LAM grid, x = 2.5 km;
• 24-36 hour predictions, 2-4 runs per day;
• Full data assimilation system of atmospheric
measurements;
• Land data assimilation system (250 m) for
detailed initial conditions of surface fields;
• Associated ensemble prediction system to
provide forecast uncertainties.
 By 2015, Environment Canada will have complete coverage over
Canada by an unprecedented convection permitting and nonhydrostatic high-resolution numerical weather prediction system
Polar Prediction Project
•
The Report from the Workshop on “Improvement of Weather and Environmental
Prediction in Polar Regions” (Met No Oslo, 6 to 8 October 2010) has been
published to the web
http://www.wmo.int/pages/prog/arep/wwrp/new/documents/Polar_NWP_Meeting_
Outcomes_FINAL.pdf;
• Three forecast prediction ranges are of interest:
–
short-term regional forecasts (one hour to 48 hours);
–
medium-range forecasts (one day to two weeks);
– sub-seasonal to one season forecasts.
• It was clear from the workshop discussions on “gaps” that many of the problems
are common to all prediction systems (including climate) whatever the range –
notably, problems with the parameterization of atmospheric, oceanic, and landsurface physical processes.
– Example: Climate models may under-predict the rate of Arctic warming
because their boundary layers are too stable
12
World Meteorological
Organization
2011 Congress
World Meteorological
Congress
WWRP
Polar Prediction project – “Congress acknowledged the success of the ten
projects of the International Polar Year THORPEX cluster, and supported the CAS
recommendation that, as a legacy of the IPY, a THORPEX Polar Research project
be established to improve the understanding of the impact of high impact weather
over Polar Regions. Congress also emphasized the need to have an adequate
observational and telecommunication network for the Polar Regions in order to
provide the relevant high impact weather services for the region. “
“Congress strongly urged all those concerned to ensure that such a Polar
Prediction Research project is established in support of, inter alia, the Global
Framework for Climate Services. Furthermore, the EC-PORS, at its Second
Session in Hobart in October 2010, agreed to the concept of a major decadal
initiative to develop a Polar Prediction System (Global Integrated Polar Prediction
System - GIPPS). Congress recognized the importance of effective coordination
between these various initiatives, and invited Members to contribute as
appropriate. “
Sub-seasonal to Seasonal Prediction – “Congress noted that the JSCs of the
WWRP and the JSC for WCRP and WWRP/THORPEX ICSC set up an
appropriate collaborative structure to carry out and international research initiative
on sub-seasonal to seasonal forecasting. This initiative should be closely
coordinated with the CBS infrastructure for long-range forecasting and with the
future developments of climate service delivery and the Global Framework for
Climate Services. “
“Congress was pleased to note that the WWRP-THORPEX / WCRP workshop on
“Sub-seasonal to seasonal prediction” (Exeter, December 2010) had
recommended the establishment of a Panel/Project for Sub-seasonal Prediction
Research and Applications - Panel members being drawn from WWRPTHORPEX, WCRP, CBS, CCl, JCOMM, CHy, CAS and CAgM and their relevant
programme bodies. “
Polar Prediction Contd.,
• This project will require a Steering Group (consisting of
members with scientific and operational expertise and
representatives of the user community). The first task for the
Steering Group (supported by a WMO consultant) will be the
preparation of an Implementation Plan, which includes
estimates of resources and a strategy for the coordination of
polar prediction research;
• If the plan is well received by the community, and if the YOTC
model is followed, a Project Office should be established at
an institution with a major interest in polar prediction;
14
Polar Prediction Initiative Steering
Committee Membership
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Thomas Jung (Chair, AWI, Germany)
Peter Bauer (ECMWF)
David Bromwich (Byrd Polar Research Centre, USA)
Trond Iversen (Norwegian Met Service, Norway)
Greg Smith (Environment Canada, Canada)
Pertti Nurmi (Finish Meteorological Institute, Finland)
Ian Renfew (University of East Anglia, UK)
Chris Fairall (NOAA/ESRL, USA)
SERA Expert (TBD)
Mikhail Tolstykh (HRC, Russia)
Data Assimilation Expert (TBD)
•
Secretary
Neil Gordon (Secretary, National Weather Service, New Zealand)
Improving Polar Predictions – Scientific
Challenges
Thank you
Merci