Transcript 132 KB - arcus

Arctic System Reanalysis
David H. Bromwich1,2 and Keith M. Hines1
1-Polar
Meteorology Group
Byrd Polar Research Center
The Ohio State University
Columbus, Ohio
2-Department
of Geography
Atmospheric Sciences Program,
The Ohio State University,
Columbus, Ohio.
Why do we need an Arctic System Reanalysis (ASR)?
1. Rapid climate change appears to be happening in the Arctic. A more
comprehensive picture of the coupled atmosphere/land surface/ ocean
interactions is needed.
2. Global reanalyses encounter many problems at high latitudes. The ASR
would use the best available description for Arctic processes and
would enhance the existing database of Arctic observations. The ASR
will be produced at improved temporal resolution and much higher
spatial resolution.
3. The ASR would provide fields for which direct observation are sparse
or problematic (precipitation, radiation, cloud, ...) at higher resolution
than from existing reanalyses.
4. The system-oriented approach would provide a community focus
including at least the atmosphere, land surface and sea ice
communities.
5. The ASR would provide a convenient synthesis of Arctic field
programs (SHEBA, LAII/ATLAS, ARM, ...)
Great Opportunity now for ASR
1. Utilize the data storage and knowledge gained from recent reanalyses (ERA40, NARR) and recently compiled Polar Pathfinder products
2. SEARCH and upcoming International Polar Year (2007)
Preliminary components for ASR are needed during current window
of opportunity
1. Improved cloud clearing for TOVS retrievals
2. Detailed evaluation of ERA-40 and NCEP's NARR
3. Prepare polar-optimized, high resolution mesoscale model
NOAA seed funding: An Initiation of Arctic Reanalysis Activity in
SEARCH
by Co-Investigators: Bromwich, Serreze, Tilley and Walsh to lay the
groundwork for ASR
Seed Funding Tasks
Task 1. Evaluation of ERA-40 and NCEP's NARR for the Arctic
While these are the current state-of-the-art reanalyses, they each have strengths and weaknesses.
The strengths can be used to set benchmarks for ASR. Documenting the weaknesses will point
to those attributes that are most in need of improvement.
Task 2. Enhancement of WRF for Arctic applications
A great deal of knowledge has been gained from the earlier reanalyses and with operational
forecasts and research simulations with Polar MM5. This knowledge must be harnessed and
used to develop Polar WRF. Then Polar WRF must be properly tested in the Arctic.
Task 3. Incorporation of non-atmospheric components into ASR
The prior reanalyses have been primarily atmospheric, thus the ASR is the vanguard of the
coupled approach. The Arctic provides a viable opportunity for the inclusion of other system
components such as the land surface and sea ice, and ultimately the ocean. The interdisciplinary
SEARCH project is the ideal framework.
Task 4. Preliminary data assimilation activities
The sensitivities of assimilated fields to the input of different types of polar data will be
evaluated and documented. It is important that the input data include previously unused data
such as some high-latitude Canadian rawinsondes, some Russian NP observations, and VTPR
and TOVS information. Also, GPS occultation soundings and MODIS observations need to be
examined.
Issues for ASR Raised at High-Latitude NWP
Workshop in Fairbanks, Alaska October 2003
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Spatial resolution 20-30 km
Southern margin at 45 N
Time period? ... 1957-present?
Land surface data assimilation
Better land surface data for Asia
Treatment of sea ice including snow cover
Mixed-phase clouds and supercooled water
Diamond dust
Very stable boundary layer
Horizontal pressure gradient near steep terrain
Upper boundary condition
Assimilate radiances or retrievals into the WRF 3DVAR?
Computational needs
International participation
Funding
Distribution of tasks
Lessons from Polar MM5
A. The Pennsylvania State University (PSU)-National Center for
Atmospheric Research (NCAR) Fifth-generation Mesoscale Model (MM5)
has been adapted for polar applications
(1) Real-time forecasting for Antarctica (AMPS)
(2) Forecasting for the Arctic Rivers (RIMS) Project
(3) Contemporary climate studies
(4) Paleoclimate studies
B. Polar Modifications to MM5
(1) Revised cloud / radiation interaction
(2) Modified explicit ice phase microphysics
(3) Optimized turbulence (boundary layer) parameterization
(4) Implementation of a sea ice surface type
(5) Improved treatment of heat transfer through snow/ice surfaces
(6) Improved upper boundary treatment
C. Future Modifications for Polar MM5
(1) Improved treatment of horizontal pressure gradient force
(2) Additional testing and development of upper boundary treatments
(3) Improved snow/ice albedo parameterization
D. Future after Polar MM5?
RIMS Surface Temperature at Barrow
(71.3 N, 156.78 W, elev = 4m)
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PMM5 forecast
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RIMS Surface Wind Speed at Barrow
(71.3 N, 156.78 W, elev = 4m)
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WRF will be the base atmospheric model for ASR
http://wrf-model.org/
The Weather Research and Forecasting Model is in production by
multiple agencies and development groups.
The "next generation" model after MM5, ETA, etc. will provide
an advanced mesoscale forecast and assimilation system.
WRF, a community model, will provide closer ties between
research and applications.
Up to 1 km resolution
Portable, efficient, parallel-friendly
Currently in development. Version 1.3 is available to public.
Projected Timeline for WRF Project
Development Task
2000
2001
2002
2003
2004
Basic WRF model (limited
physics, standard initialization)
Implementation and evaluation
of alternative prototypes
Model physics
Simple
Research suite
Advanced
Research quality NWP version
of WRF
3D-Var assimilation system
Basic
4D-Var assimilation system,
ensemble techniques
Research
Basic
Testing for operational use at
NCEP & AFWA
Diagnosis of operational
performance, refinements
Release and support to community
Operational deployment
Advanced
Advanced
2005-08
WRF Development Teams
Numerics and
Software
(J. Klemp)
Working Groups
Dynamic Model
Numerics
(W. Skamarock)
Software
Architecture,
Standards, and
Implementation
(J. Michalakes)
Data
Assimilation
(T. Schlatter)
Standard
Initialization
(J. McGinley)
Analysis and
Validation
(K. Droegemeier)
Community
Involvement
(W. Kuo)
Operational
Implementation
(G. DiMego)
Analysis and
Visualization
(M. Stoelinga)
Workshops,
Distribution,
and Support
(J. Dudhia)
Data Handling
and Archive
(G. DiMego)
Model Physics
(J. Brown)
3-D Var
(J. Derber)
4-D Data
Assimilation
(D. Barker)
Model Testing
and Verification
(C. Davis)
Ensemble
Forecasting
(D. Stensrud)
Atmospheric
Chemistry
(P. Hess)
Land Surface
Models
(J. Wegiel)
Regional Climate
Modeling
(proposed)
Operational
Requirements
(G. DiMego)
Operational
Forecaster
Training
(T. Spangler)
Model Physics in High Resolution NWP
Physics
“No Man’s Land”
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Resolved Convection
3-D Radiation
LES
10
100
km
Cumulus Parameterization
Two Stream Radiation
PBL Parameterization
ASR has the Potential to be a
Flagship Activity under SEARCH
A. A multi-disciplinary approach for monitoring the Arctic
environment
B. Provides a 50-yr context for current climate change
C. Can monitor future climate change
D. Major resources will be required to prepare for the ASR
and to execute it.
E. Now is the ideal time to undertake the ASR.