Facilitating Research into Operation: NCAR perspective

Roger WakimotoNCAR

Member Institutions

Board of Trustees

Finance & Administration

Katy Schmoll, VP

Corporate AffairsJack Fellows, VP

NCARRoger Wakimoto, Director

Maura Hagan, Deputy Director

UCAR Community Programs (UCP)

Jack Fellows, Director Hanne Mauriello, B&A

Computational & Information Systems Laboratory (CISL)

Al Kellie, Associate Director

NCAR Earth System Laboratory (NESL)

Greg Holland, Interim Associate Director

Research Applications Laboratory (RAL)

Brant Foote, Associate Director

Earth Observing Laboratory (EOL)

Sue Schauffler, Acting Associate Director

Cooperative Program for Operational Meteorology

Education & Training (COMET)

Tim Spangler

Constellation Observing System for Meteorology Ionosphere

Climate (COSMIC)

Bill Kuo

Unidata

Mohan Ramamurthy

Joint Office for Science Support (JOSS)

Gene Martin

Global Learning & Observations to Benefit the

Environment (GLOBE)

Ed Geary

Digital LearningSciences (DLS)

Karon Kelly

Visiting Scientists Program(VSP)

Meg Austin

National Science Digital Library (NSDL)

Kaye Howe

Advanced Study Program

(ASP)Chris Davis

UCARRichard Anthes,

President

Integrated Science Program (ISP) Peter Backlund

Budget & Planning(B&P)

Rena Brasher-Alleva

Research Relations

Peter Backlund

NCAR LibraryMary Marlino

High Altitude Observatory (HAO)

Michael Thompson, Associate Director

Computational & Information Systems Laboratory (CISL)

Al Kellie, Associate Director

Institute for Mathematics Applied to Geosciences (IMAGe)

Doug Nychka

Operations & Services DivisionAnke Kamrath

Technology Development DivisionRich Loft

NCAR Earth System Laboratory (NESL)Greg Holland, Interim Associate Director

Climate & Global Dynamics Division (CGD)Bill Large

High Altitude Observatory (HAO)Michael Thompson, Associate Director

Mesoscale & Microscale Meteorology Division (MMM)Rich Rotunno (Interim)

Research Applications Laboratory (RAL)Brant Foote, Associate Director

Aviation Applications Program (AAP)Bruce Carmichael

Hydrometeorological Applications Program (HAP)Roy Rasmussen

Joint Numerical Testbed (JNT)Barb Brown

National Security Applications Program (NSAP)Scott Swerdlin

Weather Systems & Assessment Program (WSAP)Bill Mahoney

Earth Observing Laboratory (EOL)Roger Wakimoto, Associate Director

Cyberinfrastructure & Data Services (CDS)Michael Daniels

Design & Fabrication Services (DFS)Jim Moore, Interim

Field Project Services (FPS)Brigitte Baeuerle

In-Situ Sensing Facility (ISF)Stephen Cohn

Research Aviation Facility (RAF)Jeff Stith

Remote Sensing Facility (RSF)Wen-Chau Lee (Acting)

Technology Development Facility (TDF)Alan Fried

Atmospheric Chemistry Division (ACD)Bill Randel

Governing Entities

UCAR (University Corporation for Atmospheric Research)

NCAR (National Center for Atmospheric Research) and Labs

Facility & Service Providers

Scientific Research Divisions

Education & Application Programs

UOP (UCAR Office of Programs)

Institute

Climate Science and Applications Program (CSAP)Lawrence Buja

NCAR involvement with DTC

• Approximately 2/3 of DTC staff reside in RAL’s Joint Numerical Testbed

• NCAR hosts the DTC Director’s Office• NCAR/NESL/MMM provides support for

the WRF modeling community• Modeling research & development

conducted at NCAR have significant potentials for operational applications

Worldwide WRF User Participation 130 Foreign Countries

Registered Users 8/08/10 U.S. Universities, govt. labs, and private sector 4759

Foreign users 9272 -------- 14031 5070 active subscribers to wrf-news@ucar.edu

425 email inquiries per month

WRF Registered Users

WRF User Community• WRF is a modeling system jointly developed by the

research and operational community over the past decade• The number of registered user exceeds 14,000, and it

keeps growing.• This is a big community of which operational centers can

leverage its research results. • NCAR/MMM, NCEP/EMC, and DTC provide community

user support for WRF modeling system• NCEP is transitioning to the NEMS framework for its

modeling systems. • We need to ensure there is a path for research-to-operation

transition. Model software framework should not become an obstacle for collaboration.

NCAR’s Modeling R&D: Some examples

• NESL: – Development of Model for Prediction Across Scales

(MPAS)– WRF 4D-Var system– WRF EnKF data assimilation– Radar data assimilation– Cloud-scale ensemble prediction

• CISL:– DART (Data Assimilation Research Testbed)

• RAL:– Model verification tools development– Aviation weather forecasting

Based on Voronoi Tesselations (hexagons)

Jointly developed, primarily by NCAR and LANL, for weather, regional climate and climate applications.

MPAS infrastructure - NCAR, LANL, others.MPAS - Atmosphere (NCAR)MPAS - Ocean (LANL)MPAS - Ice, etc.

Bill Skamarock, Joe Klemp, Michael Duda, Sang-Hun Park, Laura Fowler NCAR/NSFTodd Ringler LANL/DOEJohn Thuburn Exeter UniversityMax Gunzburger Florida State UniversityLili Ju University of South Carolina

MPAS: Model for Prediction Across Scales

Prediction Across Scales

Vertical velocity contours at 1, 5, and 10 km (c.i. = 3 m/s)

30 m/s vertical velocity surface shaded in redRainwater surfaces shaded as transparent shellsPerturbation surface temperature shaded on baseplane

500 m cell spacingSupercell at 2 hours

Jablonowski and Williamson baroclinic wave test case.Relative vorticity (s-1), day 16 (jet level)

MPAS formulation is demonstrably accurate and efficient at both large and small scales, and should scale well on next-generation supercomputers.

MPAS-Atmosphere, global configuration MPAS-Atmosphere, cloud-model configuration

MPAS: Variable Resolution Capability

• Initial test results using variable resolution grids are encouraging (baroclinic waves and squall lines).• Atmospheric (hydrostatic and nonhydrostatic) and ocean solvers are

robust on these grids.

Local refinement capabilities are critical for NWP and regional climate applications.

MPAS - Current Status - August 20103D Solvers• Hydrostatic 3D SVCT solver (pressure coordinate).• Nonhydrostatic 3D SVCT solver (height coordinate).• Both solvers work on the sphere and on 2D and 3D Cartesian

domains.• Tests results confirm viability of Voronoi C-grid discretization at

large scales (global) and cloud-permitting scales for both solvers.

• Variable-resolution grid results are encouraging.

Present and Future Development• Weather, regional climate and climate physics suites.• Further testing of variable resolution meshes, physics

development.• Further development and testing of higher-order transport

schemes.

Expectations• NWP testing by early next year.• Friendly-user release summer/fall 2011.

Software Engineering

MPAS software:• Developed based on MPAS applications requirements.• Lightweight (for rapid prototyping, ease of maintenance).• We have developed and use a Registry similar to that used

in the WRF infrastructure.• We are exploring using other model physics (e.g. from

CCSM, WRF, GFS) directly from the other models’ repositories (in the spirit of Kalnay et al’s Interchange of Physical Parameterizations proposal in BAMS 1989 620-622).

• We are considering possible model couplers (e.g. CPL7).• We have not adopted any formal software framework.• We are considering lightweight, industry-standard

approaches for the MPAS software infrastructure (e.g. OOPS - Object-Oriented Prediction System being developed at ECMWF).

MPAS - Current Status - August 2010

The Ensemble Kalman Filter (EnKF)

• EnKF combines data assimilation and ensemble forecasting– Analysis step produces ensemble of analyses, given new

observations– Analysis step employs covariance, estimated from short-range

ensemble– In forecast step, make ensemble of short-range forecasts from

ensemble of analyses

• Attractions for mesoscale applications– Few assumptions about covariances, so applicable to range of

scales/phenomena– Flexible to details of model, such as complex microphysical

schemes– Ease of implementation and parallelization; no adjoints

• For applications here, use 50-100 members

Data Assimilation Research Testbed (DART)

• Provides general, model-independent algorithms for ensemble filtering

• Numerous DART-compliant models– ARW, CAM, NOGAPS, …– Applications to atmospheric, ocean, and space weather data

assimilation

• Parallel analysis scheme that scales well to 100’s of processors

• See http://www.image.ucar.edu/DAReS/DART/

Real-Time Analyses for Tropical Cyclones

• Analyses from WRF/DART provided ICs for NCAR’s high-res TC forecasts during 2009 season

• Produced 36-km analyses every 6 h – Assimilate conventional obs + satellite winds + vortex position, intensity– NO bogussing of any kind; no satellite radiances

• WRF configuration– “hurricane” physics + KF convection– 36 km, with stationary 12-km nest centered on each TC/TS/TD

• System cycled continuously for ~ 4 months

Real-Time Analyses for Tropical Cyclones (cont.)

Real-Time Analyses for Tropical Cyclones (cont.)

• Analyses captured all 2009 storms, from depressions to hurricanes.– No need to bogus– No spurious storms, despite not assimilating radiances

RMS fits of analysis and 6-h forecast to best-track estimates

Courtesy R. Torn

Real-Time Analyses for Tropical Cyclones (cont.)

• Analysis increment from position observation– Reflects covariance (wind speed, vortex position),

which in turn reflects vortex structure– Shifts vortex coherently and consistently in all

model fieldsHurricane Bill, 00Z 19 Aug 2009

Wind speed @ 1st level

contours: ens.-mean, 6-h forecast

colors: increment given obs of vortex position (analysis - forecast)

Courtesy S. Cavallo

Radar data assimilation slides

b) WRF 1h FCST

WRF-VAR radar data assimilation testing in central U.S.

• Radar data assimilation systems are being tested and improved over selected U.S. regions and foreign countries

• These systems include GSI, WRF-VAR, and WRF/DART.

• 3DVAR, 4DVAR, and EnKF are all involved in the testing/development.

• These systems are tested with WRF as the forecast model and with a goal to support operational applications.

WRF 3h FCSTRadar Mosiac

Beijing operational pre-testing

25 radars assimilated

Different requirements in Operation and Research NWP

• Operation:– Robustness– Efficiency– Easy maintenance– Prefers incremental

changes– Thorough testing

• Research:– Flexibility– Multiple-choices– User friendliness– Community support– Innovation

Effective Research to Operation Transition

• Need to challenge (attract) research community to work on problems of interest to operation

• Need a clear path for R2O• Need to minimize obstacles preventing

R2O (e.g., model software framework)• Need to provide sufficient support for

O2R and R2O activities

Concluding Remarks

• NCAR is committed to:– Support the WRF community for many

more years to come.– Support the development of next

generation modeling and data assimilation systems (e.g., MPAS, DART/EnKF)

– Support the research to operation transition through the DTC