from laps to vlaps multiscale hot-start analysis noaa esrl/gsd/fab y. xie, s. albers, h. jiang, d....
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From LAPS to VLAPSmultiscale hot-start analysisFrom LAPS to VLAPS
multiscale hot-start analysis
NOAA ESRL/GSD/FAB
Y. Xie, S. Albers, H. Jiang, D. Birkenheuer, J. Peng, H. Wang, and Z. toth
Global Systems Division
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OutlineReview of LAPS features;Multigrid variational analysis (Space and
Time Multiscale Analysis System, STMAS);Modernizing LAPS using STMAS:
Multigrid variational analysis;Variational cloud analysis;Balance and constraints;Use of remote sensing data;
Future plan and collaboration with KMA
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LAPS reviewAn objective analysis (modified Barnes) scheme;Meteorological states are analyzed sequentially
and dynamic balance is applied afterward;Hot-start:
Analysis of microphysics;Temperature adjustment;Vertical velocity;Analysis of water vapor;
Efficiency;Ease of use, particularly with local data.
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Transition from Traditional to Fully Variational LAPS
state vars, wind (u,v) clouds / precip
balance and constraintsin multi-scale variational
analysis
Windanalysis
Temp/Ht analysis
Humidity analysis
Cloud analysis
balance
Traditional LAPS analysis: Wind, Temp, Humidity, Cloud, Balance
Ultimately
Temporary hybrid system: Traditional LAPS cloud analysis
and balance
NumericalForecast
model
Large Scale Model First Guess
Cycling Option
Var.LAPS
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LAPS assimilates a wide range of datasets and local data
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6
LAPS USER BASE
• NOAA– ~120 WFOs (via AWIPS), ARL, NESDIS
• Other US Agencies– DHS, DoD, FAA, CA DWR, GA Air Qual.
• Academia– Univ of HI, Athens, Arizona, CIRA, UND,
McGill
• Private Sector– Weather Decision Tech., Hydro Meteo,– Vaisala, Greenpower Labs
• International agencies (10+ countries)– KMA, CMA, CWB, Finland (FMI), Italy, Spain, – BoM (Australia), Canary Islands, HKO, – Greece, Serbia
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Cloud analysis vs. all sky camera
• Demonstrates high resolution analysis of hydrometeors, aerosols, land surface• Check 3-D cloud placement and microphysical properties• Forecasts can also be visualized• Data assimilation a future possibility
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Multigrid variational analysisSTMAS
Inherit traditional LAPS multiscale (Barnes) analysis by a multigrid technique (wavelet and recursive filter were also tested and yielded similar results);Improvement of standard 3dvar;
Enhance the analysis by a fully variational analysis with simultaneous balance and constraints;Improvement of traditional LAPS;
Better assimilate remotely sensed observation data, such as satellite IR/VIS, cloud optical depth and radar;Improvement of traditional LAPS.
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OAR/ESRL/GSD/Forecast Applications Branch
Sequence of 3-4DVARs with proper balances– need for covariance information reduced
Similar to traditional LAPS
Standard 3-4DVARWith banded covariance
Possible ensembleFilter application
Long waves Short waves
Xie et al. “A Space–Time Multiscale Analysis System: A Sequential Variational Analysis Approach”, MWR 2011
Analysis and model initialization may endat different multigrid levels
MULTISCALE VARIATIONAL ANALYSIS
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Humidity Analysis resolving discontinuity
LAPS
STMAS
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VLAPS (STMAS) bound constraintsVLAPS uses the L-BFGSB in its variational analysis
and this quasi-Newton software allows users to use bound constraints;
VLAPS can use cloud and/or reflectivity information to constrain its humidity analysis:Currently, if an area is covered with cloud and
reflectivity, VLAPS constrains its humidity to 100% RH.
An on-going evaluation is to make it as weak one for accommodating other obs (e.g., GPS);
Such bound constraints are considered for variational cloud analysis.
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A real time example
Possible collaboration: improving covariance
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VLAPS assimilation of remote sensing observations with collaborators
A long list of datasets:AMSU-A and B for Taiwan now;GPS (TPW now and slant delay next);GOES sounder IPW;Cloud mask and optical depth (testing now);Dual Pol radar (Serbia Meteorological Agency);GOES IR and visible imagery (with CRTM);GOES-R cloud cooling and over-shooting;……
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AMSU-B Up Air Impact
No AMSU-B AMSU-B all channels
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GPS TPW data impact
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General methodology of VLAPS analysis of remote sensing data
A forward operator mapping analysis variables to observations: F(X)≈Y;
An adjoint of this operator, F’(X);
An additional term in the minimization cost function: (F(X)-Y)T O-1 (F(X)-Y);
Minimization is done with added gradient term from the remote sensing data.
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GPS TPW forward operator
vertically
Surface grid box
Domain top
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GPS Examples:A forward operator for GPS TPW(specific humidity):
An integration of vertical specific humidity along a given GPS zenith path;
A forward operator for GPS slant delay:An integration of refractivity along the GPS slant
path;
Both are differentiable in terms of the control variables, sh for the former and sh, T and p for the later.
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Variational cloud analysisCurrently, use the traditional LAPS cloud analysis as an
initial guess;Cloud mask as constraints of cloud ice, liquid, rain and
snow (possible graupel), including ;Cloud phase products are also used;Cloud optical depth is being tested;IR and visible data will be assimilated;Temperature is used to constrain cloud ice and liquid;Variationalization of LAPS cloud components, e.g.,
estimated cloud from RH;Sophisticated covariance is needed for filling the data
void regions.
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Cloud optical depth vs. cloud ice analyses
VLAPS
LAPS
Cloud Optical Depth OBS
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VLAPS (1km) without GPS and COD
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Future PlanIdentify and assimilate important observation
data sources, dual pol radar, IR and visible;Improve balance and constraints, particularly
on the hydrometer state variables;Continuity (already in), hydrostatic, etc;WRF FDDA collaborating with US Army;WRF adjoint for short 4DVAR assimilation
window.Improve forecast model parameters, e.g.,
snow cover, land types etc;Parallelization of VLAPS;Object-oriented design of VLAPS.
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Collaboration with KMAForecast model for 200-m resolution run with
tuned model parameters and topography;Local observation datasets, in-situ and
remotely sensed data, including all-sky images;Observation forward operators and their
adjoint;Variational cloud analysis;Hydrometeor constraints;Terrain following VLAPS code development;GIT LAPS software sharing;Object-oriented VLAPS development.