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CURRICULUM VITAE

By Ray Greene,2014-03-26 16:14
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Introduced the DA activity at EMC. DA group at EMC is planning to use Use of real observations or simulated observations in a perfect model framework?

    SUMMARY OF TELECONFERENCE DISCUSSION

    May 17, 2007, 1:00pm 3:00 pm EST

Present: J. Whitaker and T. Hamill (CDC), C. Bishop and Dan Hodyss (NRL),

    M. Zupanski (CIRA/CSU), Jeff Anderson and Joe Tribbia (NCAR) I. Szunyogh

    and E. Kalnay(UMD), Y. Song, Z. Toth and M. Wei (NCEP/EMC) , E. Kostelich

    (Arizona State Uni.)

    Agenda:

    1). Review of progress by each group (5-10 minute each group with slides

     if possible)

    2). Plans for the next 3-6 months by each group

    3). Status of benchmark, discussion on comparison of results

    4). Longer term issues-expected benefits & computational costs of ens-DA

     and hybrid variational approach.

Jeff Whitaker:

Reported the progress he has made. Modified the DA code for new GFS model,

    and new GSI will be used for forward operator (GSI has been implemented since

    May 1, 2007) in ensemble DA. New codes have been ported and debugging has

    started at T126. Satellite data have not shown much benefit for the ensemble DA

    analysis. They are looking at flow-dependent error covariance and model errors.

    Increasing model resolution is expected to reduce the role of model errors.

Eugenia Kalnay:

Sent some slides and presentations from recent meetings. The experiments

    using Quasi-Geostrophic model showed that 40-member LETKF is better than

    12-hour 4D-Var which is better than hybrid (3D/Var + 20 BVs), while 3D-Var and

    24-hour 4D-Var are the worst and best respectively. Singular vectors and bred

    vectors are compared with the errors of the day. It was demonstrated that the

    errors of the day are most important for providing background error covariance in

    LETKF and 3D-Var.

Jeff Anderson:

Reported the newly released MPI version of DART using WRF model. Ran test

    with re-analysis observations. New inflation strategy, which is called adaptive

    inflation, greatly improved the analysis results.

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Milija Zupanski:

    Still working with setting up computers. Was working on development of new ensemble localization scheme that will take time into account.

Istvan Szunyogh:

    Finished a final version of paper for Physica D that summarizes the results based on LETKF without satellite radiances. Implemented LETKF on NCEP model and produced some good results from using satellite data. Gave support to Jeff Whitaker’s experiments.

Craig Bishop:

    Sent some new slides to show the results from his new localization scheme where a SENCORP moderation function is constructed from equivalent potential temperature correlation filed smoothing in both horizontal and vertical using a Gaussian weighting function in Fourier phase space was performed. He showed the impact of using these moderation function in DA on forecast and analysis with NOGAPS ensembles. It is going to be tested in NVADAS system at NRL first. In the future it can be used in Whitaker’s ens-DA system.

Mozheng Wei:

    Introduced the DA activity at EMC. DA group at EMC is planning to use ensemble information to improve the background covariance matrix in GSI. The initial plan is to use the hybrid method which consists of both static 3D-Var background and flow-dependent ensemble based error covariance matrix. Ensemble group is hoping to get the estimate of analysis error variance from GSI for ensemble use in initialization.

Zoltan Toth:

    Planned the next meeting in August 2007. Future Ens-DA should work with regional, ocean and global ensembles. Two-way comparison with future 4D-Var system. Proposed to create a new benchmark at T126L64 from GSI with new observations from May 1, 2007 when GSI was implemented.

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    SUMMARY OF TELECONFERENCE DISCUSSION

    January 30, 2007, 11am 1:30 pm EST

Present: J. Whitaker and T. Hamill (CDC), C. Bishop and Dan Hodyss (NRL),

    M. Zupanski (CIRA/CSU), Joe Tribbia (NCAR)I. Szunyogh and E Kalnay(UMD),

    Y. Song, Z. Toth and M. Wei (NCEP/EMC) , E. Kostelich (Arizona State Uni.),

    Fuqing Zhang (Texas A&M), Gregory Hakim (Uni. of Washington)

Agenda:

    1). Review of progress by each group (5-10 minute each group with slides

     if possible)

    2). Plans for the next 3-6 months by each group

    3). Status of benchmark, discussion on comparison of results

    4). Longer term issues-expected benefits & computational costs of ens-DA

     and hybrid variational approach.

    5). Link wirh regional DA efforts (Grep Hakim and Fuqing Zhang joined

     discussion)

Istvan Szunyogh:

Finished a paper that summarizes the results based on LETKF without satellite

    radiances. In the new code, bias correction can be done in different ways.

    Results can be compared with different bias correction schemes. The code has

    been tested by Jeff Whitaker to compare with EnSRF in the same environment.

    The differences from these two algorithms are not significant right now. More

    real observations are going to be tested.

Eugenia Kalnay:

Suggested to try Milija Zupanski’s MLEF idea in the system Jeff Whitaker is

    testing. Reported different ways of turning inflation factors for background error

    covariance. Experimented different ways of adaptive tuning of observation errors.

Jeff Whitaker and Tom Hamill:

Sent the slides he showed at Jan 2007 AMS meeting. The results showed that

    6-12 hours forecast improvement at 100hPa is more than at 850hPa.

    Improvement is largest in data sparse regions, such as SH or stratosphere. A

    radiative transfer model was used, carried out bias correction in radiance

    observations, e.g. scan-angle correction and using linear regression model. The

    bias coefficients in Air-Mass bias correction scheme were updated using global

    ETKF equations.

Craig Bishop

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    Based on the slides from last tele-conference, described more detail about his method for moderating spurious ensemble correlations. The method called Smoothed ENsemble Correlations Raised to a Power (SENCORP) is proposed to provide flow adaptive moderations functions in comparison with the conventional method used in current DA systems. It has shown advantage over hierarchical ensemble filter which is subject to noise when tested in a simplified system. The next step is to test it in NOGAP system at Navy. A full description of this method is expected at later stage.

Milija Zupanski:

    Work on testing MLEF (maximum likelihood ensemble filter) is continuing using real observations and satellite radiance data. A lot of attention has been on localization using background error covariance information. Plan to collaborate with experts in computer science department at CSU and more research will be done. Also on agenda is testing a local version of MLEF.

Fuqing Zhang:

Introduced his group’s work on regional scale EnKF in comparison with WRF 3D-

    Var. In his experiments, it was found that EnKF consistently produced better results than WFR 3D-Var. The benefit from using ensemble mean to initialize the forecast has been demonstrated. Pointed out that multi-physics model also improves analysis results.

Greg Hakim:

    Introduced the operational EnKF data assimilation system over North America in University of Washington. Pointed out a lot of results from their group available on web site. The Washington EnKF system is focusing on North America. The boundary conditions are generated from NCEP GFS forecasts. They found larger noise from the boundary. More research work needs to be done to reduce the noise near boundary.

Zoltan Toth:

    Planned to schedule the next tele-conference during March-April 2007. Raised possibility of possible future comparison or implementation of regional ensemble DA at NCEP. Other questions raised: Do we need to run T254 benchmark? How to best tune observation errors and background error inflation and localization? Exploit Milija’s adaptive localization technique.

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    SUMMARY OF TELECONFERENCE DISCUSSION

    October 19, 2006, 1 0am 1 pm EST

Present: J. Whitaker and T. Hamill (CDC), C. Bishop (NRL), M. Zupanski

    (CIRA/CSU), I. Szunyogh (UMD), Y. Song, Z. Toth and M. Wei (NCEP/EMC) , E. Kostelich (Arizona State Uni.)

Agenda:

    1). Review of progress by each group (with slides if possible)

    2). Plans for the next 3-6 months by each group

    3). Status of benchmark, discussion on unified verification of results

Jeff Whitaker and Tom Hamill:

    Sent 3 slides prior to the meeting. One of the slides shows the schematic of ensemble DA flow with 2 members. The DA system uses NCEP SSI to compute

    observation operator which maps the model state to observational points. Bias correction is carried out by inputting ensemble mean to SSI. The DA system can be easily switched to LETKF from EnSRF. Several inflation schemes have been built in including additive inflation which is being used to produce the results in the figures. The results without satellite data show that both ensemble DA systems are much better than SSI in the SH where the observations are less. The differences between LETKF and EnSRF are not significant. However,

    LETKF is much faster, possibly due to the fact that LETKF computes Hx itself, while EnSRF calls SSI. But it is also harder to do data thinning in LETKF. When satellite data are included. Only results from LETKF are shown. They are similar to SSI, except in SH where SSI is better.

Craig Bishop

    Showed 18 slides about moderating spurious ensemble correlations continuing their work on covariance localization for ensemble based Kalman filter data assimilation system. A method of using Smoothed ENsemble Correlations

    Raised to a Power (SENCORP) moderation functions is proposed to provide flow adaptive moderations functions in comparison with the conventional method used in current DA systems. A fixed moderation function is multiplied in the convention method. This method can also be used to simulate model errors. Again the experiments are carried out on an extremely simple system. The results are positive. Jeff Whitaker expressed interest in testing this method in his ensemble Kalman filter DA system. A full description of this method is expected at later stage.

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Istvan Szunyogh:

    Real observations are used for LETKF formulation which uses ETKF solution for a small patch at each grid point. The algorithm is more efficient than EnSRF algorithm during the experiments with and without satellite data. The code has been given to Jeff Whitaker to compare with EnSRF in the same environment. The differences from these two algorithms are not significant right now. Emphasis will be on bias correction of radiance in higher levels. A paper will be submitted in a few weeks. LETK is planned to be operational in Brazil.

Milija Zupanski:

    Work on testing MLEF (maximum likelihood ensemble filter) has begun on using real observations and satellite radiance data. More attention has been paid to bias correction by studying the PDF distribution. He will have more cooperation with people working in satellite data. Dual resolutions will be tested. A lot of more results from the experiments will be expected in the next half year. The results will provide a good comparison with the results from other schemes.

Zoltan Toth:

    Scheduled the next tele-conference in December 2006 after Thorpex meeting in Germany. Grep Hakim will join Thorpex project for regional ensemble data assimilation. Suggested a new benchmark with higher resolution summer case. NOAA Thorpex has requested CPU time on Air Force supercomputers. Proposed a new analysis for shorter lead time of 1-3 hours.

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    SUMMARY OF TELECONFERENCE DISCUSSION

    July 27 2006, 1 pm 3 pm EST

Present: T. Hamill (CDC), J. Anderson and J. Tribbia (NCAR), C. Bishop and

    Dan (NRL), M. Zupanski (CIRA/CSU), I. Szunyogh (UMD), Y. Song, Z. Toth and M. Wei (NCEP/EMC) ( E. Kostelich, J. Whitaker and E. Kalnay on vacation or leave)

Agenda:

    1). Review of progress by each group (with slides if possible)

    2). Plans for the next 3-6 months by each group

    3). Status of benchmark, discussion on unified verification of results

Craig Bishop and Dan:

    Showed a new way of doing covariance localization for ensemble based Kalman filter data assimilation system. They provided 3 slides showing how to estimate the forecast error covariance matrix using historical data by modulation. The experiments using this method on a simple system showed positive results. A full description of this method is expected at later stage.

Milija Zupanski:

    After securing accounts on NCEP IBM computers and experiments have started to test his MLEF (maximum likelihood ensemble filter). MLEF is similar to ETKF, except solves for mode (instead of mean) of distribution. It has tested the simulated and real obs in NCEP operational environment. Further experiments are planned.

Tom Hamill:

    After successfully compared their ensemble data assimilation results with T62 NCEP SSI benchmark, using same or less amount of conventional data, some satellite data have been added to the experiments. The preliminary results are very positive. The pace of further experiments is delayed by the lack of computer resources. They are looking NCEP for help.

Istvan Szunyogh:

    Started work with real obs, and applied ETKF formulation to local patches, each grid point at a time. The algorithm is very efficient. They gave the code to Jeff Whitaker to compare with his square root filter. Plan to do more research on use of additive inflation procedures. Studied the effect of imperfect model on DA results, using bias correction. Two slides distributed showed positive results.

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Jeff Anderson (Unfunded collaborator):

    No funding from NOAA. Developed a more scalable generic filter, looked at sampling error in ensemble filters. The system runs an ensemble of ensembles (4-8) to estimate the error covariance localization factors. This procedure is very expensive, but only needs to do it once in a while. They argued that this method of generating covariance localization factors will make the filter more scalable and more generic.

Yucheng Song:

    Briefly described a new NCEP T62 SSI benchmark analysis/forecast data set . The new benchmark is based on using satellite data as more groups are ready to handle larger number of observations.

Zoltan Toth:

    Pointed out there is a need for different groups to share some common verification packages in order to compare different algorithms and filters. NCEP/EMC will initiate the discussion toward the development of common verification software..

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    SUMMARY OF TELECONFERENCE DISCUSSION

    July 29 2005, 11 am 1 pm EST

Present: J. Whitaker (CDC), J. Anderson (NCAR), C. Bishop (NRL), M.

    Zupanski (CIRA/CSU), I. Szunyogh, E. Kostelich (UM), Y. Song, and Z. Toth (NCEP/EMC) (T. Hamill missed the call, M. Wei on travel)

Agenda:

    1. Brief description of activities in first year - Each group described their work

    and main results

Jeff Whitaker

    Successfully compared their ensemble data assimilation results with T62 NCEP SSI benchmark, using same or less amount of data (in fact, only 75-150k pieces of data were used, compared with ~300k in SSI only data from +/-1 hr window

    used, and even that was thinned). No radiance, radar, or scatterometer data used. Results are very encouraging, 5-10% rms error reduction compared with SSI results (see his slides). Processing of remotely sensed data with same sequential algorithm is not practical, looking for alternative solutions (ETKF?) Tested 3 types of variance inflation methods, difference between successive archived analysis fields may work best, simple inflation by a coefficient almost as good

Istvan Szunyogh

    Started work with simulated obs, worked well. Adapted ETKF formulation, still applied locally (region by region), very efficient algorithm. When switched to assimilation of real observations some bugs got into code, working on clearing up software. Expects some results by end of summer 2005. Looking into use of additive inflation procedures. Analyzing effect of imperfect model on DA results, using bias estimation ideas. Discussed a slide indicating that a relatively small ensemble may be able to well describe low dimensional dynamics for global circulation (PECA-type analysis).

Craig Bishop

    Was unable to hire post-doc, working with Master level student, had to adjust research plans somewhat. Worked on producing large ensembles with ETKF. In parallel, work on generating ensemble perturbations to be centered around NAVDAS variational analysis, similar to M. Wei’s research at NCEP: use estimate of analysis error variance derived from NAVDAS to constrain initial ensemble variance using ET algorithm. Reports that successfully used ET technique to inflate covariance: uses ET to transform old archived ensemble data tfor inflating variance in tropics of current ensemble Toth points out link between this work and that of D. Hou at EMC who plans to use similar technique to introduce stochastic perturbations. Plans to experiment with combining ensembles from different sources.

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Milija Zupanski

    Hired postdoc, secured accounts on NCEP IBM computers. Plans to test his

    method, similar to ETKF, except solves for mode (instead of mean) of distribution.

    Currently setting up software on NCEP machines, will start testing with simulated

    obs soon, in couple of mos will start using real obs. Plans using bos operators

    and other applicable software from NCEP SSI code. This will enable quick

    technology transfer to NCEP operations if research is successful.

Jeff Anderson (Unfunded collaborator)

    Made an attempt to port GFS system to NCAR. Work is not complete, no funding

    from NOAA. Worked on generic filters, looked at sampling error in ensemble

    filters. Found a solution where no inflation is needed in perfect model setup. Ran

    some experiments, without much tuning, with NCAR T85 CAM climate model,

    real observations, January 2003 cases, using radiosonde and other traditional

    data, but no radiances. Compared results with GFS T254 operational system (p.

    16 of his slides). Very encouraging results, 5-10+% rms error reduction for

    temperature, even larger reduction for low level wind errors. Problem with winds

    higher up traced to use of inaccurate obs error variances with ACAR data.

Yucheng Song

    Briefly described NCEP T62 SSI benchmark analysis/forecast data set that he

    prepared for use by other groups (see below)

Zoltan Toth

    Pointed out few links between external research and NCEP development

    activities: Connection between model error studies of B. Hunt (UM) and M. Pena

    (EMC); ET initialization by C. Bishop (NRL) and M. Wei (EMC); Inflation with ET

    method by C. Bishop (NRL) and D. Hou (EMC). nd year ZT commented that the results by JW-TH & FA are very encouraging, and 2). Preliminary discussion on plans for 2warrant continuation of ensemble-based DA research work. There was general

    agreement on this. JW and CB discussed potential for using ensemble

    covariance information for improving variational schemes. They pointed out the

    demonstrated ability of variational schemes to process large amounts of data. JA

    made the point that ensemble-based DA is a new field and there is no evidence

    that these methods could not be modified to cope with heavy data volume, all

    agreed on this. MZ mentioned that after working on 4DVAR for 10 yrs, he

    switched to ens-DA methods because he believes they offer a theoretically more

    appealing approach. IS & ZT pointed out that CPU limitations on current

    operational machines should not constrain research aimed at 3-5 years into the

    future. Focus should be on understanding whether and how much improvements

    can be gained by using ens-DA methods compared to variational methods.

    Algorithms should be built with resource limitations in mind, but that should not

    be the primary consideration at this stage. Optimization of procedures can be

    considered and will become more important as the research evolves. ZT

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