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Issue 1 | Spring 2013

Lead Story

Mesoscale Model Evaluation Testbed


The DTC provides a common framework for researchers to demonstrate the merits of new developments through the Mesoscale Model Evaluation Testbed (MMET).

Established in the Fall of 2012, MMET provides initialization and observation data sets for several case studies and week-long extended periods that can be used by the entire numerical weather prediction (NWP) community for testing and evaluation. The MMET data sets also include baseline results generated by the DTC for select operational configurations.

To date, MMET includes nine cases that are of interest for the National Centers for Environmental Prediction/ Environmental Modeling Center (NCEP/EMC). A brief description of each case, along with access to the full data sets is available at http:// Researchers are encouraged to run several case studies spanning multiple weather regimes to illustrate the versatility of this new innovation for operational use.

“Researchers are encouraged to run several case studies to illustrate the versatility of the system.”

One particular case available in MMET is 28 February 2009, when nearly 7 inches of snow fell in Memphis, TN. A squall line marched through the Southeast along the leading edge of a cold front, prompting three tornado and several high-wind reports. The next two days (1-2 March), snow fell from Atlanta to New York, dropping up to a foot of snow in some areas. The figure above shows the two day precipitation accumulation. This case is of interest to NCEP/ EMC because the North American Mesoscale (NAM) model quantitative precipitation forecast valid 1 March shifted precipitation too far north, missing a rain/snow mix in Georgia and falsely predicting snow in western parts of the Carolinas.

If improved forecast accuracy is demonstrated through objective verification results with MMET cases, the technique can be submitted for further extensive testing by the DTC.

Community users can nominate innovations for more extensive DTC testing by filling out the nomination form ( mmet/candidates/form_submission. php).

As MMET continues to mature, additional cases will be made available to broaden the variety of available events in the collection. Submissions for additional cases to be included in MMET are accepted at: http://www. submission.php. For more information on the testing protocol process defined to accelerate the transition of mesoscale modeling techniques from research to operations, please see testing_protocol.pdf.

Comments and questions regarding MMET or any stage of the testing protocol process can be directed to Jamie Wolff (

Contributed by J. Wolff, C. Phillips


Director's Corner

Welcome Message by Bill Kuo

Dear Colleagues,

Welcome to the first issue of a quarterly newsletter for the Developmental Testbed Center (DTC). The research to operations (R2O) transition in numerical weather prediction (NWP) is a major challenge facing the U.S. meteorological community. It has been recognized that the U.S. has the largest community around the world working on weather research and numerical modeling. Yet, most of these research results do not directly benefit operational NWP. The DTC was established in 2003 with a mission to facilitate the transition of research innovations in regional modeling into operations.

An effective R2O process requires active participation of research and operational communities. With this quarterly newsletter, we hope to provide a forum for discussion of important issues facing the NWP community. We will also provide updates on DTC activities that are of interest to the community.

We welcome articles submitted for consideration for publication in upcoming issues.

Contributed by Bill Kuo, DTC Director


Who's Who

John Halley Gotway

If you’ve submitted a question to the MET help desk, or attended a MET tutorial, there’s a very good chance that you already know John Halley Gotway. John joined NCAR’s Research Applications Laboratory (RAL) as a software developer in 2004 and has been contributing to the verification efforts within RAL and the DTC. John’s background is in mathematics.

He worked in Los Angeles at Northrop Grumman, before NCAR and the Rockies drew him to Colorado. His expertise is in numerical verification techniques. In particular, his fingerprint is on much of the internal workings of the MET code. He has also played several roles in applying MET to many testing and evaluation projects.

Outside of work, John’s children, Otis (7), Robin (4), and Cate (1) keep him very busy. One thing you may not know is that besides computing expertise, John contributes directly to critical RAL protein intake by providing fresh eggs from his “gentlemen’s farm” near Longmont. Next time you call or email him with a C++ question, ask him how his chickens are doing.


Bridges to Operations

Innovation in HWRF 2013 Baseline

One of the regional numerical weather prediction models used operationally by the National Weather Service is the Hurricane WRF (HWRF), a coupled model with atmospheric and ocean components that exchange fluxes of short- and long-wave radiation, momentum, moisture, and heat. The momentum flux is particularly important because the strong winds in tropical cyclones cause turbulence and upwelling in the ocean, which can lead to transport of cold water from deep in the ocean towards the surface, reducing the storm’s energy source and causing it to weaken.


A comparison between the ocean cooling in HWRF against observational buoy data, performed by the Hurricane Research Division of NOAA’s Atlantic Oceanographic and Meteorological Laboratory, showed that the ocean surface cooling in HWRF is too small. The DTC worked with the NOAA Environmental Modeling Center and oceanographers from the University of Rhode Island to formulate a test in which the momentum flux in the ocean model was altered to be more physically consistent. The figure below shows the mean intensity error as a function of lead time for 2012. The black curve is the control and the red curve is the forecast with modified fluxes with 95% confidence intervals.


Results aggregated over all 2012 Atlantic storms showed the more physical flux reduced the 5-kt positive intensity bias of the operational model to near-zero. This change has been incorporated by EMC into the 2013 HWRF baseline, and is expected to be adopted operationally for the 2013 hurricane season.

Contributed by Ligia Bernardet


Did you know?


For several winter seasons, the DTC has worked with the Hydrometeorology Testbed (HMT) to develop effective verification techniques for ensemble forecasts of heavy winter precipitation associated with atmospheric rivers in California. For example, the performance diagram below displays the impact of model resolution. See additional HMT information and links on the DTC website. See http://www.dtcenter. org/eval/hmt/2012/.


PROUD Awards

Man Zhang, Research Scientist II CU/CIRES and NOAA GSL |

Man Zhang works for CU/CIRES at NOAA GSL and contributes to three DTC projects: Testing and Evaluation of Unified Forecast System (UFS) Physics for Operations, Toward a Unified Physics Package for the UFS Applications, and CCPP Software Support & Community Engagement.

Man has gone above and beyond the call of duty to mentor a student during the Summer of 2022. It all started when she wrote about an idea for a short project, which caught the eye of CU Denver undergraduate student Jessica Paredes Saltijeral, a sophomore pursuing a degree in physics. Man helped Jessica broaden her understanding of numerical weather prediction models, observations of the Earth System, and forecast verification. Given the virtual nature of the internship, as dictated by the COVID-19 pandemic, Man fostered close continuity with Jessica via remote collaboration tools such as Google Meet and Drive. They collaborated on comparisons of model forecasts against satellite observations. This involved physics testing for the GFS/GEFS, relevant for the project Testing and Evaluation of UFS Physics for Operations.  Jessica presented their results at a mini conference organized by CU/CIRES, the entity that sponsored the internship. They also prepared an abstract that was accepted for the AMS Student Conference in Denver, CO in 2023. Throughout this partnership, Man generously shared her expertise, thereby making a profound difference in the career (and life) of a young scientist. The experience may have been just as rewarding for Man, as evidenced by her willingness to take a new student in 2023!

Man achieved a number of additional noteworthy accomplishments in the last year. She assumed the leadership of two DTC activities (Testing and Evaluation of UFS Physics for Operations and Toward a Unified Physics Package for the UFS Applications), was a member of the DTC retreat committee, was an organizer of the CU/CIRES Rendezvous, and was promoted to CU/CIRES supervisor.

Man has made a powerful difference in a new scientist, all while taking on new roles and responsibilities in her everyday projects. Her hard work, extensive knowledge, and overall excellence has made a significant impact in the research community and the people she works with. We are very fortunate to have her in the DTC!

Man Zhang, Research Scientist II CU/CIRES and NOAA GSL