Greater Sacramento
I grew up on a farm on the outskirts of Sacramento, California. I greatly disliked school but loved the outdoors. I was not a good student. That changed when I had key teachers in high school that introduced me to algebra, geometry and chemistry. Through their teaching, support of my mother, and hard work, I was the first person in my family to go to college. Mentorship has been a key factor in my career, starting back in high school and later when I was introduced to the challenging and demanding work of research science through my Ph.D. advisor at the University of Oklahoma, Yoshi Sasaki. I co-developed the science mentorship program at the National Severe Storms Laboratory in 1990 with then-director Robert Maddox when I was Director of Meteorological Research. The program developed wings and is still growing strong. A relatively large number of students in the program are now researchers and professors of meteorology and mathematics. I have been a Ph.D. advisor for ten students and have taught many different courses in science. I see potential in every student and want to "encourage, not discourage" (credit for quote from Verner Suomi, former director of SSEC). I have gotten more than a few notes from former students who told me that when they struggled through their programs, I gave them tools to overcome their difficulties and succeed. I am a scientist with experience in seismology, meteorology, and oceanography. I have been a scientist in private industry (Shell Oil Company), operational weather prediction (National Meteorological Center (NMC) and Fleet Numerical Weather Center, U.S. Navy), Tenured Professor of Meteorology (University of Illinois, Champaign-Urbana), and a federal scientist at the Space, Science, and Engineering Laboratory (SSEC). I am a lead author of one book and co-author of another book in dynamic data assimilation (Cambridge University Press and Springer, respectively), and a lead author in a history of science book published by the American Meteorological Society. I have been an author and co-author of over 150 peer reviewed published articles in my career, including 30 peer reviewed history of science publications. Avocations: Art, drawing/watercolor, sports (participant and observer), short story writing.
Research Areas: Severe Storm Predictability Dynamic Data Assimilation Synoptic Meteorology History of Science
Data Assimilator for Satellite Meteorology My role at SSEC centered on development of a variational data assimilation method for analyzing upper-air observations from satellites—specifically observations collected by the VAS instrument. The VISSR Atmospheric Sounder (VAS) Project In the late-1970s, Vern Suomi and collaborators designed a satellite instrument package that could follow weather visually and collect quantitative data simultaneously from geostationary altitude. JML was hired to develop a variational data assimilation system that could process the VAS data and produce meteorological fields with high resolution in space and time (horizontal resolution of 50 km and time resolution of 3 hours). The Adjoint Data Assimilation Method To accommodate the large number of observations from VAS and the associated production of meteorological analyses on small scale in space and time, a new variational data assimilation strategy was needed that differed from the scheme developed at FNWC ten years earlier. Speed-up of the optimization process (fitting observations to model in the least squares context) was the critical element. After struggling for about a year and a half on this challenging problem, with a team of excellent doctoral students and post-doctoral scientists (a total of four young scientists), a breakthrough took place. JML became aware of a new optimization strategy developed by control theorists in France (called the adjoint method because the process used a set of equations that were adjoint to the governing forecast equations). Colleagues Francois LeDimet and Olivier Talagrand presented the theory to JML. We took the theory, giving credit to these Frenchmen, and implemented it on the VAS data under the constraints of vorticity conservation. The key publication appeared in 1985: Lewis, J. M., and J. C. Derber, 1985: The use of adjoint equations to solve a variational adjustment problem. Tellus, 37A, 309 – 322.
Academic Responsibilities Helped develop the fledging graduate program in the Laboratory for Atmospheric Research—a laboratory attached to the physics department at Univ. of Illinois (C-U). Notably, developed the synoptic meteorology component of the program (taught the synoptic course and laboratory from 1973 until 1980). I introduced a general education course into the university curriculum titled Weather Forecasting that generated plenteous revenue for the program as a result of attracting a large number of students to the course every year. It remains a stalwart of the program. I was also the initial chair of the Graduate Studies Committee and served as Seminar Organizer for several years. Research Introduced severe storm meteorology research into the program through two NSF research grants from 1974 through 1978. Two doctoral students and three master’s degree students were graduated under his guidance with sponsorship from the NSF grants. Key Publications: Lewis, J., Y. Ogura, and L. Gidel, 1974: Large-scale influences upon the generation of a mesoscale disturbance. Mon. Wea. Rev., 102, 545 – 560. Through use of a mesoscale network of upper-air observations, the precise location of cumulus convection onset could be determined from the evolution of thermodynamic and kinematic structure in the lower troposphere. Lewis, J. M., 1975: Test of the Ogura-Cho model on a pre-frontal squall line case. Mon. Wea. Rev., 103, 764 – 778. The parameterization of a squall line’s cloud structure (ensemble of cloud heights) was generated through use of a convection model that was verified against the 3-D cloud-height distribution obtained from radar data. The model performed admirably.
Developed and implemented the first variational data assimilation system at an operational weather prediction center (the U. S. Navy’s Fleet Numerical Weather Central). The analysis was programmed on the CDC 6600 (fastest digital computer in the world at that time—early 1970s) and used only 30 minutes of clock time to generate the analyses. This variational method produced surface and upper-air analyses over the globe every 6 hours between 1972 (year of commission) and the early-1990s (when it was decommissioned). Foundation of the operational analysis was based on Yoshi Sasaki’s classic work in variational mechanics and its practical implementation as found in JML’s Ph. D. dissertation that was completed under the guidance of Professor Sasaki: Lewis, J. M., 1969: Numerical Variational Objective Analysis of the Boundary Layer in Conjunction with Squall Line Formation. Ph. D. Dissertation. University of Oklahoma, 63 pp. Primary publication on the operational data assimilation method: Lewis, J. M., 1972: An operational upper-air analysis using the variational method. Tellus, 24, 514 -530. The variational method of data assimilation (3D-Var and 4D-Var) is central to assimilation-prediction strategies at weather prediction centers worldwide as reviewed in: Lewis, J. M., and S. Lakshmivarahan, 2008: Sasaki’s pivotal contribution: Calculus of variations applied to weather map analysis. Mon. Wea. Rev., 136, 3553 – 3567.