Eugenia Kalnay
Distinguished University Professor

Prior to her coming to UMD, Eugenia Kalnay was Branch Head at NASA Goddard, and later the Director of the Environmental Modeling Center (EMC, ex Development Division) of the National Centers for Environmental Prediction (NCEP, ex NMC), National Weather Service (NWS) from 1987 to 1997. During those ten years there were major improvements in the NWS models' forecast skill. Many successful projects such as the 60+years NCEP/NCAR Reanalysis (the paper on this Reanalysis has been cited over 10,000 times), seasonal and interannual dynamical predictions, the first operational ensemble forecasting, 3-D and 4-D variational data assimilation, advanced quality control, and coastal ocean forecasting. EMC became a pioneer in both the fundamental science and the practical applications of numerical weather prediction.

Current research interests of Dr. Kalnay are in data assimilation, numerical weather prediction, data assimilation, predictability and ensemble forecasting, coupled ocean-atmosphere modeling and climate change. Zoltan Toth and Eugenia Kalnay introduced the breeding method for ensemble forecasting. She is also the author (with Ross Hoffman and Wesley Ebisuzaki) of other widely used ensemble methods known as Lagged Averaged Forecasting and Scaled LAF. Her book, Atmospheric Modeling, Data Assimilation and Predictability (Cambridge University Press, 2003) sold out within a year, is now on its fifth printing and was published in Chinese (2005) and in Korean (2012). A second edition is in preparation. She has received numerous awards, including the 2009 IMO Prize of the World Meteorological Organization.

Work at UMD/AOSC

She worked with Drs.Shu-Chih Yang and Ming Cai on ensemble and data assimilation methods on coupled ocean-atmosphere models using breeding (Cai et al, 2003, Yang et al, 2005, 2006, 2008, 2009), on the one and two-way interaction of the ocean and the atmosphere (Pena et al., 2003, Pena and Kalnay, 2004). Kalnay and Cai (2003) proposed a method (Observation minus Reanalysis trends, OMR) to estimate impact of land-cover and land-use change in climate change. The OMR paper was selected by Discovery Magazine as one of the top 100 science news of the year, and many papers have since used OMR to conclude that Green is cool.

E. Kalnay co-founded with J. Yorke the Weather/Chaos Group at UMCP, which discovered the presence of low dimensionality in unstable regions of the atmosphere detected with breeding (Patil et al, 2002) and applied this result to develop the Local Ensemble Kalman Filter (Ott et al. 2002, 2004), the Local Ensemble Transform Kalman Filter (Hunt et al., 2007), and its extension to 4 dimensions (Hunt et al., 2004). See papers and publications for new applications of the LETKF.  She has also published papers on atmospheric dynamics and convection, use of satellite data, numerical methods, and the atmosphere of Venus. More than a dozen doctoral theses have been completed in this project including former students of Eugenia (DJ Patil, Chris Danforth, Malaquias Pena, Shu-Chih Yang, Takemasa Miyoshi, Pablo Grumman, Matt Hoffman, Hong Li, Junjie Liu, Ji-Sun Kang). Recent students' work include Steve Greybush (data assimilation for Mars, localization and stability  in EnKF), Yan Zhou (estimation and correction of model bias in reanalysis), Javier Amezcua (RAW method, continuous EnKF), Steve Penny (LETKF applied to ocean data assimilation), Tamara Singleton (data assimilation in coupled systems), Adrienne Norwood (Lyapunov Vectors), Safa Motesharrei (Population and Climate Change), Yongjing Zhao (rogue waves, Mars), Guo-Yuan Lien (effective assimilation of precipitation. With Inez Fung, Junjie Liu and Ji-Sun Kang she developed a system to estimate surface carbon fluxes from the simultaneous assimilation of atmospheric variables and CO2 concentration. With Zhao-xia Pu and Seon Ki Park, she introduced the quasi-inverse method of backward integration of atmospheric models and novel applications to targeted observations and data assimilation.

Awards

  • WMO/IMO Prize for 2009, see talk Population and Climate Change: A Proposal (also in Spanish)
  • Member of the National Academy of Engineering (1996)
  • Foreign Member of the Academia Europaea (2000)
  • Distinguished University Professor, UMD (2001)
  • Eugenia Brin Professor in Data Assimilation (2008)
  • Doctor Honoris Causa, University of Buenos Aires (2008)
  • Corresponding member of the Argentine National Academy of Physical Sciences (2003)
  • Fellow of AGU (2005), AAAS (2006), AMS (1983)
  • UMD-wide Kirwan Award (2006)
  • Robert E. Lowry Chair, School of Meteorology, U. of Oklahoma (1998)
  • NASA medal for Exceptional Scientific Achievement (1981)
  • Two Department of Commerce Gold and one Silver Medal
  • Discovery Magazine selected her Nature paper as a top 100 science news of 2003 (see feature in International Association for Urban Climate newsletter)
  • The Reanalysis paper of 1996 is the most cited paper in all geosciences (more that 10 thousand citations)
  • Lorenz AGU 2012 Lecture

Publications

Seminars and Presentations

Student Dissertations

  • Pablo Grunmann Variational Data Assimilation of Soil Moisture Information
  • Shannon Sterling The Impact of Anthropogenic Global Land Cover Transformation on the Land-Atmosphere Fluxes of the Water
  • Shu-ChihYang Bred Vectors in the NASA NSIPP Global Coupled Model and their Application to Coupled Ensemble Predictions and Data Assimilation
  • Takemasa Miyoshi Ensemble Kalman Filter Experiments with a Primitive-Equation GLobal Model"
  • Chris Danforth Making Forecasts for Chaotic Processes in the Presence of Model Error
  • Hong Li Simultaneous estimation of inflation and observational errors
  • Junji Liu Adaptive obs, obs sensitivity, obs impact w/o adjoint, and assimilation of humidity
  • Matt Hoffman Ensemble Data Assilimation and Breeding in the Ocean, Chesapeake Bay, and Mars
  • Ji-Sun Kang Carbon Cycle Data Assimilation Using a Coupled Atmosphere-Vegetation Model and the Local Ensemble Transform Kalman Filter

Courses (syllabus, notes and required readings)