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Lisa Goddard

Research Scientist

ENSO, Climate Prediction Methodology, Near-Term Climate Change

228

61 Route 9W

Palisades, New York 10964

Phone: 845 680 4430

Fax: 845 680 4865

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Curriculum Vitae
IRI Publications
Profile

Background

Dr. Lisa Goddard is a research scientist at the International Research Institute for Climate and Society (IRI) and an adjunct associate professor within the Department of Earth and Environmental Sciences of Columbia University. She has been involved in El Nino and climate forecasting research and operations since the mid 1990s. She has extensive experience in forecasting methodology and has published papers on El Nino, seasonal climate forecasting and verification, and probabilistic climate change projections. Currently leading the IRI's effort on Near-Term Climate Change, Dr. Goddard oversees research and product development aimed at providing climate information at the 10-20 year horizon and how that low frequency variability and change interacts with the probabilistic risks and benefits of seasonal-to-interannual variability. Most of Dr. Goddard's research focuses on diagnosing and extracting meaningful information from climate models and available observations. She also developed and oversees a new national post-doctoral program, the Climate Prediction Applications Postdoctoral Program (CPAPP), which explicitly links recent climate PhDs with decision making institutions. In addition, Dr. Goddard sits on five scientific advisory panels and co-chairs two working groups.
Dr. Goddard holds a Ph.D. in atmospheric and oceanic sciences from Princeton University and a B.A. in physics from the University of California at Berkeley.

Research Interests

Dr. Goddard pursues several lines of research aimed at improving the quality and content of climate predictions. This goal is approached with a focus on climate diagnostics and predictability. Research areas include

  • Near-term climate change,

  • El Nino/La Nina and their impact on climate variability and predictability,

  • Methodologies for identifying the relative importance of regional SSTs to regional climate variability,

  • Assessment of climate prediction tools, and

  • Strategies for advancing research, development and implementation of climate forecasts.

Dr. Goddard also contributes to the real time production of IRI's ENSO outlook and seasonal climate forecasts.



Published Papers

Barnston, A.G., S. Li, S.J. Mason, D.G. DeWitt, L. Goddard, X. Gong, 2010. Verification of the First 11 Years of IRI's Seasonal Climate Forecasts. J. App. Met. and Clim., 49: 493-520.

Goddard, L., D.G. DeWitt, and R.W. Reynolds, 2009. Practical implications of uncertainties in observed SSTs. Geophys. Res. Lett., 36, L09710, doi:10.1029/2009GL037703.

Goddard, L., W. Baethgen, B. Kirtman, and G. Meehl, 2009. The Urgent Need for Improved Models and Predictions. EOS, 90: 343.

Meehl, G.A., L. Goddard, J.Murphy, R.J. Stouffer, G. Boer, G. Danabasoglu, K. Dixon, M.A. Giorgetta, A. Greene, E. Hawkins, G. Hegerl, D. Karoly, N. Keenlyside, M. Kimoto, B. Kirtman, A. Navarra, R. Pulwarty, D. Smith, D. Stammer and T. Stockdale, 2009. Decadal prediction: Can it be skillful?, Bull. Amer. Meteor. Soc., 90: 1467-1485.

Coelho, C.A.S and L. Goddard, 2009. El Nino-induced tropical droughts in climate change projections, J. Climate, 22: 6456-6476.

Ndiaye, O., L. Goddard, and M.N. Ward, 2008. Using regional wind fields to improve general circulation model forecasts of July-September Sahel rainfall. Int. J. Climatol. (published online in advance of print). DOI: 10.1002/joc.1767

Li, S., L. Goddard, and D. G. DeWitt, 2008. Predictive skill of AGCM seasonal climate forecasts subject to different SST prediction methodologies, J. Climate, 21: 2169-2186.

Mason, S. J., J. S. Galpin, L. Goddard, N. E. Graham, and B. Rajartnam. 2007. Conditional exceedence probabilities. Mon. Wea. Rev., Mon. Wea. Rev., 135:363-372.

Goddard, L., A. Kumar, A. G. Barnston and M. P. Hoerling. 2006. Diagnosis of anomalous winter temperatures over the eastern United States during the 2002/03 El Nino. J. Climate, 19: 5624-5636.

Goddard, L. and M. Dilley, 2006. Reply to Comments on "El Nino: Catastrophe or Opportunity". J. Climate, 19: 6443-6445.

Greene, A.M., L. Goddard, and U. Lall. 2006. Probabilistic multimodel regional temperature change projections. J. Climate, 19: 4326-4343.

Barnston, A.G., A. Kumar, L. Goddard, and M.P. Hoerling. 2005. Improving seasonal prediction practices through attribution of climate variability. Bull. Amer. Meteor. Soc., 86: 59-72.

Berri, G.J., Antico, P.L., and Goddard, L.. 2005. Evaluation of the Climate Outlook Forum seasonal precipitation forecasts of Southeast South America during 1998-2002. Int. J. Climatol., 25: 365-377.

Goddard, L. and M. Dilley. 2005. El Nino: Catastrophe or opportunity. J. Climate, 18: 651-665.

Landman, W. A., S. Botes, L. Goddard, and M. Shongwe. 2005. Assessing the predictability of extreme rainfall seasons over southern Africa. Geophys. Res. Lett., 32: L23819, doi:10.1029/2005GL023787

Landman, W. A. and L. Goddard. 2005. Predicting southern African summer rainfall using a combination of MOS and perfect prognosis. Geophys. Res. Lett., 32: L15809, doi:10.1029/2005GL022910.

Potgieter, A.B., Hammer, G.L., Meinke, H., Stone, R.C., and Goddard, L.. 2005. Spatial variability in impact on Australian wheat yield reveals three types of El Nino. J. Climate, 18: 1566-1574.

Tippett, M.K., Goddard, L., and Barnston, A.G. 2005. Statistical-dynamical seasonal forecasts of Central Southwest Asia winter preicipitation, J. Climate, 18, 1831-1843.

Kumar, A., F. Yang, L. Goddard, and S. Schubert. 2004. Differing trends in the tropical surface temperatures and precipitation over land and oceans. J. Climate, 17: 653-664.

Robertson, A.W., Zebiak, S.E., U. Lall, and L. Goddard. 2004. Optimal combination of multiple atmospheric GCM ensembles for seasonal prediction. Mon. Wea. Rev., 132: 2732-2744, DOI: 10.1175/MWR2818.1.

Barnston, A.G., S.J. Mason, L. Goddard, D. G. DeWitt, and S. E. Zebiak. 2003. Increased automation and use of multi-model ensembling in seasonal climate forecasting at the IRI. Bull. Amer. Meteor. Soc., 84: 1783-1796.

Goddard, L., A. G. Barnston and S.J. Mason. 2003. Evaluation of the IRI's "Net Assessment" seasonal climate forecasts: 1997-2001. Bull. Amer. Meteor. Soc., 84: 1761-1781.

Goddard, L. and S.J. Mason, 2002. Sensitivity of seasonal climate forecasts to persisted SST anomalies. Climate Dynamics, 19:619-632, DOI 10.1007/s00382-002-0251-y. (PDF version), (HTML version)

Landman, W.A. and L. Goddard. 2002. Statistical recalibration of GCM forecats over southern Africa using model output statistics. J. Climate, 15: 2038-2055.

Goddard, L., S. J. Mason, S. E. Zebiak, C. F. Ropelewski, R. Basher, and M. A. Cane. 2001. Current approaches to seasonal-to-interannual climate predictions. Int. J. Climatology, 21 (9): 1111-1152. (PDF version)

Mason, S.J. and L. Goddard, 2001. Probabilistic precipitation anomalies associated with ENSO. Bull. Amer. Met. Soc., 82: 619-638.

Gershunov, A., T.P. Barnett, D. Cayan, A. Tubbs, and L. Goddard, 2000. Predicting ENSO impacts on intraseasonal precipitation in California: The 1997-98 event. J. Hydrometeorology, 1: 201-210.

Goddard, L. and S. G. H. Philander, 2000. The energetics of El Nino and La Nina. J. Climate, 13: 1496-1516.

Kumar, A, A. G. Barnston, P. Peng, M.P. Hoerling, and L. Goddard, 2000. Changes in the spread of the variability of the seasonal mean atmospheric states associated with ENSO. J. Climate, 13: 3139-3151.

Peng, P., A. Kumar, A.G. Barnston, and L. Goddard, 2000. Simulation skills of the SST-forced global climate variability of the NCEP-MRF9 and the Scripps-MPI ECHAM3 models. J. Climate, 13: 3657-3679.

Goddard, L. and N. E. Graham, 1999. The importance of the Indian Ocean for simulating precipitation anomalies over eastern and southern Africa. J. Geophys. Res., 104: 19099-19116.

Mason, S. J., L. Goddard, N. E. Graham, E. Yulaeva, L. Sun, and P. A. Arkin, 1999. The IRI seasonal climate prediction system and the 1997/98 El Nino. Bull. Amer. Meteor. Soc., 80: 1853-1873.

Goddard, L. and N. E. Graham, 1997. El Nino the 1990s. J. Geophys. Res., 102: 10423-10436.



Published Papers - Not Peer Reviewed

Goddard, L., K. Redmond and M. Austin, 2007. Climate Prediction Applications Postdoctoral Program (CPAPP): An Experiment in Interfacing Climate and Society. U.S. CLIVAR Variations, Vol 5, No. 2, September 2007.

Goddard, L., A. Wood, N. Mantua and K. Jacobs, 2007. Decadal Climate Prediction: Learning from the Oceans, Solicited contribution for California Department of Water Resources publication on drought.

Goddard, L. and Martin P. Hoerling 2006. Practices for Seasonal-to-Interannual Climate Prediction, U.S. CLIVAR Variations, Fall 2006, Vol. 4. (Invited).

Goddard, L. and D.G. DeWitt, 2005. Seeking progress in El Nino Prediction, U.S. CLIVAR Variations, Winter 2005, Vol. 3. (Invited).

Goddard, L., S.J. Mason, and A.W. Robertson, 2005. Multi-model ensembling: Combining and refining, CLIVAR Exchanges, Jan 2005, No 32 (Vol. 10, No.1).



Submitted/In Press

Solomon, A., L. Goddard, A. Kumar, J. Carton, C. Deser, I. Fukumori, A. Greene, G. Hegerl, B. Kirtman, Y. Kushnir, M. Newman, D. Smith, D. Vimont, T. Delworth, J. Meehl, and T. Stockdale, 2010. Distinguishing the roles of natural and anthropogenically forced decadal climate variability: Implications for prediction. Bull. Amer. Meteor. Soc., Submitted.

Mehta, V., G. Meehl, L. Goddard, J. Knight, A. Kumar, M. Latif, T. Lee, A. Rosati, and D. Stammer, 2010. The Eighth Workshop on Decadal Climate Variability, Decadal Climate Predictability and Prediction: Where Are We?. Bull. Amer. Meteor. Soc., submitted.

Goddard, L., J. Murphy, T. Stockdale, C. Vera, J. Hurrell, B. Kirtman, 2010. Provision of Seasonal-to-Decadal Climate Information to Underpin Climate Services, Bull. Amer. Meteor. Soc., submitted.