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GFDL Statistical Downscaling Research Team Members & Collaborators


NOAA GFDL federal employees:

[Keith Dixon]
Keith Dixon, NOAA/GFDL – Team Lead
Keith’s research focuses on the use of state-of-the-art computer models to simulate the global climate and connecting those model results to applications relevant to decision-making. His interest in statistical downscaling stems from a desire to assess the capabilities of climate models and downscaling methods. Keith also is active in the science communications arena, seeking to enhance the exchange of scientifically credible information between the realms of large-scale climate research and societally relevant local-scale impacts and applications.


UCAR contract staff:

[Dennis Adams-Smith]
Dennis Adams-Smith, UCAR at NOAA/GFDL
Dennis joined the ESD team in June 2016 as a data analyst and programmer. He brings in-depth knowledge of statistical methods, R programming and climate data. Dennis is supporting the creation of an expanded and improved framework both for downscaling climate model output and for analyzing the results in a rigorous manner that can be readily communicated to users of statistically downscaled climate products.

SAIC contract staff:

[Nicole Zenes]
Nicole Zenes, SAIC at NOAA/GFDL
Nickie, who received her Ph.D. from the University of Utah and her undergraduate degree from Princeton University, joined the ESD team in July 2023. In her scientific programmer role she makes use of her R programming skills and research experience to advance the team’s capabilities to develop well-designed experiments and conduct appropriate analyses reliably.

Princeton University CIMES:

Data Specialist:

[Serguei Nikonov photo]

Serguei Nikonov, Princeton University’s Cooperative Institute for Modeling the Earth System (CIMES)

Serguei Nikonov joined our team during 2023 after several years working with GFDL’s Data Portal Team. Our ESD team will benefit from Serguei’s skills and experiences working with large numbers of large climate model data sets, including assuring that files meet standards so as to maximiize interoperability with the team’s software programs.


NOAA GFDL federal collaborator:

[John Lanzante]
John Lanzante, NOAA/GFDL
John is a member of GFDL’s Weather and Climate Dynamics Division. His work involves the use of statistics and data analysis techniques as applied to both observed and model (GCM) generated data. Recently, John has been focusing on the representation of climate extremes (i.e., the tails of the distribution) in bias corrected and statistical downscaled data products generated by different techniques.


Other Internal Research Collaborators at NOAA-GFDL & Princeton

MARINE ECOSYSTEMS FOCUS:
[MED icon]

CURRENT:
Charles Stock, NOAA/GFDL
Andrew Ross NOAA/GFDL
Liz Drenkard, NOAA/GFDL
Vimal Koul Princeton Univ/CIMES
Vincent Saba, NOAA Northeast Fisheries Science Center

Members of GFDL’s ESD Team collaborate with Charlie Stock and others in GFDL’s Marine Ecosystems and Downscaling Division on the bias correction and statistical downscaling of surface climate variables for use in marine resource impacts applications.  To date, this work has focused on multi-decadal projections as well as sub-seasonal to seasonal forecasts.

♦ Drenkard, E. J., C. Stock, A. C. Ross, K. W. Dixon, and Coauthors, 2021: Next-generation regional ocean projections for living marine resource management in a changing climate. ICES Journal of Marine Science, fsab100, https://doi.org/10.1093/icesjms/fsab100.
♦ Ross, A. C., C. A. Stock, D. Adams-Smith, K. W. Dixon, K. L. Findell, V. S. Saba, and B. Vogt, 2020: Estuarine Forecasts at Daily Weather to Subseasonal Time Scales. Earth and Space Science, doi:  10.1029/2020EA001179.
♦ Muhling, B. A., C. F. Gaitán, C. A. Stock, V. S. Saba, D. Tommasi, and K. W. Dixon, 2017: Potential Salinity and Temperature Futures for the Chesapeake Bay Using a Statistical Downscaling Spatial Disaggregation Framework. Estuaries and Coasts, doi:10.1007/s12237-017-0280-8.
♦ Muhling, B. A., J. Jacobs, C. A. Stock, C. F. Gaitan, and V. S. Saba, 2017: Projections of the future occurrence, distribution, and seasonality of three Vibrio species in the Chesapeake Bay under a high-emission climate change scenario: Vibrio and Climate in the Chesapeake Bay. GeoHealth, doi:10.1002/2017GH000089.


Our Other Collaborators

[Ellen Mecray photo]

Ellen Mecray, NOAA Regional Climate Services Director, Eastern Region

Ellen focuses on how to make the climate data and information coming out of various parts of NOAA useful, useable, and used by a broad range of stakeholders. Ellen’s knowledge about what customers want from NOAA in terms of climate services, and her efforts to work within NOAA to figure out how best to be responsive to those needs, meshes with the aspect of the GFDL ESD Team’s research efforts that can promote better informed use of such data products in climate impacts studies. The use of downscaled climate projections for applied research into the effects of heat on human health is a topic of mutual interest.


[Hunter Jones]
Hunter Jones, NOAA/CPO
Hunter Jones is the program manager and lead of the Climate Program Office’s Extreme Heat Climate Risk Area. Hunter fosters and manages connections between scientists and stakeholders, with a very specific focus on climate change and the health risk of heat in urban environments.  He is a principal for the 2022 NOAA Urban Heat Island Campaigns – part of the National Integrated Heat Health Information System (NIHHIS).

[University of Oklahoma logo]

Adrienne Wootten, Research Scientist at The University of Oklahoma

Adrienne became the primary research point-person for OU-GFDL collaborative activities in January 2017 and we have continued to interact with her in her role at the South Central Climate Adaptation Science Center (SC-CASC). Adrienne is involved in the co-ordinated analysis of downscaled climate projections generated at GFDL, and in the conversion of knowledge developed from that research into products and guidance useful to researchers and the broader SC-CASC stakeholder community.

♦ Wootten, A. M., K. W. Dixon, D. Adams‐Smith, and R. A. McPherson, 2020: Statistically Downscaled Precipitation Sensitivity to Gridded Observation Data and Downscaling Technique. International Journal of Climatology, doi: 10.1002/joc.6716.