Having joined NCICS in 2010, Dr. Jessica Matthews is a member of the NCICS leadership team, supervising roughly a third of the institute staff.
In general, Dr. Matthews’ research interests focus on models of physical and biological phenomenon, the underlying mathematical principles, and the associated uncertainty quantification methodologies. Her work at the institute has spanned such topics as developing machine learning algorithms to retrieve satellite-based observations, adapting large scale processing of geostationary satellite data to produce a land surface albedo climate data record, improving the NOAA US Billion Dollar Weather and Climate Disaster product with the addition of confidence intervals, modeling vegetation observations to analyze phenological trends, and evaluating statistical models that project when the Arctic will be ice-free in summer.
Dr. Matthews earned a PhD in applied mathematics from North Carolina State University in 2010. Her dissertation research examined water stress conditioning and sensitivity analysis of photosynthesis and stomatal conductance models. As an undergraduate, she participated in a cooperative education experience at NASA Goddard Space Flight Center in Greenbelt, MD, where she supported efforts of the Earth Observing System (EOS). Following completion of her master’s degree, from 2004 through 2010 she worked as a biomathematician for SRA International, Inc.
Cheng, S., B.A. Konomi, J.L. Matthews, G. Karagiannis, and E. Kang, 2021: Hierarchical Bayesian nearest neighbor co-kriging gaussian process models; An application to intersatellite calibration. Spatial Statistics, In press.
Matthews, J. L., G. Peng, W. N. Meier, and O. Brown, 2020: Sensitivity of Arctic Sea Ice Extent to Sea Ice Concentration Threshold Choice and Its Implication to Ice Coverage Decadal Trends and Statistical Projections. Remote Sensing, 12, 807, https://doi.org/10.3390/rs12050807.
Peng, G., J. L. Matthews, M. Wang, R. Vose, and L. Sun, 2020: What Do Global Climate Models Tell Us about Future Arctic Sea Ice Coverage Changes? Climate, 8 (1). http://dx.doi.org/10.3390/cli8010015
Runkle, J. D., M. M. Sugg, R. D. Leeper, Y. Rao, J. L. Mathews, and J. J. Rennie, 2020: Short-term effects of weather parameters on COVID-19 morbidity in select US cities. Science of The Total Environment, 140093. http://dx.doi.org/10.1016/j.scitotenv.2020.140093
Matthews, J. L., and L. Shi, 2019: Intercomparisons of long-term atmospheric temperature and humidity profile retrievals. Remote Sensing, 11, 853. http://dx.doi.org/10.3390/rs11070853
Moroni, D.F., H. Ramapriyan, G. Peng, J. Hobbs, J. Goldstein, R. Downs, R. Wolfe, C.-L. Shie, C.J. Merchant, M. Bourassa, J.L. Matthews, P. Cornillon, L. Bastin, K. Kehoe, B. Smith, J.L. Privette, A.C. Subramanian, O. Brown, and I. Ivánová, 2019: Understanding the Various Perspectives of Earth Science Observational Data Uncertainty. Figshare. http://dx.doi.org/10.6084/m9.figshare.10271450.v1
Peng, G., J. Matthews, and J. Yu, 2018: Sensitivity analysis of Arctic sea ice extent trends and statistical projections using satellite data. Remote Sensing, 10, 230. http://dx.doi.org/doi:10.3390/rs10020230
Claverie, M., J. L. Matthews, E. F. Vermote, and C. O. Justice, 2016: A 30+ year AVHRR LAI and FAPAR Climate Data Record: Algorithm description and validation. Remote Sensing, 8, 263. http://dx.doi.org/10.3390/rs8030263
Knapp, K. R., J. L. Matthews, J. P. Kossin, and C. C. Hennon, 2016: Identification of tropical cyclone storm types using crowdsourcing. Monthly Weather Review, 144, 3783-3798. http://dx.doi.org/10.1175/MWR-D-16-0022.1
Peng, G., L. Shi, S. T. Stegall, J. L. Matthews, and C. W. Fairall, 2016: An evaluation of HIRS near-surface air temperature product in the Arctic with SHEBA data. Journal of Atmospheric and Oceanic Technology, 33, 453-460. http://dx.doi.org/10.1175/JTECH-D-15-0217.1
Shi, L., J. L. Matthews, S.-p. Ho, Q. Yang, and J. J. Bates, 2016: Algorithm development of temperature and humidity profile retrievals for long-term HIRS observations. Remote Sensing, 8, 280. http://dx.doi.org/10.3390/rs8040280
Smith, A. B., and J. L. Matthews, 2015: Quantifying uncertainty and variable sensitivity within the US billion-dollar weather and climate disaster cost estimates. Natural Hazards, 77, 1829-1851. http://dx.doi.org/10.1007/s11069-015-1678-x
Lattanzio. A., J. Schulz, J. L. Matthews, A. Okuyama, B. Theodore, J. J. Bates, K. R. Knapp, Y. Kosaka, L. Schuller, 2013: Land Surface Albedo from Geostationary Satellites: a multi-agency collaboration within SCOPE-CM. Bulletin of the American Meteorological Society, 94, 205-214. http://doi.org/10.1175/BAMS-D-11-00230.1
Matthews, J. L., E. Mannshardt, and P. Gremaud, 2013: Uncertainty Quantification for Climate Observations, Bulletin of the American Meteorological Society, 94, ES21-ES25. http://doi.org/10.1175/BAMS-D-12-00042.1
Matthews, J. L., E. L. Fiscus, R. C. Smith, and J. L. Heitman, 2013: Quantifying plant age and available water effects on soybean leaf conductance. Agronomy Journal, 105, 28-36. http://dx.doi.org/10.2134/agronj2012.0263
Matthews, J. L., I. R. Schultz, M. R. Easterling, and R. L. Melnick, 2013: Physiologically based pharmacokinetic modeling of dibromoacetic acid in F344 rats. Journal of Toxicology and Applied Pharmacology, 24, 196-207. http://doi.org/10.1016/j.taap.2009.12.033
Matthews, J. L., R. C. Smith, and E. L. Fiscus, 2013: Confidence interval estimation for an empirical model quantifying the effect of soil moisture and plant development on soybean (Glycine max (L.) Merr.) leaf conductance. International Journal of Pure and Applied Mathematics, 83, 439-464. http://doi.org/10.12732/ijpam.v83i3.6
Matthews, J. L., E. K. Lada, L. M. Weiland, R. C. Smith and D. J. Leo, 2006: Monte Carlo simulation of a solvated ionic polymer with cluster morphology. Smart Materials and Structure, 15, 187-199. http://doi.org/10.1088/0964-1726/15/1/048
Peng, G., M. Steele, A. Bliss, W. Meier, J. Matthews, M. Wang, and S. Dickinson, 2019: Characterizing Arctic Sea Ice Coverage Variability. Barcelona Supercomputing Center and Copernicus Data Store, Barcelona, Spain. September 23, 2019.
Prat, O. P., R. D. Leeper, J. L. Matthews, B. R. Nelson, J. Adams, and S. Ansari, 2019: Using Remotely Sensed Precipitation Information and Vegetation Observations for Early Drought Detection and Near-Real Time Monitoring on a Global Scale. AMS 99th Annual Meeting, Phoenix, AZ, January 9, 2019.
Prat, O. P., R. Leeper, J. L. Matthews, B. R. Nelson, S. Ansari, and J. Adams, 2018: Toward Earlier Drought Detection Using Remotely Sensed Precipitation Information and Vegetation Observations from the Reference Environmental Data Record (REDR) Program. American Geophysical Union Fall Meeting, Washington, DC, December 13, 2018.
Matthews, J. L., and L. Shi, 2018: Long-term HIRS-based Temperature and Humidity Profiles. American Geophysical Union Fall Meeting, Washington, DC, December 12, 2018.
Matthews, J., 2018: Weather and Satellites. Leicester Elementary School, Leicester, NC, November 8, 2018.
Matthews, J., and J. J. Rennie, 2018: Embracing Big Data + Cloud Computing. The Collider, Asheville, NC, October 2, 2018
Matthews, J., and J. J. Rennie, 2018: The process of moving 2 applications to the cloud. NCEI Science Council meeting, Asheville, NC, August 9, 2018.
Matthews, J. L., 2018: Optimization Methods in Remote Sensing. SAMSI Climate Transition Workshop, Research Triangle Park, NC, May 14, 2018.
Matthews, J. L., 2018: Remotely sensed retrievals of atmospheric temperature and humidity profiles. University of Minnesota Institute for Research on Statistics and its Applications (IRSA) Annual Conference, Minneapolis, MN, May 3, 2018.
Matthews, J. L., 2018: Remotely sensed retrievals of atmospheric temperature and humidity profiles. NOAA Cooperative Institute for Climate and Satellites Executive Board Meeting. College Park, MD, April 30, 2018.
Matthews, J. L., 2018: Mathematics in Climate Science. University of Tennessee Mathematics Department Undergraduate Math Conference, Knoxville, TN, April 21, 2018.
Matthews, J. L., 2018: Optimization methods in Remote Sensing. Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems Workshop, Pasadena, CA, February 12, 2018.
Matthews, J. L., 2018: Earth Science Data Uncertainty from the Application Perspective. Earth Science Information Partner (ESIP) Winter Meeting, Bethesda, MD, January 11, 2018.
Matthews, J., 2017: What to Expect in a Nonacademic Career, Association for Women in Mathematics (AWM), Clemson University, Clemson, SC, November 20, 2017.
Matthews, J. L., 2017: Fusing Data from Multiple Remote Sensing Instruments. Joint Statistical Meeting, Baltimore, MD, July 30, 2017.
Matthews, J. L., 2017: Next-generation Environmental Intelligence for the Solar Industry. The Climate Resilient Grid: A Forum on Energy, Climate, and the Grid, Asheville, NC, June 15, 2017.
Matthews, J. L. and L. Shi, 2016: Long-term HIRS-based temperature and humidity proles. CICS Science Conference, College Park, MD, December 1, 2016.
Matthews, J. L., 2016: Long-term HIRS-based Temperature and Humidity Profiles, CICS Science Conference, College Park, MD November 29, 2016.
Shi, L., J.L. Matthews, S. Stegall, and G. Peng, 2016: A long-term global dataset of temperature and humidity profiles from HIRS. 2016 CLIVAR Open Science Conference, 19-23 September 2016, Qingdao, Shangdong, China.
Matthews, J. L., 2016: Research applications at the National Centers for Environmental Information. Clemson University Mathematical Sciences Department Colloquia, Clemson, SC, September 16, 2016.
Knapp, K.R., and J. L. Matthews, 2016: Reprocessing GOES GVAR data. AMS 21st Conference on Satellite Meteorology, Madison, WI, August 14-19, 2016.
Matthews, J. L., 2016: Research applications at the National Centers for Environmental Information. Environmental Protection Agency, Research Triangle Park, NC, July 20, 2016.
Matthews, J. L., 2016: What to expect in a non-academic career. SAMSI's Workshop for Women in Math Sciences, Durham, NC, April 6-8, 2016.
Shi, L., J. L. Matthews, S. Stegall, and G. Peng, 2015: Deriving long-term global dataset of temperature and humidity profiles from HIRS. The 20th International TOVS Study Conference, Lake Geneva, WI, October 28-November 3, 2015.
Lattanzio, A., J. Matthews, M. Takahasi, K. Knapp, J. Schulz, R. Roebeling, R. Stoeckli, 2014: 30 years of land surface albedo from GEO satellites. QA4ECV Review Meeting, Mainz, Germany, February 5-6, 2015.
Shi, L., J. L. Matthews, Q. Yang, S.-P. Ho, 2015: HIRS-Derived temperature and humidity profiles and comparisons with GPS R0 derived profiles, American Meteorological Society Annual Meeting, Phoenix, AZ, January 7, 2015.
Matthews, J. L., 2015: Land surface albedo from a constellation of geostationary satellites compared and fused with polar-orbiting data. American Meteorological Society Annual Meeting, Phoenix, AZ, January 5, 2015.
Matthews, J. L., 2014: Research applications at the National Climatic Data Center, North Carolina State University Mathematics Department First Year seminar, Raleigh, NC, November 14, 2014.
Lattanzio, A., J. Matthews, M. Takahasi, K. Knapp, J. Schulz, R. Roebeling, R. Stoeckli, 2014: 30 years of land surface albedo from GEO satellites: Status of the SCOPE-CM LAGS Project. The Climate Symposium 2014, Darmstadt, Germany, October 13-17, 2014.
Matthews, J. L. 2014: Land surface albedo climate data record from a constellation of geostationary satellites. EUMETSAT visiting scientist seminar, Darmstadt, Germany, October 4, 2014.