Dr. Matthews earned a PhD in applied mathematics from North Carolina State University, Raleigh, NC, 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., primarily modeling agents under study by the National Toxicology Program.
Dr. Matthews joined NCICS as a Postdoctoral Research Associate in 2010 and moved to a Research Scholar position in 2015. At NCICS she acts as transition manager for a land surface albedo climate data record based on geostationary satellite data as part of an international effort with EUMETSAT and JMA. As the designated subject matter expert for vegetation climate data records, Dr. Matthews pursues innovative applications of these essential climate variables, such as monitoring drought and incidence of vector-borne disease. Additionally, she supports research in the retrieval of atmospheric temperature and humidity profile data from long-term HIRS observations. Her research interests focus on models of physical and biological phenomenon, the underlying mathematical principles, and the associated uncertainty quantification methodologies.
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
Shi, L., J. L. Matthews, S. Stegall, and G. Peng, 2016: Poster, A long-term global dataset of temperature and humidity profiles from HIRS. 2016 CLIVAR Open Science Conference, Qingdao, Shangdong, China, 19-23 September 2016.
Matthews, J. L., 2015: Land surface albedo from a constellation of geostationary satellites compared and fused with polar-orbiting data. Annual Meeting of the American Meterological Society, Phoenix, AZ, 4-8 January 2015.
Matthews, J. L., L. Shi, Q. Yang, and S.-P. Ho., 2015: HIRS-Derived temperature and humidity profiles and comparisons with GPS R0 derived profiles. Annual Meeting of the American Meteorological Society, Phoenix, AZ, 4-8 January 2015.
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, Wisconsin, 28 October - 3 November 2015.
Lattanzio, A., J. Matthews, M. Takahasi, K. Knapp, J. Schulz, R. Roebeling, and R. Stoeckli, 2014: 30 years of land surface albedo from GEO satellites. QA4ECV Review Meeting, Mainz, Germany, 5-6 February, 2015.
Matthews, J., A. Lattanzio, M. Takahasi, K. Knapp, J. Schulz, R. Roebeling, and 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, 13-17 October 2014.
Matthews, J. L., 2014: Land surface albedo climate data record from a constellation of geostationary satellites. EUMETSAT visiting scientist seminar, Darmstadt, Germany, 4 October 2014.
Matthews, J. L., 2014: Research applications at the National Climatic Data Center. North Carolina State University Mathematics Department First Year seminar, Raleigh, NC, 14 November 2014.