Peer-reviewed publications
2024
[47] Zhang, L., Risser, M.D., Wehner, M.F., O'Brien, T.A. (2024) Explaining the unexplainable: leveraging extremal dependence to characterize the 2021 Pacific Northwest heatwave. Journal of Agricultural, Biological and Environmental Statistics, https://doi.org/10.1007/s13253-024-00636-8
[46] Rahimi, S., Huang, L., Goldenson, N., Risser, M.D., Feldman, D.R., Lebo, Z.J., Norris, J., Dennis, E., Thackeray, C., Hall, A. (2024) Understanding the Cascade: Removing GCM biases improves dynamically downscaled climate projections. Geophysical Research Letters, https://doi.org/10.1029/2023GL106264
[45] Risser, M.D., Rahimi, S., Goldenson, N., Hall, A., Lebo, Z.J., Feldman, D.R. (2024) Is bias correction in dynamical downscaling defensible? Geophysical Research Letters, https://doi.org/10.1029/2023GL105979
[44] Duan S., Ullrich, P.A., Risser, M.D., Rhoades, A.M. (2024) Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent over the Rocky Mountains. Water Resoures Research, https://doi.org/10.1029/2023WR035009
[43] Wehner, M.F., Duffy, M., Risser, M.D., Paciorek, C.J., Stone, D.A., Pall, P. (2024). On the uncertainty of long-period return values of extreme daily precipitation. Frontiers in Climate: Climate Monitoring, https://doi.org/10.3389/fclim.2024.1343072
[42] Noack, M.M., Luo, H., Risser, M.D. (2024) A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes. APL Machine Learning, https://doi.org/10.1063/5.0176963
[41] Risser, M.D., Collins, W.D., Wehner, M.F., O'Brien, T.A., Huang, H., Ullrich, P.A. (2024) Anthropogenic aerosols mask increases in US rainfall by greenhouse gases. Nature Communications, https://doi.org/10.1038/s41467-024-45504-8
2023
[40] Vishnu, S., Risser, M.D., O'Brien, T.A., Ullrich, P.A., Boos, W. (2023) Observed increase in the peak rain rates of monsoon depressions. npj Climate and Atmospheric Science, https://doi.org/10.1038/s41612-023-00436-w
[39] Longmate, J.M., Risser, M.D., Feldman, D.R. (2023) Prioritizing the Selection of CMIP6 Model Ensemble Members for Downscaling Projections of CONUS Temperature and Precipitation. Climate Dynamics, https://doi.org/10.1007/s00382-023-06846-z
[38] Ombadi, M., Risser, M.D., Rhoades, A.M., Varadharajan, C. (2023) A warming-induced reduction in snow fraction amplifies rainfall extremes. Nature, https://doi.org/10.1038/s41586-023-06092-7
[37] Pierce, D.W., Cayan, D.R., Feldman, D.R., Risser, M.D. (2023) Future Increases in North American Extreme Precipitation in CMIP6 downscaled with LOCA Journal of Hydrometeorology, https://doi.org/10.1175/JHM-D-22-0194.1
[36] Noack, M.M., Krishnan, H., Risser, M.D., Reyes, K.G. (2023) Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels. Nature Scientific Reports, https://doi.org/10.1038/s41598-023-30062-8
2022
[35] Bercos-Hickey, E., O'Brien, T.A., Wehner, M.F., Zhang, L., Patricola, C.M., Huang, H., Risser, M.D. (2022) Anthropogenic contributions to the 2021 Pacific Northwest heatwave. Geophysical Research Letters, https://doi.org/10.1029/2022GL099396
[34] Rhoades, A.M., Hatchett, B.J., Risser, M.D., Collins, W.D., et al. (2022) Asymmetric Emergence of Low-to-No Snow in the Midlatitudes of the American Cordillera. Nature Climate Change, https://doi.org/10.1038/s41558-022-01518-y
[33] Ombadi, M., Risser, M.D. (2022) How is the weather tomorrow? Increasing Trends in Volatility of Daily Maximum Temperature in Central and Eastern United States (1950--2019). Weather and Climate Extremes, https://doi.org/10.1016/j.wace.2022.100515
[32] Zhang, L., Risser, M.D., Molter, E.M., Wehner, M.F., O'Brien, T.A. (2022) Accounting for the spatial structure of weather systems in detected changes in precipitation extremes. Weather and Climate Extremes, https://doi.org/10.1016/j.wace.2022.100499
[31] Charn, A.B., O'Brien, T.A., Risser, M.D., Longmate, J.M., Feldman, D.R. (2022) Sign of Observed California Temperature Trends Depends on Data Set Homogenization: Implications for Weighting and Downscaling. Geophysical Research Letters, https://doi.org/10.1029/2022GL099186
[30] Risser, M.D., Collins, W.D., Wehner, M.F., O'Brien, T.A., Paciorek, C.J., O'Brien, J.P., Patricola, C.M., Huang, H., Ullrich, P.A., Loring, B. (2022) A framework for detection and attribution of regional precipitation change: Application to the United States historical record. Climate Dynamics, https://doi.org/10.1007/s00382-022-06321-1
2021
[29] Risser, M.D., Feldman, D.R., Wehner, M.F., Pierce, D.W., Arnold, J. (2021). Identifying and Correcting Biases in Localized Downscaling Estimates of Daily Precipitation Return Values. Climatic Change, https://doi.org/10.1007/s10584-021-03265-z
[28] Molter, E.M., Collins, W.D., Risser, M.D. (2021). Quantitative Precipitation Estimation of Extremes in CONUS with Radar Data. Geophysical Research Letters, https://doi.org/10.1029/2021GL094697
[27] Pierce, D.W., Su, L., Cayan, D.R., Risser, M.D., Livneh, B., Lettenmaier, D.P. (2021). An extreme-preserving long-term gridded daily precipitation data set for the conterminous United States. Journal of Hydrometeorology, https://doi.org/10.1175/JHM-D-20-0212.1
[26] Rhoades, A.M., Risser, M. D., Stone, D.A., Wehner, M.F., Jones, A.D. (2021) Implications of warming on western United States landfalling atmospheric rivers and their flood damages, Weather and Climate Extremes, https://doi.org/10.1016/j.wace.2021.100326
[25] Charn, A.B.. Collins, W. D., Parishani, H., Risser, M.D. (2021) Global microphysical sensitivity of superparameterized precipitation extremes. Earth and Space Science, https://doi.org/10.1029/2020EA001308
[24] Huang, H., Patricola, C.M., O'Brien, T.A., Bercos-Hickey, E., Zhou, Y., Rhoades, A.M., Risser, M. D., Collins, W.D. (2021) Sources of subseasonal-to-seasonal predictability of atmospheric rivers and precipitation in the western United States. JGR-Atmospheres, https://doi.org/10.1029/2020JD034053
[23] Risser, M.D., Wehner, M.F., O'Brien, J.P., Patricola, C.M., O'Brien, T.A., Collins, W.D., Paciorek, C.J., Huang, H. (2021) Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation. Climate Dynamics, https://doi.org/10.1007/s00382-021-05638-7
[22] Wehner, M.F., Lee, J., Risser, M.D., Ullrich, P., Gleckler, P., Collins, W.D. (2021) Evaluation of extreme subdaily precipitation in high-resolution global climate model simulations. Philosophical Transactions of the Royal Society, https://doi.org/10.1098/rsta.2019.0545
2020
[21] O'Brien, T.A., Risser, M. D., Loring, B., Elbashandy, A.A., Krishnan, H., Johnson, J., Patricola, C.M., O'Brien, J.P., Mahesh, A., Arriaga Ramirez, S. and Rhoades, A.M. (2020) Detection of Atmospheric Rivers with Inline Uncertainty Quantification: TECA-BARD v1. 0. Geoscientific Model Development Discussions. https://doi.org/10.5194/gmd-2020-55
[20] Risser, Mark D., Wehner, M.F. (2020) The effect of geographic sampling on evaluation of extreme precipitation in high resolution climate models. Advances in Statistical Climatology, Meteorology and Oceanography, 6, 115–139. https://doi.org/10.5194/ascmo-6-1-2020
[19] Risser, Mark D., Turek, Daniel. (2020) Bayesian inference for high-dimensional nonstationary Gaussian processes. Journal of Statistical Computation and Simulation. https://doi.org/10.1080/00949655.2020.1792472
[18] Charn, A.B.. Collins, W. D., Parishani, H., Risser, M.D., O'Brien, T.A. (2020) Microphysical sensitivity of superparameterized precipitation extremes in the continental US due to feedbacks on large-scale circulation. Earth and Space Science, 7(7). https://doi.org/10.1029/2019EA000731
[17] Patricola, C.M., O’Brien, J.P., Risser, M.D., Rhoades, A.M., O’Brien, T.A, Ullrich, P.A., Stone, D.A., Collins, W.D. (2020). Maximizing ENSO as a source of western US hydroclimate predictability. Climate Dynamics, 54(1-2), 351-372. https://doi.org/10.1029/2019EA000731
2019
[16] Srivastava, A., Grotjahn, R., Ullrich, P. A., Risser, M. (2019). A unified approach to evaluating precipitation frequency estimates with uncertainty quantification: Application to Florida and California watersheds. Journal of Hydrology, 578, 124095. https://doi.org/10.1016/j.jhydrol.2019.124095
[15] Risser, M.D., Paciorek, C.J., O'Brien, T.A., Wehner, M.F., Collins, W.D. (2019). Detected changes in precipitation extremes at their native scales derived from in situ measurements. Journal of Climate, 32(23), 8087-8109. https://doi.org/10.1175/JCLI-D-19-0077.1
[14] Russell, B. T., Risser, M.D., Smith, R. L., Kunkel, K. E. (2019). Investigating the association between late spring Gulf of Mexico sea surface temperatures and US Gulf Coast precipitation extremes with focus on Hurricane Harvey. Environmetrics, e2595. https://doi.org/10.1002/env.2595
[13] Risser, M.D., Paciorek, C.J., O'Brien, T.A., Wehner, M.F., Collins, W.D. (2019). A probabilistic gridded product for daily precipitation extremes over the United States. Climate Dynamics, 53(5):2517--2538. https://doi.org/10.1007/s00382-019-04636-0
[12] Risser, M.D., Calder, C. A., Berrocal, V. J., Berrett, C. (2019). Nonstationary spatial prediction of soil organic carbon: Implications for stock assessment decision making. The Annals of Applied Statistics, 13(1), 165-188. https://doi.org/10.1214/18-AOAS1204
2018
[11] Risser, M.D., Paciorek, C.J., Stone, D.A. (2018). Spatially-Dependent Multiple Testing Under Model Misspecification, with Application to Detection of Anthropogenic Influence on Extreme Climate Events. Journal of the American Statistical Association, 114(525):61-78. https://doi.org/10.1080/01621459.2018.1451335
[10] Feldman, D. R., Collins, W. D., Biraud, S. C., Risser, M.D., Turner, D. D., Gero, P. J., et al. (2018). Observationally derived rise in methane surface forcing mediated by water vapour trends. Nature Geoscience, 11(4), 238. https://doi.org/10.1038/s41561-018-0085-9
[9] Stone, D. A., Risser, M.D., Ang\'elil, O. M., Wehner, M. F., Cholia, S., Keen, N., et al. (2018). A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5. 1-1degree. Weather and climate extremes, 19, 10-19. https://doi.org/10.1016/j.wace.2017.12.003
2017
[8] Risser, M.D., Wehner, M.F. Attributable human‐induced changes in the likelihood and magnitude of the observed extreme precipitation during hurricane Harvey. Geophysical Research Letters, 44(24):12-457. https://doi.org/10.1002/2017GL075888
[7] Dayton, E. A., Holloman, C. H., Subburayalu, S., Risser, M.D. (2017). Using crop management scenario simulations to evaluate the sensitivity of the Ohio phosphorus risk index. Journal of Environmental Protection, 8(02), 141. https://doi.org/10.4236/jep.2017.82012
[6] Risser, M.D., Stone, D. A., Paciorek, C. J., Wehner, M. F., Ang\'elil, O. (2017). Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence. Climate Dynamics, 49(9-10), 3051-3073. https://doi.org/10.1007/s00382-016-3492-x
[5] Risser, M.D., Calder, C.A. (2017). Local Likelihood Estimation for Covariance Functions with Spatially-Varying Parameters: The convoSPAT Package for R. Journal of Statistical Software, 81(14), 1-32. https://doi.org/10.18637/jss.v081.i14
2016
[4] Sirilla, J., Thompson, K., Yamokoski, T., Risser, M.D., Chipps, E. (2017). Moral distress in nurses providing direct patient care at an academic medical center. Worldviews on Evidence‐Based Nursing, 14(2), 128-135. https://doi.org/10.1111/wvn.12213
[3] Tanner-Smith, E. E., Risser, M.D. (2016). A meta-analysis of brief alcohol interventions for adolescents and young adults: variability in effects across alcohol measures. The American Journal of Drug and Alcohol Abuse, 42(2), 140-151. https://doi.org/10.3109/00952990.2015.1136638
2015
[2] Risser, M.D., Calder, C. A. (2015). Regression‐based covariance functions for nonstationary spatial modeling. Environmetrics, 26(4), 284-297. https://doi.org/10.1002/env.2336
2013
[1] Miller, J., Risser, M., Griffiths, R. (2013). Student choice, instructor flexibility: Moving beyond the blended instructional model. Issues and trends in educational technology, 1(1), 8-24.