Our peer-reviewed papers.
In Review
Mizukami, N., M.P. Clark, S. Gharari, E. Kluzek, M. Pan, P, Lin, H.E. Beck and D. Yamazaki, 2020: A vector-based river routing model for Earth System Models: Parallelization and global applications. Journal of Advances in Modeling Earth Systems,
in review
Musselman, K.N., F. Lehner, K. Ikeda, M.P. Clark, A. Prein, C. Liu, M. Barlage and R. Rasmussen, 2017: Projected increases and regime shifts in rain-on-snow flood potential over western North America. Nature Climate Change,
in review
Musselman, K.N., N.P. Molotch, and S.A. Margulis, 2017: Snowmelt response to simulated warming across a large elevation gradient, southern Sierra Nevada, California. The Cryosphere,
11,
1-19,
doi:10.5194/tc-11-1-2017
Lehner, F., A. W. Wood, D. Llewellyn, D. B. Blatchford, A. G. Goodbody, F. Pappenberger, 2017: Mitigating the impacts of climate non-stationarity on seasonal streamflow predictability in the US Southwest. Geophysical Research Letters,
in review
Clark, E.A., A.W. Wood, and B. Nijssen, 2017: Assessing ensemble particle filters for the estimation of model states for streamflow forecasting. Wat. Res. Rsrch.,
in review
Maurer, E.P., G. Kayser, L. Doyle, and A.W. Wood, 2016: Incorporating increased flood frequency in the Western United States due to climate change in infrastructure planning. J. Water and Clim. Chng.,
in review
2019
Rakovec, O, N. Mizukami, R. Kumar, A.J. Newman, S. Thober, M.P. Clark, A.W. Wood, M.P. Clark and L. Samaniego, 2019: Diagnostic Evaluation of Large‐Domain Hydrologic Models Calibrated Across the Contiguous United States. Journal of Geophysical Research: Atmospheres,
124,
13991– 14007,
doi:https://doi.org/10.1029/2019JD030767
Mizukami, N., O. Rakovec, A.J. Newman, M.P. Clark, A.W. Wood, H.V. Gupta and R. Kumar, 2019: On the choice of calibration metrics for “high-flow” estimation using hydrologic models. Hydrology and Earth System Sciences,
23,
2601-2614,
doi:https://doi.org/10.5194/hess-23-2601-2019
2018
Vano, J.A., J.R. Arnold, B. Nijssen, M.P. Clark, A.W. Wood, E.D. Gutmann, N. Addor, J. Hamman, and F. Lehner, 2018: DOs and DON’Ts for using climate change information for water resource planning and management: guidelines for study design. Climate Services,
doi:10.1016/j.cliser.2018.07.002
Monaghan, A. J., M. P. Clark, M. P. Barlage, A. J. Newman, L. Xue, J. R. Arnold, and R. M. Rasmussen, 2018: High-resolution historical climate simulations over Alaska: A new resource for the research community. J. Applied Meteor. Climatol.,
57,
709-731,
doi:10.1175/JAMC-D-17-0161.1
Melsen, L., N. Addor, N. Mizukami, A. J. Newman, P. Torfs, M. Clark, R. Uijlenhoet, and A. J. Teuling, 2018: Mapping (dis)agreement in hydrologic projections. HESS,
22,
1775-1791,
doi:10.5194/hess-22-1775-2018
Longman, R. J., T. W. Giambelluca, M. A. Nullet, A. G. Frazier, K. Kodama, S. D. Crausbay, P. D. Krushelnycky, S. Cordell, M. P. Clark, A. J. Newman, and J. R. Arnold, 2018: Compliation of climate data from heterogeneous networks across the Hawaiian Islands. Sci. Data,
5,
180012,
doi:10.1038/sdata.2018.12
2017
Zhao, T., J. Bennett, Q.J. Wang, A. Schepen, A.W. Wood, D. Robertson, and M.H. Ramos, 2017: How suitable is quantile mapping for post-processing GCM precipitation forecasts?. J. Climate,
30,
3185-3196,
doi:10.1175/JCLI-D-16-0652.1
Wobus, C., E. Gutmann, R. Jones, M. Rissing, N. Mizukami, M. Lorie, H. Mahoney, A.W. Wood, D. Mills, and J. Martinich, 2017: Climate change impacts on flood risk and asset damages within mapped 100-year floodplains of the contiguous United States. Nat. Hazards Earth Syst. Sci.,
17,
2199-2211,
doi:10.5194/nhess-17-2199-2017
Vano, J.A., D. Behar, P.W. Mote, D.B. Ferguson, and R.E. Pandya, 2017: Partnerships Drive Science to Action Across the AGU Community. Eos,
98,
doi:10.1029/2017EO088041
Newman, A. J., N. Mizukami, M.P. Clark, A. W. Wood, B. Nijssen, and G. Nearing, 2017: Benchmarking of a physically based hydrology model. J. Hydrometeorology,
18,
2215-2225,
doi:10.1175/JHM-D-16-0284.1
Musselman, K.N. and J.W. Pomeroy, 2017: Estimation of needle-leaf canopy and trunk temperatures and longwave contribution to melting snow. Journal of Hydrometeorology,
18(2),
555-572,
doi:10.1175/jhm-d-16-0111.1
Musselman, K.N., M.P. Clark, C. Liu, K. Ikeda, and R. Rasmussen, 2017: Slower snowmelt in a warmer world. Nature Climate Change,
7(3),
214–219,
doi:10.1038/nclimate3225
Mizukami, N., M.P. Clark, A. J. Newman, A. W. Wood, E. Gutmann, B. Nijssen, O. Rakovec, and L. Samaniego, 2017: Towards seamless large domain parameter estimation for hydrologic models. Water Resources Research,
accepted
doi:10.1002/2017WR020401
Mendoza P.A., A.W. Wood, E. Clark, E. Rothwell, M.P. Clark, B. Nijssen, L.D. Brekke, and J.R. Arnold, 2017: An intercomparison of approaches for improving predictability in operational seasonal streamflow forecasting. Hydrology and Earth System Sciences Discussions,
21,
3915-3935,
doi:10.5194/hess-2017-60
Mendoza, P.A., N. Mizukami, K. Ikeda, M.P. Clark, E.D. Gutmann, J.R. Arnold, L.D. Brekke, and B. Rajagopalan, 2017: Effects of different regional climate model resolution and forcing scales on projected hydrologic changes. Journal of Hydrology,
541,
1003-1019,
doi:10.1016/j.jhydrol.2016.08.010
López-Moreno, I., S. Gascoin, J. Herrero, E. Spoles, M. Pons, E. Alonso, J. Sickman, K.N. Musselman, A. Boudhar, L. Hanich, N. Molotch, and J. Pomeroy, 2017: Different sensitivities of snowpack to warming in Mediterranean climate mountain areas. Environmental Research Letters,
12(7),
074006,
Liu, C., K. Ikeda, R. Rasmussen, M. Barlage, A.J. Newman, A.F. Prein, F. Chen, L. Chen, M. Clark, A. Dai, J. Dudhia, T. Eidhammer, D. Gochis, E. Gutmann, S. Kurkute, Y. Li, G. Thompson, and D. Yates, 2017: Continental-scale convection-permitting modeling of the current and future climate of North America. Climate Dynamics,
49,
71-95,
doi:10.1007/s00382-016-3327-9
Lehner, F., E.R. Wahl, A.W. Wood, D.B. Blatchford, and D. Llewellyn, 2017: Assessing recent declines in Upper Rio Grande River runoff efficiency from a paleoclimate perspective. Geophysical Research Letters,
doi:10.1002/2017GL073253
Huang, C., A.J. Newman, M.P. Clark, A.W. Wood, and X. Zheng, 2017: Evaluation of snow data assimilation using the ensemble Kalman Filter for seasonal streamflow prediction in the Western United States. HESS,
in press
Gutmann, E.D., J.T. Van Stan, J. Friesen, D.P. Aubrey, and J. Lundquist, 2017: Observed compression of in situ tree stems during freezing. Agricultural and Forest Meteorology,
243,
19-24,
doi:10.1016/j.agrformet.2017.05.004
Clark, M.P., B. Nijssen, and C.H. Luce, 2017: An analytical test case for snow models. Water Resources Research,
53,
909-922,
doi:10.1002/2016WR019672
Clark, M.P., M.F.P. Bierkens, L. Samaniego, R.A. Woods, R. Uijenhoet, K.E. Bennet, V.R.N. Pauwels, X. Cai, A.W. Wood, and C.D. Peters-Lidard, 2017: The evolution of process-based hydrologic models: Historical challenges and the collective quest for physical realism. Hydrol. and Earth Syst. Sci.,
21,
3427–3440,
doi:10.5194/hess-21-3427-2017
Arnal, L., A.W. Wood, E. Stephens, H.L. Cloke, and F. Pappenberger, 2017: An Efficient Approach for Estimating Streamflow Forecast Skill Elasticity. Journal of Hydrometeorology,
Early Online Release,
doi:10.1175/JHM-D-16-0259.1
Addor, N., A.J. Newman, N. Mizukami, and M.P. Clark, 2017: The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrol. and Earth Syst. Sci.,
21,
5293-5313,
doi:10.5194/hess-21-5293-2017
2016
Wood, A.W.,T. Hopson,A. Newman, L.D. Brekke, J.R. Arnold, and M. Clark, 2016: Quantifying Streamflow Forecast Skill Elasticity to Initial Condition and Climate Prediction Skill. Journal of Hydrometeorology,
17,
651-668,
doi:10.1175/JHM-D-14-0213.1
Sofaer, H.R., S.K. Skagen, J.J. Barsugli, B.S. Rashford, G.C. Reese, J.A. Hoeting, A.W. Wood, and B.R. Noon, 2016: Projected wetland densities under climate change: habitat loss but little geographic shift in conservation strategy. Ecol Appl.,
doi:10.1890/15-0750.1
Pagano, T.C., F. Pappenberger, A.W. Wood, M.H. Ramos, A. Persson, and B. Anderson, 2016: Automation and human expertise in operational river forecasting. WIREs Water,
3,
692–705,
doi:10.1002/wat2.1163
Mizukami, N., M.P. Clark, E. Gutmann, P.A. Mendoza, A.J. Newman, B. Nijssen, B.Livneh, L.E. Hay, J.R. Arnold, and L.D. Brekke, 2016: Implications of the Methodological Choices for Hydrologic Portrayals of Climate Change over the Contiguous United States: Statistically Downscaled Forcing Data and Hydrologic Models. Journal of Hydrometeorology,
17,
73-98,
doi:10.1175/JHM-D-14-0187.1
Mizukami, N., M.P. Clark, K. Sampson, B. Nijssen, Y. Mao, H. McMillan, R.J. Viger, S.L. Markstrom, L.E. Hay, R. Woods, J.R. Arnold, and L.D. Brekke, 2016: mizuRoute version 1: a river network routing tool for a continental domain water resources applications. Geoscientific Model Development,
9,
2223-2238,
doi:10.5194/gmd-9-2223-2016
McEvoy, D., J. Huntington, M. Hobbins, A.W. Wood, C. Morton, and J. Verdin, 2016: The Evaporative Demand Drought Index Part II: Application and Assessment. AMS J. Hydromet,
doi:10.1175/JHM-D-15-0122.1
Madadgar, S., A. AghaKouchak, S. Shukla, S. Sorooshian, K-L Hsu, M. Svoboda, and A.W. Wood, 2016: A Hybrid Statistical-Dynamical Drought Prediction Framework: Application to for the Southwestern United States. Wat. Res. Rsrch,
doi:10.1002/2015WR018547
Hobbins, M., A.W. Wood, D. McEvoy, J. Huntington, C. Morton, and J. Verdin, 2016: The Evaporative Demand Drought Index: Part I – Linking Drought Evolution to Variations in Evaporative Demand. AMS J. Hydromet.,
doi:10.1175/JHM-D-15-0121.1
Gutmann, E., I. Barstad, M.P. Clark, J. Arnold, and R. Rasmussen, 2016: The Intermediate Complexity Atmospheric Research Model. Journal of Hydrometeorology,
17,
957–973,
doi:10.1175/JHM-D-15-0155.1
Clark, M.P., B. Schaefli, S. Schymanski, L. Samaniego, C. Luce, B. Jackson, J. Freer, J.R. Arnold, D. Moore, E. Istanbulluoglu, and S. Ceola, 2016: Improving the theoretical underpinnings of process-based hydrologic models. Water Resources Research,
52,
doi:10.1002/2015WR017910
Clark, M.P., R.L. Wilby, E.D. Gutmann, J.A. Vano, S. Gangopadhyay, A.W. Wood, H.J. Fowler, C. Prudhomme, J.R. Arnold, and L.D. Brekke, 2016: Characterizing uncertainty of the hydrologic impacts of climate change. Climate Change Reports,
2,
55-64,
doi:10.1007/s40641-016-0034-x
Addor N., M. Rohrer, R. Furrer, and J. Seiber, 2016: Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment. Journal of Geophysical Research: Atmospheres,
in press,
doi:10.1002/2015JD024040
2015
Wood, E.F., S. Schubert, A.W. Wood, C. Peters-Lidard, K. Mo, A. Mariotti, and R. Pulwarty, 2015: Prospects for Advancing Drought Understanding, Monitoring and Prediction. J. Hydromet.,
doi:10.1175/JHM-D-14-0164.1
Newman, A.J., M.P. Clark, J. Craig, B. Nijssen, A.W. Wood, E.D. Gutmann, N. Mizukami, L. Brekke, and J.R. Arnold, 2015: Gridded ensemble precipitation and temperature estimates for the contiguous United States. Journal of Hydrometeorology,
16,
2481-2500,
doi:10.1175/JHM-D-15-0026.1
Newman, A. J., M.P. Clark, K. Sampson, A.W. Wood, L.E. Hay, A. Bock, R.J. Viger, D. Blodgett, L. Brekke, J.R. Arnold, T. Hopson, and Q. Duan, 2015: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences,
19,
209-223,
doi:10.5194/hess-19-209-2015
Mendoza P.A., B. Rajagopalan, M.P. Clark, K. Ikeda, and R.M. Rasmussen, 2015: Statistical Postprocessing of High-Resolution Regional Climate Model Output. Monthly Weather Review,
143(5),
1533–1553,
doi:10.1175/MWR-D-14-00159.1
Mendoza P.A., M.P. Clark, M. Barlage, B. Rajagopalan, L. Samaniego, G. Abramowitz, and H. Gupta, 2015: Are we unnecessarily constraining the agility of complex process-based models?. Water Resources Research,
51,
716–728,
doi:10.1002/2014WR015820
Mendoza, P. A., M. Clark, N. Mizukami, A. Newman, M. Barlage, E. Gutmann, R. Rasmussen, B. Rajagopalan, L. Brekke, and J. Arnold, 2015: Effects of hydrologic model choice and calibration on the portrayal of climate change impacts. J. Hydrometeor,
16,
762–780,
doi:10.1175/JHM-D-14-0104.1
Mendoza, P.A., M.P. Clark, N. Mizukami, E.D. Gutmann, J.R. Arnold, L.D. Brekke, and B. Rajagopalan, 2015: How do hydrologic modeling decisions affect the portrayal of climate change impacts?. Hydrol. Process.,
30,
1071–1095,
doi:10.1002/hyp.10684
Gochis, D., R. Schumacher, K. Friedrich, N. Doesken, M. Kelsch, J. Sun, K. Ikeda, D. Lindsey, A. Wood, B. Dolan, S. Matrosov, A. Newman, K. Mahoney, S. Rutledge, R. Johnson, P. Kucera, P. Kennedy, D. Sempere-Torres, M. Steiner, R. Roberts, J. Wilson, W. Yu, V. Chandrasekar, R. Rassmussen, A. Anderson, and B. Brown, 2015: The great Colorado flood of September 2013. Bulletin of the American Meteorological Society,
96,
1461-1487,
doi:10.1175/BAMS-D-13-00241.1
Emerton, R., E.M. Stephens, F. Pappenberger, T.C. Pagano, A.H. Weerts, A.W. Wood, P. Salamon, J.D. Brown, N. Hjerdt, C. Donnelly, and H.L. Cloke, 2015: Continental and Global Scale Flood Forecasting Systems. WIREs Water,
doi:10.1002/wat2.1137
Crochemore, L., M.H. Ramos, F. Pappenberger, S.J. van Andel, and A.W. Wood, 2015: An experiment on risk-based decision-making in water management using probabilistic forecasts. Bull. Amer. Met. Soc.,
doi:10.1175/BAMS-D-14-00270.1
Clark, M.P., B. Nijssen, J.D. Lundquist, D. Kavetski, D.E. Rupp, R.A. Woods, J.E. Freer, E.D. Gutmann, A.W. Wood, D.J. Gochis, R.M. Rasmussen, D.G. Tarboton, V. Mahat, G.N. Flerchinger, and D.G. Marks, 2015: A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies. Water Resources Research,
51,
2515-2542,
doi:10.1002/2015wr017200
Clark, M.P., B. Nijssen, J.D. Lundquist, D. Kavetski, D.E. Rupp, R.A. Woods, J.E. Freer, E.D. Gutmann, A.W. Wood, L.D. Brekke, J.R. Arnold, D.J. Gochis, and R.M. Rasmussen, 2015: A unified approach to process-based hydrologic modeling. Part 1: Modeling concept. Water Resources Research,
51,
2498–2514,
doi:10.1002/2015WR017198
2014
Pagano, T.C., A.W. Wood, M.H. Ramos, H.L. Cloke, F. Pappenberger, V. Andréassian, M.P. Clark, M. Cranston, D. Kavetski, T. Mathevet, S. Sorooshian, and J.S. Verkade, 2014: Challenges of Operational River Forecasting. AMS J. Hydromet.,
15,
1692–1707,
doi:10.1175/JHM-D-13-0188.1
Newman,A.J., M.P. Clark, A. Winstral, D. Marks, and M. Seyfried, 2014: The use of similarity concepts to represent sub-grid varibility in hydrologic an land-surface models: Case study in a snowmelt dominated watershed. Journal of Hydrometeorology,
15,
1717-1738,
doi:10.1175/JHM-D-13-038.1
Mizukami, N., M.P. Clark, A.G. Slater, L.D. Brekke, M.M. Elsner, J.R. Arnold, and S. Gangopadhyay, 2014: Hydrologic Implications of Different Large-Scale Meteorological Model Forcing Datasets in Mountainous Regions.. Journal of Hydrometeorology,
15,
474-488,
doi:doi:10.1175/JHM-D-13-036.1
Mendoza P.A., B. Rajagopalan, M.P. Clark, G. Cortés, and J. McPhee, 2014: A robust multimodel framework for ensemble seasonal hydroclimatic forecasts. Water Resources Research,
50(7),
6030–6052,
doi:10.1002/2014WR015426
Brekke L., A.W. Wood, and T. Pruitt, 2014: Downscaled CMIP3 and CMIP5 Hydrology Projections: Release of Hydrology Projections, Comparison with Preceding Information, and Summary of User Needs. prepared by the U.S. Department of the Interior, Bureau of Reclamation, Technical Service Center, Denver, Colorado,
, download at:http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/techmemo/BCSD5HydrologyMemo.pdf
2012
Gutmann, E.D., R.M. Rasmussen, C. Liu, K. Ikeda, D.J. Gochis, M.P. Clark, J. Dudhia, and G. Thompson, 2012: A Comparison of Statistical and Dynamical Downscaling of Winter Precipitation over Complex Terrain. Journal of Climate,
25,
262–281,
doi:10.1175/2011JCLI4109.1
2010
Samaniego, L., R. Kumar, and S. Attinger, 2010: Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale. Water Resources Research,
26,
W05523,
doi:10.1029/2008WR007327
2006
Barstad, I., and S. Gronas, 2006: Dynamical structures for southwesterly airflow over southern Norway: the role of dissipation. Tellus Series a-Dynamic Meteorology and Oceanography,
58,
2-18,
doi:doi:10.1111/j.1600- 0870.2006.00152.x
2005
Gangopadhyay, S., M.P. Clark, and B. Rajagopalan, 2005: Statistical downscaling using K-nearest neighbor. Water Resources Research,
41,
W02024,
doi:10.1029/2004WR003444
