Publications

2020

18. Smyth E., Raleigh M.S., and E.E. Small (2020), Improving SWE estimation with data assimilation: the influence of snow depth observation timing and uncertainty, Water Resources Research, accepted.

2019

17. Rittger K., Raleigh M.S., Dozier J., Hill A.F., Lutz J.A., and T.H. Painter (2019), Canopy adjustment and improved cloud detection for remotely sensed snow cover mapping, Water Resources Research, in press, doi: 10.1029/2019WR024914. Paper 

16. Ménard C. B., Essery R., Barr A., Bartlett P., Derry J., Dumont M., Fierz C., Kim H., Kontu A., Lejeune Y., Marks D., Niwano M., Raleigh M.S., Wang L., and N. Wever (2019), Meteorological and evaluation datasets for snow modelling at ten reference sites: description of in situ and bias-corrected reanalysis data, Earth System Science Data, doi: 10.5194/essd-11-865-2019. Paper  Data 

15. Smyth E., Raleigh M.S., and E.E. Small (2019), Particle filter data assimilation of monthly snow depth observations improves estimation of snow density and SWE, Water Resources Research, doi: 10.1029/2018WR023400. Paper

2018

14. Krinner G., Derksen C., Essery R., Flanner M., Hagemann S., Clark M., Hall A., Rott H., Brutel-Vuilmet C., Kim H., Ménard C. B., Mudryk L., Thackeray C., Wang L., Arduini G., Balsamo G., Bartlett P., Boike J., Boone A., Chéruy F., Colin J., Cuntz M., Dai Y., Decharme B., Derry J., Ducharne A., Dutra E., Fang X., Fierz C., Ghattas J., Gusev Y., Haverd V., Kontu A., Lafaysse M., Law R., Lawrence D., Li W., Marke T., Marks D., Nasonova O., Nitta T., Niwano M., Pomeroy J., Raleigh M.S., Schaedler G., Semenov V., Smirnova T., Stacke T., Strasser U., Svenson S., Turkov D., Wang T., Wever N., Yuan H., and W. Zhou (2018), ESM-SnowMIP: Assessing models and quantifying snow-related climate feedbacks, Geoscientific Model Development, doi:10.5194/gmd-11-5027-2018. Paper 

2017

13. Raleigh, M. S., and E.E. Small (2017), Snowpack density modeling is the primary source of uncertainty when mapping basin-wide SWE with lidar, Geophysical Research Letters, doi:10.1002/2016GL071999. Paper 

12. Cristea, N.C., Breckheimer I., Raleigh M.S., HilleRisLambers J., and J.D. Lundquist (2017), An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery, Water Resources Research, doi: 10.1002/2017WR020799. Paper

2016

11. Raleigh, M.S., Livneh B., Lapo K., and J.D. Lundquist (2016), How does availability of meteorological forcing data impact physically-based snowpack simulations?, Journal of Hydrometeorology, doi:10.1175/J HM-D-14-0235.1. Paper

2015

10. Raleigh, M.S., Lundquist J.D., and M.P. Clark (2015), Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework, Hydrology and Earth System Sciences, doi:10.5194/hess-19-3153-2015. Paper 

9. Dickerson-Lange, S.E., Lutz J.A., Martin K.A., Raleigh M.S., Gersonde R., and J.D. Lundquist (2015), Evaluating observational methods to quantify snow duration under diverse forest canopies, Water Resources Research, doi: 10.1002/2014WR015744. Paper 

8. Lapo, K.E., Hinkelman L.M., Raleigh M.S., and J.D. Lundquist (2015), Impact of errors in the downwelling irradiances on simulations of snow water equivalent, snow surface temperature, and the snow energy balance, Water Resources Research, 51, doi: 10.1002/2014WR0162591. Paper 

2014

7. Landry, C.C., Buck K.A., Raleigh M.S., and M.P. Clark (2014), Mountain system monitoring at Senator Beck Basin, San Juan Mountains, Colorado: A new integrative data source to develop and evaluate models of snow and hydrologic processes, Water Resources Research, doi: 10.1002/2013WR013711. Paper 

2013

6. Raleigh, M.S., Landry C.C. , Hayashi M., Quinton W.L., and J.D. Lundquist (2013), Approximating snow surface temperature from standard temperature and humidity data: New possibilities for snow model and remote sensing evaluation, Water Resources Research, doi: 10.1002/2013WR013958. Paper 

5. Raleigh, M.S., Rittger K., Moore C.E., Henn B., Lutz J.A., and J.D. Lundquist (2013), Ground-based testing of MODIS fractional snow cover in subalpine meadows and forests of the Sierra Nevada, Remote Sensing of Environment, doi: 10.1016/j.rse.2012.09.016. Paper 

4. Henn, B, Raleigh M.S., Fisher A., and J.D. Lundquist (2013), A comparison of methods for filling gaps in hourly near-surface air-temperature data, Journal of Hydrometeorology, doi: 10.1175/JHM-D-12-027.1. Paper 

3. Slater, A.G., Barrett A.P., Clark M.P., Lundquist J.D., and M.S. Raleigh (2013), Uncertainty in seasonal snow reconstruction: relative impacts of model forcing and image availability, Advances in Water Resources, doi: 10.1016/j.advwatres.2012.07.006. Paper 

2. Ford, K.R., Ettinger A.K., Lundquist J.D., Raleigh M.S., and J. Hille Ris Lambers (2013), Spatial heterogeneity in ecologically important climate variables at coarse and fine scales in a high-snow mountain landscape, PLoS ONE, doi: 10.1371/journal.pone.0065008. Paper 

2012

1. Raleigh, M.S., and J.D. Lundquist (2012), Comparing and combining SWE estimates from the SNOW-17 model using PRISM and SWE reconstruction, Water Resources Research, doi:10.1029/2011WR010542. Paper 


Conference Proceedings

Raleigh, M.S., & J.S. Deems (2018), Filling the holes in the space-time cube of snowpack evolution with lasers, cameras, computers, and snow shovels, 86th Western Snow Conference, Albuquerque, New Mexico. Paper

Raleigh, M.S., and J.S. Deems (2016), Investigating the response of an operational snowmelt model to unusual snow conditions and melt drivers, 84th Western Snow Conference, Seattle, Washington. Paper 

Raleigh, M.S., and M.P. Clark (2014), Are temperature-index models appropriate for assessing climate change impacts on snowmelt?, 82nd Western Snow Conference, Durango, Colorado. Paper 

Raleigh, M.S., Rittger K., and J.D. Lundquist (2011), What lies beneath? Comparing MODIS fractional snow covered area against ground-based observations under forest canopies and in meadows of the Sierra Nevada, 79th Western Snow Conference, Stateline, Nevada. Paper 


Academic Research

Raleigh, M. S. (2013), Quantification of uncertainties in snow accumulation, snowmelt, and snow disappearance dates, PhD Thesis, Department of Civil and Environmental Engineering, University of Washington. Thesis 

Raleigh, M.S. (2009), A statistical evaluation of a snow water equivalent reconstruction method using three snowmelt models at daily and hourly time steps, Masters Thesis, Department of Civil and Environmental Engineering, University of Washington.


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