M. Raleigh

发表

A Comparison of Methods for Filling Gaps in Hourly Near-Surface Air Temperature Data

J. Lundquist, B. Henn, M. Raleigh, 2013 .

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

J. Lundquist, M. Clark, M. Raleigh, 2014 .

Ground-based testing of MODIS fractional snow cover in subalpine meadows and forests of the Sierra Nevada

Jessica D. Lundquist, Karl Rittger, James A. Lutz, 2013 .

A microfabrication approach for making metallic mechanical metamaterials

M. Raleigh, H. Wadley, W. King, 2018, Materials & Design.

An evaluation of terrain‐based downscaling of fractional snow covered area data sets based on LiDAR‐derived snow data and orthoimagery

Janneke HilleRisLambers, Jessica D. Lundquist, Nicoleta C. Cristea, 2017 .

Impact of errors in the downwelling irradiances on simulations of snow water equivalent, snow surface temperature, and the snow energy balance

Jessica D. Lundquist, Laura M. Hinkelman, J. Lundquist, 2015 .

Improving SWE Estimation With Data Assimilation: The Influence of Snow Depth Observation Timing and Uncertainty

M. Raleigh, E. Small, E. Smyth, 2020, Water Resources Research.

Within‐Stand Boundary Effects on Snow Water Equivalent Distribution in Forested Areas

D. McGrath, N. Molotch, M. Raleigh, 2019, Water Resources Research.

Large‐diameter trees affect snow duration in post‐fire old‐growth forests

M. Raleigh, J. Lutz, Kendall M. L. Becker, 2022, Ecohydrology.

How Does Availability of Meteorological Forcing Data Impact Physically Based Snowpack Simulations

J. Lundquist, M. Raleigh, B. Livneh, 2016 .

ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks

S. Hagemann, F. Chéruy, A. Ducharne, 2018, Geoscientific Model Development.

Evaluating observational methods to quantify snow duration under diverse forest canopies

J. Lundquist, M. Raleigh, J. Lutz, 2014 .

Uncertainty in seasonal snow reconstruction: Relative impacts of model forcing and image availability

Martyn P. Clark, Jessica D. Lundquist, Andrew G. Slater, 2013 .

Hydrophobic and oleophobic re-entrant steel microstructures fabricated using micro electrical discharge machining

A. Jacobi, M. Raleigh, W. King, 2014 .

Meteorological and evaluation datasets for snow modelling at ten reference sites: description of in situ and bias-corrected reanalysis data

Libo Wang, P. Bartlett, D. Marks, 2019 .

Canopy Adjustment and Improved Cloud Detection for Remotely Sensed Snow Cover Mapping

T. Painter, J. Dozier, M. Raleigh, 2020, Water Resources Research.

Landsat, MODIS, and VIIRS snow cover mapping algorithm performance as validated by airborne lidar datasets

Edward H. Bair, R. Davis, M. Raleigh, 2023, The Cryosphere.

Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring

P. Blanken, M. Raleigh, E. Small, 2021, Water Resources Research.

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

M. Raleigh, E. Small, E. Smyth, 2022, Water Resources Research.

Spatial Heterogeneity in Ecologically Important Climate Variables at Coarse and Fine Scales in a High-Snow Mountain Landscape

J. Lundquist, M. Raleigh, A. Ettinger, 2013, PloS one.

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

V. Chandrasekar, W. Boos, J. Harrington, 2021 .

Comparing and combining SWE estimates from the SNOW‐17 model using PRISM and SWE reconstruction

Jessica D. Lundquist, J. Lundquist, M. Raleigh, 2012 .

Quantification of uncertainties in snow accumulation, snowmelt, and snow disappearance dates

M. Raleigh, 2013 .

WHAT LIES BENEATH ? COMPARING MODIS FRACTIONAL SNOW COVERED AREA AGAINST GROUND-BASED OBSERVATIONS UNDER FOREST CANOPIES AND IN MEADOWS OF THE SIERRA NEVADA

J. Lundquist, M. Raleigh, K. Rittger, 2012 .

The Challenges of Simulating SWE Beneath Forest Canopies are Reduced by Data Assimilation of Snow Depth

M. Raleigh, E. Small, E. Smyth, 2022, Water Resources Research.

Isolating forest process effects on modelled snowpack density and snow water equivalent

M. Raleigh, E. Small, Hannah M. Bonner, 2022, Hydrological Processes.

Particle Filter Data Assimilation of Monthly Snow Depth Observations Improves Estimation of Snow Density and SWE

Eric E. Small, M. Raleigh, E. Small, 2019, Water Resources Research.

ESM-SnowMIP: Assessing models and quantifying snow-related climate feedbacks

Chris Derksen, Anna Kontu, Helmut Rott, 2018 .

Snowpack density modeling is the primary source of uncertainty when mapping basin‐wide SWE with lidar

Eric E. Small, M. Raleigh, E. Small, 2017 .

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

Thomas Howell Painter, P. E. Lyon, M. Clark, 2006 .

From flowering to foliage: Accelerometers track tree sway to provide high-resolution insights into tree phenology

C. Wessman, M. Raleigh, J. Friedman, 2022, Agricultural and Forest Meteorology.

FILLING THE HOLES IN THE SPACE-TIME CUBE OF SNOWPACK EVOLUTION WITH LASERS, CAMERAS, COMPUTERS, AND SNOW SHOVELS

M. Raleigh, J. Deems, 2018 .

Approximating snow surface temperature from standard temperature and humidity data: New possibilities for snow model and remote sensing evaluation

William L. Quinton, Masaki Hayashi, Jessica D. Lundquist, 2013 .

Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA

Tate G. Meehan, S. O’Neel, M. Raleigh, 2024, The Cryosphere.

Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data

M. Raleigh, R. Essery, N. Wever, 2019, Earth System Science Data.

Tracking the Evolution of Snow Drought in the U.S. Pacific Northwest at Variable Scales

M. Raleigh, B. M. Roberts‐Pierel, R. E. Kennedy, 2024, Water Resources Research.

The Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign

V. Chandrasekar, W. Boos, J. Lundquist, 2023, Bulletin of the American Meteorological Society.