Nick Rutter

Radiative Transfer Modeling of a Coniferous Canopy Characterized by Airborne Remote Sensing

Abstract Solar radiation beneath a forest canopy can have large spatial variations, but this is frequently neglected in radiative transfer models for large-scale applications. To explicitly model spatial variations in subcanopy radiation, maps of canopy structure are required. Aerial photography and airborne laser scanning are used to map tree locations, heights, and crown diameters for a lodgepole pine forest in Colorado as inputs to a spatially explicit radiative transfer model. Statistics of subcanopy radiation simulated by the model are compared with measurements from radiometer arrays, and scaling of spatial statistics with temporal averaging and array size is discussed. Efficient parameterizations for spatial averages and standard deviations of subcanopy radiation are developed using parameters that can be obtained from the model or hemispherical photography.

Evaluation of the NOHRSC Snow Model (NSM) in a One-Dimensional Mode

Abstract The National Operational Hydrologic Remote Sensing Center (NOHRSC) Snow Model (NSM) is an energy- and mass-balance model used by the National Oceanic and Atmospheric Administration’s National Weather Service for moderate-resolution spatially distributed snow analysis and data assimilation over the United States. The NSM was evaluated in a one-dimensional mode using meteorological and snowpit observations from five sites in Colorado collected during 2002–03. Four parameters estimated by the NSM [snow water equivalent (SWE), snow depth, average snowpack temperature, and snow surface temperature] were compared with snowpit observations and with estimates from another snow energy and mass-balance model, SNTHERM. Root-mean-squared differences (RMSDs) between snowpit SWE observations (January–June) at all sites and estimates from the NSM were about 11% (RMSD = 0.073 m) of the average maximum observed SWE from all sites of 0.694 m. SNTHERM exhibited only a slightly better agreement (RMSD = 0.066 m). Dur...

NASA Cold Land Processes Experiment (CLPX 2002/03): Ground-Based and Near-Surface Meteorological Observations

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters include air temperature, relative humidity, wind speed and direction, barometric pressure, short- and long-wave radiation, leaf wetness, snow depth, snow water content, snow and surface temperatures, volumetric soil-moisture content, soil temperature, precipitation, water vapor flux, carbon dioxide flux, and soil heat flux. The CLPX weather stations include 10 main meteorological towers, 1 tower within each of the nine intensive study areas (ISA) and one near the local scale observation site (LSOS); and 36 simplified towers, with one tower at each of the four corners of each of the nine ISAs, which measured a reduced set of parameters. An eddy covariance system within the North Park mesocell study area (MSA) collected a variety of additional parameters beyond the 10 standard CLPX tower components. Additional meteorological observations come from a variety of existing networks maintained by the U.S. Forest Service, U.S. Geological Survey, Natural Resource Conservation Service, and the Institute of Arctic and Alpine Research. Temporal coverage varies from station to station, but it is most concentrated during the 2002/ 03 winter season. These data are useful in local meteorological energy balance research and for model development and testing. These data can be accessed through the National Snow and Ice Data Center Web site.

Recording microscale variations in snowpack layering using near-infrared photography

Deposition of snow from precipitation and wind events creates layering within seasonal snowpacks. The thickness and horizontal continuity of layers within seasonal snowpacks can be highly variable, due to snow blowing around topography and vegetation, and this has important implications for hydrology, remote sensing and avalanche forecasting. In this paper, we present practical field and post-processing protocols for recording lateral variations in snow stratigraphy using near-infrared (NIR) photography. A Fuji S9100 digital camera, modified to be sensitive to NIR wavelengths, was mounted on a rail system that allowed for rapid imaging of a 10 m long snow trench excavated on the north side of Toolik Lake, Alaska (68°3? N, 149°36? W). Post-processing of the images included removal of lens distortion and vignetting. A tape measure running along the base of the trench provided known locations (control points) that permitted scaling and georeferencing. Snow layer heights estimated from the NIR images compared well with manual stratigraphic measurements made at 0.2 m intervals along the trench (n = 357, R2 = 0.97). Considerably greater stratigraphic detail was captured by the NIR images than in the manually recorded profiles. NIR imaging of snow trenches using the described protocols is an efficient tool for quantifying continuous microscale variations in snow layers and associated properties.

Evaluation of Operation IceBridge quick‐look snow depth estimates on sea ice

We evaluate Operation IceBridge (OIB) ‘quick-look’ (QL) snow depth on sea ice retrievals using in situ measurements taken over immobile first-year ice (FYI) and multi-year ice (MYI) during March of 2014. Good agreement was found over undeformed FYI (-4.5 cm mean bias) with reduced agreement over deformed FYI (-6.6 cm mean bias). Over MYI, the mean bias was -5.7 cm but 54% of retrievals were discarded by the OIB retrieval process as compared to only 10% over FYI. Footprint scale analysis revealed a root mean square error (RMSE) of 6.2 cm over undeformed FYI with RMSE of 10.5 cm and 17.5 cm in the more complex deformed FYI and MYI environments. Correlation analysis was used to demonstrate contrasting retrieval uncertainty associated with spatial aggregation and ice surface roughness.

An Evaluation of Forest Snow Process Simulations

The Northern Hemisphere has large areas that are forested and seasonally snow covered. Compared with open areas, forest canopies strongly influence interactions between the atmosphere and snow on the ground by sheltering the snow from wind and solar radiation and by intercepting falling snow; these influences have important consequences for the meteorology, hydrology, and ecology of forests. Many of the land surface models used in meteorological and hydrological forecasting now include representations of canopy snow processes, but these have not been widely tested in comparison with observations. Phase 2 of the Snow Model Intercomparison Project (SnowMIP2) was therefore designed as an intercomparison of surface mass and energy balance simulations for snow in forested areas. Model forcing and calibration data for sites with paired forested and open plots were supplied to modeling groups. Participants in 11 countries contributed output from 33 models, and the results are published here for sites in Canada, the United States, and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide intermodal spread and a tendency to underestimate differences in snow mass between open and forested areas. Most models capture the large differences in surface albedos and temperatures between forest canopies and open snow well. There is, however, a strong tendency for models to underestimate soil temperature under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil.

Snow stratigraphic heterogeneity within ground‐based passive microwave radiometer footprints: Implications for emission modeling

Two-dimensional measurements of snowpack properties (stratigraphic layering, density, grain size, and temperature) were used as inputs to the multilayer Helsinki University of Technology (HUT) microwave emission model at a centimeter-scale horizontal resolution, across a 4.5 m transect of ground-based passive microwave radiometer footprints near Churchill, Manitoba, Canada. Snowpack stratigraphy was complex (between six and eight layers) with only three layers extending continuously throughout the length of the transect. Distributions of one-dimensional simulations, accurately representing complex stratigraphic layering, were evaluated using measured brightness temperatures. Large biases (36 to 68 K) between simulated and measured brightness temperatures were minimized (−0.5 to 0.6 K), within measurement accuracy, through application of grain scaling factors (2.6 to 5.3) at different combinations of frequencies, polarizations, and model extinction coefficients. Grain scaling factors compensated for uncertainty relating optical specific surface area to HUT effective grain size inputs and quantified relative differences in scattering and absorption properties of various extinction coefficients. The HUT model required accurate representation of ice lenses, particularly at horizontal polarization, and large grain scaling factors highlighted the need to consider microstructure beyond the size of individual grains. As variability of extinction coefficients was strongly influenced by the proportion of large (hoar) grains in a vertical profile, it is important to consider simulations from distributions of one-dimensional profiles rather than single profiles, especially in sub-Arctic snowpacks where stratigraphic variability can be high. Model sensitivity experiments suggested that the level of error in field measurements and the new methodological framework used to apply them in a snow emission model were satisfactory. Layer amalgamation showed that a three-layer representation of snowpack stratigraphy reduced the bias of a one-layer representation by about 50%.

Modeling subcanopy incoming longwave radiation to seasonal snow using air and tree trunk temperatures

Data collected at three Swiss alpine forested sites over a combined eleven-year period were used to evaluate the role of air temperature in modeling sub-canopy incoming longwave radiation to the snow surface. Simulated sub-canopy incoming longwave radiation is traditionally partitioned into that from the sky and that from the canopy, i.e. a two-part model. Initial uncertainties in predicting longwave radiation using the two-part model resulted from vertical differences in measured air temperature. Above-canopy (35m) air temperatures were higher than those within (10m) and below (2m) canopy throughout four snow seasons (Dec-Apr), demonstrating how the forest canopy can act as a cold sink for air. Lowest model RMSE was using above-canopy air temperature. Further investigation of modeling sub-canopy longwave radiation using above-canopy air temperature showed underestimations, particularly during periods of high insolation. In order to explicitly account for canopy temperatures in modeling longwave radiation, the two-part model was improved by incorporating a measured trunk-view component and trunk temperature. Trunk temperature measurements were up to 25°C higher than locally measured air temperatures. This three-part model reduced the RMSE by up to 7.7 Wm-2 from the two-part air temperature model at all sensor positions across the 2014 snowmelt season, and performed particularly well during periods of high insolation when errors from the two-part model were up to 40 Wm-2. A parameterization predicting tree trunk temperatures using measured air temperature and incoming shortwave radiation demonstrate a simple method that can be applied to provide input to the three-part model across mid-latitude coniferous forests.

Measurement of Incoming Radiation below Forest Canopies: A Comparison of Different Radiometer Configurations

AbstractGround-based, subcanopy measurements of incoming shortwave and longwave radiation are frequently used to drive and validate energy balance and snowmelt models. These subcanopy measurements are frequently obtained using different configurations (linear or distributed; stationary or moving) of radiometer arrays that are installed to capture the spatial and temporal variability of longwave and shortwave radiation. Three different radiometer configurations (stationary distributed, stationary linear, and moving linear) were deployed in a spruce forest in the eastern Swiss Alps during a 9-month period, capturing the annual range of sun angles and sky conditions. Results showed a strong seasonal variation in differences between measurements of shortwave transmissivity between the three configurations, whereas differences in longwave enhancement appeared to be seasonally independent. Shortwave transmissivity showed a larger spatial variation in the subcanopy than longwave enhancement at this field site. T...

Understanding Snow Microstructure for Microwave Remote Sensing

Scientists from the snow and soil remote sensing communities met to build on recent developments in objective snow microstructure measurement techniques by improving the understanding of their application in remote sensing at microwave frequencies.