Thomas H. Painter

Mountain hydrology of the western United States

Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground-based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges. Copyright 2006 by the American Geophysical Union.

Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data

We describe and validate an automated model that retrieves subpixel snow-covered area and effective grain size from Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) data. The model analyzes multiple endmember spectral mixtures with a spectral library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model; spectra for vegetation, rock, and soil were collected in the field and laboratory. For three AVIRIS images of Mammoth Mountain, California that span common snow conditions for winter through spring, we validate the estimates of snow-covered area with fine-resolution aerial photographs and validate the estimates of grain size with stereological analysis of snow samples collected within 2 h of the AVIRIS overpasses. The RMS error for snowcovered area retrieved from AVIRIS for the combined set of three images was 4%. The RMS error for snow grain size retrieved from a 3 � 3 window of AVIRIS data for the combined set of three images is 48 Am, and the RMS error for reflectance integrated over the solar spectrum and over all hemispherical reflectance angles is 0.018. D 2003 Elsevier Science Inc. All rights reserved.

Response of Colorado River runoff to dust radiative forcing in snow

The waters of the Colorado River serve 27 million people in seven states and two countries but are overallocated by more than 10% of the river’s historical mean. Climate models project runoff losses of 7–20% from the basin in this century due to human-induced climate change. Recent work has shown however that by the late 1800s, decades prior to allocation of the river’s runoff in the 1920s, a fivefold increase in dust loading from anthropogenically disturbed soils in the southwest United States was already decreasing snow albedo and shortening the duration of snow cover by several weeks. The degree to which this increase in radiative forcing by dust in snow has affected timing and magnitude of runoff from the Upper Colorado River Basin (UCRB) is unknown. Here we use the Variable Infiltration Capacity model with postdisturbance and predisturbance impacts of dust on albedo to estimate the impact on runoff from the UCRB across 1916–2003. We find that peak runoff at Lees Ferry, Arizona has occurred on average 3 wk earlier under heavier dust loading and that increases in evapotranspiration from earlier exposure of vegetation and soils decreases annual runoff by more than 1.0 billion cubic meters or ∼5% of the annual average. The potential to reduce dust loading through surface stabilization in the deserts and restore more persistent snow cover, slow runoff, and increase water resources in the UCRB may represent an important mitigation opportunity to reduce system management tensions and regional impacts of climate change.

The ecology of dust

Wind erosion and associated dust emissions play a fundamental role in many ecological processes and provide important biogeochemical connectivity at scales ranging from individual plants up to the entire globe. Yet, most ecological studies do not explicitly consider dust-driven processes, perhaps because most relevant research on aeolian (wind-driven) processes has been presented in a geosciences rather than an ecological context. To bridge this disciplinary gap, we provide a general overview of the ecological importance of dust, examine complex interactions between wind erosion and ecosystem dynamics from the scale of plants and surrounding space to regional and global scales, and highlight specific examples of how disturbance affects these interactions and their consequences. It is likely that changes in climate and intensification of land use will lead to increased dust production from many drylands. To address these issues, environmental scientists, land managers, and policy makers need to consider wind erosion and dust emissions more explicitly in resource management decisions.

The Effect of Grain Size on Spectral Mixture Analysis of Snow-Covered Area from AVIRIS Data

Abstract We developed a technique to improve spectral mixture analysis of snow-covered area in alpine regions through the use of multiple snow endmembers. Snow reflectance in near-infrared wavelengths is sensitive to snow grain size while in visible wavelengths it is relatively insensitive. Snow-covered alpine regions often exhibit large surface grain size gradients due to changes in aspect and elevation. The sensitivity of snow spectral reflectance to grain size translates these grain size gradients into spectral gradients. To spectrally characterize a snow-covered image domain with mixture analysis, the variable spectral nature of snow must be accounted for by use of multiple snow endmembers of varying grain size. We performed numerical simulations to demonstrate the sensitivity of mixture analysis to grain size for a range of sizes and snow fractions. From Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data collected over Mammoth Mountain, CA on 5 April 1994, a suite of snow image endmembers spanning the imaged region’s grain size range were extracted. Mixture models with fixed vegetation, rock, and shade were applied with each snow endmember. For each pixel, the snow fraction estimated by the model with least mixing error (RMS) was chosen to produce an optimal map of subpixel snow-covered area. Results were verified with a high spatial resolution aerial photograph demonstrating equivalent accuracy. Analysis of fraction under/overflow and residuals confirmed mixture analysis sensitivity to grain size gradients.

Measurements of the hemispherical-directional reflectance of snow at fine spectral and angular resolution

[1] We present 2 days’ measurements of the hemispherical-directional reflectance factor (HDRF) of snow made at fine spectral and angular resolution with the Automated Spectro-Goniometer (ASG) for the range of solar zenith angles (q0 =4 0� –50� ) and snow textures (surface grain size = 80–280 mm). Measurements of the stratigraphy of snow texture and density accompanied each day’s suite of measurements. These measurements represent the most detailed available in terms of angular and spectral resolution. The HDRF for fine grain, faceted snow exhibited a local backscattering peak at the view zenith near the solar zenith angle, whereas those for medium grain, clustered snow did not have a local backscattering peak. The HDRF decreased at all wavelengths for an increase in grain radius from 80 m mt o 280mm. However, the decrease in HDRF in the visible wavelengths was largest at qr =8 0� in the forward direction and largest for l >1 .8mm near qr =3 0� in the backward direction. As solar zenith angle decreased from 47� to 41� , the HDRF increased near nadir for l � 1.03 mm but decreased with coherent angular structure for l > 1.03 mm. We compared forward radiative transfer modeling results with the HDRF measurements. The forward model used single-scattering parameters for ice spheres with radii that matched the surface-area-to-volume ratio derived from stereological analysis of snow samples and a stratigraphic distribution of optical depths from measured density and modeled extinction efficiency. All HDRF models underestimated reflectance for l > 1.30 mm and had large absolute errors in the perpendicular plane. Mean absolute RMS errors in reflectance for the fine grain, faceted snow case were 0.09 at l =1 .3mm and 0.14 at l = 1.85 mm. Mean absolute RMS errors for the medium grain, clustered snow were 0.04–0.06 at l =1 .3mm and 0.04–0.06 at l = 1.85 mm. The models for the more spherical medium grain snow had better overall spectral and angular fits than those for the nonspherical fine grain snow. The spherical radii inferred from the surface-area-to-volume ratio from stereological analysis of snow with nonspherical particles have a greater effective path length than the actual snow particles, resulting in underestimates of hemispherical-directional reflectance. INDEX TERMS: 0634 Electromagnetics: Measurement and standards; 1863 Hydrology: Snow and ice (1827); 3360 Meteorology and Atmospheric Dynamics: Remote sensing; KEYWORDS: snow, hemispherical-directional reflectance factor, high resolution Citation: Painter, T. H., and J. Dozier (2004), Measurements of the hemispherical-directional reflectance of snow at fine spectral and angular resolution, J. Geophys. Res., 109, D18115, doi:10.1029/2003JD004458.

Dust radiative forcing in snow of the Upper Colorado River Basin: 2. Interannual variability in radiative forcing and snowmelt rates

forcing ranged from 0 to 214 W m � 2 , with hourly peaks up to 409 W m � 2 . Mean springtime dust radiative forcings across the period ranged from 31 to 49 W m � 2 at the alpine site and 45 to 75 W m � 2 at the subalpine site, in turn shortening snow cover duration by 21 to 51 days. The dust-advanced loss of snow cover (days) is linearly related to total dust concentration at the end of snow cover, despite temporal variability in dust exposure and solar irradiance. Under clean snow conditions, the temperature increases shorten snow cover by 5–18 days, whereas in the presence of dust they only shorten snow duration by 0–6 days. Dust radiative forcing also causes faster and earlier peak snowmelt outflow with daily mean snowpack outflow doubling under the heaviest dust conditions. On average, snow cover at the towers is lost 2.5 days after peak outflow in dusty conditions, and 1–2 weeks after peak outflow in clean conditions.

Instruments and Methods Contact spectroscopy for determination of stratigraphy of snow optical grain size

We present a technique for in situ measurement of the vertical and spatial stratigraphic distribution of snow optical grain size with a coupled contact illumination probe and field spectroradiometer. Accurate measurements of optical-equivalent grain size are critical for modeling radiative properties of snow such as spectral albedo and microwave emission. Measurements of the spectral reflectance of the snow-pit surface are made at 2 cm intervals in the vertical plane under constant illumination and view geometries. We invert the integral of the continuum normalization of the ice absorption feature with maximum at 1.03 mm wavelength for optical-equivalent grain size using the validated model of Nolin and Dozier (2000) that has accuracy of � 10-50 mm across the grain-size range 50-900 mm. Results are presented for an alpine site in southwest Colorado, USA, across the ablation season and for a Greenland ice-sheet site at the onset of snowmelt. These results suggest that traditional measurements of grain size using a hand lens are nearly accurate only for rounded grains (R 2 ¼ 0.41, rmse ¼ 160 mm); for polycrystals and faceted grains the hand-lens approach is very inaccurate (R 2 ¼ 0.03 and 0.24, rmse ¼ 1206 and 1010 mm, respectively). We demonstrate an order-of- magnitude improvement in modeling of shortwave spectral albedo and net shortwave flux with contact spectroscopy measurements of grain-size stratigraphy over those from a hand lens.

Incorporating remotely-sensed snow albedo into a spatially-distributed snowmelt model

Basin-average albedo estimated from remotely-sensed Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS) data specific to the catchment typically differed by 20% from albedo estimated using a common snow-age-based empirical relation. In some parts of the basin, differences were as large as 0.31. Using the AVIRIS albedo estimates in a distributed snowmelt model that explicitly includes net solar radiation resulted in a much more accurate estimate of the timing and magnitude of snowmelt as compared to the same model with the empirical albedo (R2 of 0.73 versus 0.59 and magnitude error of 2% versus 36% . Model improvement was most significant in areas and at times where incident solar radiation was relatively high and temperatures low. Copyright 2004 by the American Geophysical Union.

Biological consequences of earlier snowmelt from desert dust deposition in alpine landscapes

Dust deposition to mountain snow cover, which has increased since the late 19th century, accelerates the rate of snowmelt by increasing the solar radiation absorbed by the snowpack. Snowmelt occurs earlier, but is decoupled from seasonal warming. Climate warming advances the timing of snowmelt and early season phenological events (e.g., the onset of greening and flowering); however, earlier snowmelt without warmer temperatures may have a different effect on phenology. Here, we report the results of a set of snowmelt manipulations in which radiation-absorbing fabric and the addition and removal of dust from the surface of the snowpack advanced or delayed snowmelt in the alpine tundra. These changes in the timing of snowmelt were superimposed on a system where the timing of snowmelt varies with topography and has been affected by increased dust loading. At the community level, phenology exhibited a threshold response to the timing of snowmelt. Greening and flowering were delayed before seasonal warming, after which there was a linear relationship between the date of snowmelt and the timing of phenological events. Consequently, the effects of earlier snowmelt on phenology differed in relation to topography, which resulted in increasing synchronicity in phenology across the alpine landscape with increasingly earlier snowmelt. The consequences of earlier snowmelt from increased dust deposition differ from climate warming and include delayed phenology, leading to synchronized growth and flowering across the landscape and the opportunity for altered species interactions, landscape-scale gene flow via pollination, and nutrient cycling.