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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Additional Contributions to the Development of the New Snow-Physics Scheme for SSiB

The Simplified Simple Biosphere Model (SSiB) had a well-documented problem with snowmelt timing and infiltration. A new snow-physics scheme was developed for use in SSIB. In this, the snow layer is separated from the soil, with its own energy budget and temperature. Solar energy reaching the top of the snowpack is divided into three parts: one, reflected by the snow; two, absorbed by the snow; and three, transmitted to the ground following a simple extinction relation. Heat is exchanged between the ground and snow by conduction and by radiation through an arbitrary air-gap between them. In the GSWP exercise using the GEWEX ISLSCP Initiative I forcing data (hereafter "offline"), it was found that the new snow scheme ameliorated a significant fraction of snowmelt time-delay as compared to observations from satellite. It also produced warmer ground temperatures under the snowpack, which allowed realistic meltwater infiltration, resulting in better simulated spring soil moisture recharge and peak runoff amount as compared to observations. An ensemble of six June-July-August (JJA) simulations for 1987 and 1988 were performed with the NASA Goddard GEOS II GCM coupled with the new snow-physics SSIB using new initial soil moisture (ISM) from the offline simulations. The GCM produced more realistic precipitation in northern regions that had large snowmelt and wetter ISM in response to better snow-physics, as compared to simulations with ISM without the new snow scheme. The new SSiB-GCM also increased the interannual precipitation signal in the Indian monsoon region, resulting from changes in ISM in the Himalayas and central Asia.

Mocko, David M.↗
NASA NTRS1990

Comparison of measurements and theory for backscatter from bare and snow-covered saline ice

C-band radar backscatter measurements were made on artificially grown sea ice during the winters of 1987-1988 and 1988-1989. These measurements were made on smooth, rough, and snow-covered saline ice. The measured sigma-deg(theta) of smooth saline ice (rms height less than 0.05 cm) disagreed with small perturbation method (SPM) surface scattering predictions. Using physical parameters of the ice in a simple layer model, it us shown that this discrepancy can be explained by scattering from beneath the surface. A thin (7-cm) dry snow cover had a significant influence on backscatter from the smooth ice sheet. This influence was due to scattering from particles within the snow, and can be predicted by a commonly used empirical layer model for snow. The results of backscatter measurements of a moderately rough saline ice sheet were found to agree with SPM predictions.

Bredow, Jonathan W.↗
NASA NTRS1985

Studies on Physical Properties of Snow Based on Multi Channel Microwave Radiometer

The analysis of the data observed over a snow field with a breadboard model of MSR (microwave scanning radiometer) to be installed in MOS-1 (Marine Observation Satellite-1) indicates that: (1) the influence of incident angle on brightness temperature is larger in horizontal polarization component than in vertical polarization component. The effect of incident angle depends upon the property of snow with larger value for dry snow; (2) the difference of snow surface configuration consisting of artifically made parallel ditches of 5 cm depth and 5 cm width with spacing of 10 and 30 cm respectively which are oriented normal to electrical axis do not affect brightness temperature significantly; and (3) there is high negative correlation between brightness temperature and snow depth up to the depth of 70 cm which suggests that the snow depth can be measured with a two channel microwave radiometer up to this depth.

Tsuchiya, K.↗
NASA NTRS1993

Polarimetric backscattering from sea ice

Polarimetric backscattering from sea ice is presented. Theoretical models for backscattering are first presented for various ice types. Then, theoretical results are compared with experimental data for new thin ice, first-year ice, and multi-year ice. Sea ice is modeled as a layer medium containing random scatterers and rough interfaces. For multi-year sea ice with snow cover, the sea ice layer is modeled as an ice background with embedded spheroidal air bubbles and the snow layer as air with ice grains. The hummocky topography on multi-year ice is characterized by a Gaussian distribution which has an averaging effect on backscattering coefficients. First-year sea ice is described by an ice medium hosting ellipsoidal brine inclusions. These inclusions are oriented preferentially in the vertical direction due to the columnar structure of first-year sea ice. Azimuthally, the orientation of the brine pockets are random corresponding to the random c-axes in sea ice, unless the axes are oriented by sea currents. For thin ice in newly opened leads, it has been observed that there exists a thin brine layer with very high salinity on the top surface of the new ice. This brine layer is depicted as a medium with high permittivity which can significantly affect electromagnetic scattering signatures from the lower thin ice layer, with a higher fractional volume of brine inclusions due to higher salinity as compared to thick first-year sea ice. The rough medium interfaces are described as Gaussian rough surfaces characterized by root-mean-square heights and surface correlation lengths. The contribution from rough surface, calculated under the Kirchhoff approximation or small perturbation method, is assumed to be independent from volume scattering. The total loss including absorption and scattering losses in the scattering media is represented by the imaginary part of effective permittivity obtained from the strong fluctuation theory. The polarimetric scattering coefficients for different ice types are then derived under the distorted Born approximation.

Nghiem, S. V.↗
NASA NTRS2019

Applying the Dark Target Aerosol Algorithm with Advanced Himawari Imager Observations During the KORUS-AQ Field Campaign

For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The Korean–United States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during May–June 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here,we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD in-creases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70t hat may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40 degree glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, reevaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm.

Gupta, Pawan↗
NASA NTRS1971

Emission characteristics of snow and ice in the microwave range

Some results are presented of a two year investigation on microwave emissions from snow. Included in the investigation were: theoretical studies; laboratory measurements of electrical properties of snow and similar materials; numerical modelling of hypothetical and real snowpacks; analysis of microwave data obtained on everflights; and quantative measurements of natural and artificial snowpacks made in the field. Results indicate that a fairly simple combination of microwave polarizations and frequencies can ultimately be used to monitor the water equivalent and free-water content as well as the distribution of snow. This understanding may also shed light on the physics of microwave emission from other wet, granular, layered media.

Meier, M. F.↗
NASA NTRS1975

A cost-effectiveness comparison of existing and Landsat-aided snow water content estimation systems

This study describes how Landsat imagery can be cost-effectively employed to augment an operational hydrologic model. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model presently used by the California Department of Water Resources. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the Landsat-aided approach.

Sharp, J. M.↗
NASA NTRS2022

Development of a “Nature Run” for Observing System Simulation Experiments (OSSEs) for Snow Mission Development

Snow is a fundamental component of global and regional water budgets, particularly in mountainous areas and regions downstream that rely on snowmelt for water resources. Land surface models (LSMs) are commonly used to develop spatially distributed estimates of snow water equivalent (SWE) and runoff. However, LSMs are limited by uncertainties in model physics and parameters, among other factors. In this study, we describe the use of model calibration tools to improve snow simulations within the Noah-MP LSM as the first step in an observing system simulation experiment (OSSE). Noah-MP is calibrated against the University of Arizona (UA) SWE product over a western Colorado domain. With spatially varying calibrated parameters, we run calibrated and default Noah-MP simulations for water years 2010–20. By evaluating both simulations against the UA dataset, we show that calibration decreases domain averaged temporal RMSE and bias for snow depth from 0.15 to 0.13 m and from −0.036 to −0.0023 m, respectively, and improves the timing of snow ablation. Increased snow simulation performance also improves estimates of model-simulated runoff in four of six study basins, though only one has statistically significant improvement. Spatially distributed Noah-MP snow parameters perform better than default uniform values. We demonstrate that calibrating variables related to snow albedo calculations and rain–snow partitioning, among other processes, is a necessary step for creating a nature run that reasonably approximates true snow conditions for the OSSEs. Additionally, the inclusion of a snowfall scaling term can address biases in precipitation from meteorological forcing datasets, further improving the utility of LSMs for generating reliable spatiotemporal estimates of snow.

Melissa L. Wrzesien↗
NASA NTRS1984

Effects of nontropical forest cover on climate

The albedo of a forest with snow on the ground is much less than that of snow-covered low vegetation such as tundra. As a result, simulation of the Northern Hemisphere climate, when fully forested south of a suitably chosen taiga/tundra boundary (ecocline), produces a hemispheric surface air temperature 1.9 K higher than that of an earth devoid of trees. Using variations of the solar constant to force climate changes in the GLAS Multi-Layer Energy Balance Model, the role of snow-albedo feedback in increasing the climate sensitivity to external perturbations is reexamined. The effect of snow-albedo feedback is found to be significantly reduced when a low albedo is used for snow over taiga, south of the fixed latitude of the ecocline. If the ecocline shifts to maintain equilibrium with the new climate - which is presumed to occur in a prolonged perturbation when time is sufficient for trees to grow or die and fall - the feedback is stronger than for a fixed ecocline, especially at high latitudes. However, this snow/vegetation-albedo feedback is still essentially weaker than the snow-albedo feedback in the forest-free case. The loss of forest to agriculture and other land-use would put the present climate further away from that associated with the fully forested earth south of the ecocline and closer to the forest-free case. Thus, the decrease in nontropical forest cover since prehistoric times has probably affected the climate by reducing the temperatures and by increasing the sensitivity to perturbations, with both effects more pronounced at high latitudes.

Otterman, J.↗
NASA NTRS2024

Using Commercial Satellite Imagery to Reconstruct 3 m and Daily Spring Snow Water Equivalent

Snow water equivalent (SWE) distribution at fine spatial scales (≤10 m) is difficult to estimate due to modeling and observational constraints. However, the distribution of SWE throughout the spring snowmelt season is often correlated to the timing of snow disappearance. Here, we show that snow cover maps generated from PlanetScope's constellation of Dove Satellites can resolve the 3 m date of snow disappearance across seven alpine domains in California and Colorado. Across a 5-year period (2019–2023), the average uncertainty in the date of snow disappearance, or the period of time between the last date of observed snow cover and the first date of observed snow absence, was 3 days. Using a simple shortwave-based snowmelt model calibrated at nearby snow pillows, the PlanetScope date of snow disappearance could be used to reconstruct spring SWE. Relative to lidar SWE estimates, the SWE reconstruction had a spatial coefficient of correlation of 0.75, and SWE spatial variability that was biased by 9%, on average. SWE reconstruction biases were then improved to within 0.04 m, on average, by calibrating snowmelt rates to track the spring temporal evolution of fractional snow cover observed by PlanetScope, including fractional snow cover over the full modeling domain, and across domain subsections where snowmelt rates may differ. This study demonstrates the utility of fine-scale and high-frequency optical observations of snow cover, and the simple and annually repeatable connections between snow cover and spring snow water resources in regions with seasonal snowpack.

Justin M Pflug↗
NASA NTRS2017

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment −PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

forecasting↗
NASA NTRS1988

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Neeman, Binyamin U.↗
NASA NTRS1975

A multidisciplinary study of earth resources imagery of Australia, Antarctica and Papua, New Guinea

The author has identified the following significant results. A thirteen category recognition map was prepared, showing forest, water, grassland, and exposed rock types. Preliminary assessment of classification accuracies showed that water, forest, meadow, and Niobrara shale were the most accurately mapped classes. Unsatisfactory results, were obtained in an attempt to discrimate sparse forest cover over different substrates. As base elevation varied from 7,000 to 13,000 ft, with an atmospheric visibility of 48 km, no changes in water and forest recognition were observed. Granodiorite recognition accuracy decreased monotonically as base elevation increased, even though the training set location was at 10,000 ft elevation. For snow varying in base elevation from 9400 to 8420 ft, recognition decreases from 99% at the 9400 ft training set elevation to 88% at 8420 ft. Calculations of expected radiance at the ERTS sensor from snow reflectance measured at the site and from Turner model calculations of irradiance, transmission and path radiance, reveal that snow signals should not be clipped, assuming that calculations and ERTS calibration constants were correct.

Fisher, N. H.↗
NASA NTRS1981

The albedo of snow for partially cloudy skies

The albedo of snow is defined as the ratio of reflected to incident solar energy, and it is an important parameter in the earth's radiation budget analysis and in the study of snowpack's thermal conditions. An approximate model for calculating the incident spectral flux for partially cloudy skies is presented. The input parameters for the calculation are atmospheric precipitable water, turbidity, ozone content, surface pressure, the optical thickness of clouds, and the grain size of snow crystals. The spectral snow reflectance model considers both specular surface reflection and volumetric multiple scattering. The surface reflection is calculated by using a crystal-shape-dependent bidirectional reflectance distribution function; the volumetric multiple scattering is calculated by using a crystal-size-dependent approximate solution in the radiative transfer equation. The model yields spectral and integrated solar flux and snow reflectance as a function of solar elevation and fractional cloud-cover. The illustrative insolation and albedo values were obtained from spectral reflectance and incident flux for representative parameters of Antarctic coastal regions. A simple relationship between grain size and the overcast albedo was obtained. For a set of grain size and shape, the albedo as a function of solar elevation and fractional cloud cover was tabulated.

Choudhury, B. J.↗
NASA NTRS1997

Microphysical Retrievals Over Stratiform Rain Using Measurements from an Airborne Dual-Wavelength Radar-Radiometer

The need to understand the complementarity of the radar and radiometer is important not only to the Tropical Rain Measuring Mission (TRMM) program but to a growing number of multi-instrumented airborne experiment that combine single or dual-frequency radars with multichannel radiometers. The method of analysis used in this study begins with the derivation of dual-wavelength radar equations for the estimation of a two-parameter drop size distribution (DSD). Defining a "storm model" as the set of parameters that characterize snow density, cloud water, water vapor, and features of the melting layer, then to each storm model there will usually correspond a set of range-profiled drop size distributions that are approximate solutions of the radar equations. To test these solutions, a radiative transfer model is used to compute the brightness temperatures for the radiometric frequencies of interest. A storm model or class of storm models is considered optimum if it provides the best reproduction of the radar and radiometer measurements. Tests of the method are made for stratiform rain using simulated storm models as well as measured airborne data. Preliminary results show that the best correspondence between the measured and estimated radar profiles usually can be obtained by using a moderate snow density (0.1-0.2 g/cu cm), the Maxwell-Garnett mixing formula for partially melted hydrometeors (water matrix with snow inclusions), and low to moderate values of the integrated cloud liquid water (less than 1 kg/sq m). The storm-model parameters that yield the best reproductions of the measured radar reflectivity factors also provide brightness temperatures at 10 GHz that agree well with the measurements. On the other hand, the correspondence between the measured and modeled values usually worsens in going to the higher frequency channels at 19 and 34 GHz. In searching for possible reasons for the discrepancies, It is found that changes in the DSD parameter Mu, the radar constants, or the path-integrated attenuation can affect the high frequency channels significantly. In particular, parameters that cause only modest increases in the median mass diameter of the snow, and which have a minor effect on the radar returns or the low frequency brightness temperature, can produce a strong cooling of the 34 GHz brightness temperature.

Meneghini, Robert↗
NASA NTRS2010

HIMALA: Climate Impacts on Glaciers, Snow, and Hydrology in the Himalayan Region

Glaciers are the largest reservoir of freshwater on Earth, supporting one third of the world s population. The Himalaya possess one of the largest resources of snow and ice, which act as a freshwater reservoir for more than 1.3 billion people. This article describes a new project called HIMALA, which focuses on utilizing satellite-based products for better understanding of hydrological processes of the river basins of the region. With support from the US Agency for International Development (USAID), the International Centre for Integrated Mountain Development (ICIMOD), together with its partners and member countries, has been working on the application of satellite-based rainfall estimates for flood prediction. The US National Aeronautics and Space Administration (NASA) partners are working with ICIMOD to incorporate snowmelt and glacier melt into a widely used hydrological model. Thus, through improved modeling of the contribution of snow and ice meltwater to river flow in the region, the HIMALA project will improve the ability of ICIMOD and its partners to understand the impact of weather and climate on floods, droughts, and other water- and climate-induced natural hazards in the Himalayan region in Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal, and Pakistan.

Brown, Molly Elizabeth↗
NASA NTRS1975

A comparison of operational and LANDSAT-aided snow water content estimation systems

How LANDSAT imagery can be cost effectively employed to augment an operational hydrologic model is described. Attention is directed toward the estimation of snow water content, a major predictor variable in the volumetric runoff forecasting model. A stratified double sampling scheme is supplemented with qualitative and quantitative analyses of existing operations to develop a comparison between the existing and satellite-aided approaches to snow water content estimation. Results show a decided advantage for the LANDSAT-aided approach.

Sharp, J. M.↗
NASA NTRS1973

Break-up characteristics of Chena River Basin

The author has identified the following significant results. Results from snowmelt model were obtained showing the decreasing changes in snow depth for four elevational ranges in the Chena River Basin. This model is based on the energy balance of the snowpack and the results are shown on attached figures. Also, the measured hydrographs for two stations on the Chena River are shown. The next phase of the study will be to analyze the model using both ERTS-1 imagery and measured field values.

Carlson, R. F.↗