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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lead isotopic compositions of airborne particulates collected from snow and from dry deposition in the East River Watershed, Colorado and at the Southern Sierra Critical Zone Observatory, California

The data set consists of lead (Pb) isotopic ratios (206Pb/207Pb and 208Pb/207Pb, as well as 206Pb/204Pb, 207Pb/204Pb, 208Pb/204Pb) for particulate samples collected from snow and dry deposition. This was part of a study (O’Day et al. 2020) that was looking at the speciation of phosphorous in splits of these samples to evaluate the flux and bio-availability of phosphorous to the mountain sites in the study. The Pb isotopic data allow sourcing of long-range transported Pb, specifically the fraction of Pb sourced in Asia, and so a comparison of the relative distances of PM sources between the high and low elevation sites. Samples were collected at the East River Watershed, CO (dry deposition collected over Sept.-Oct. 2016, show sampling winter 2017) and at the Southern Sierra Critical Zone Observatory (dry deposition collected over Sept-Nov 2016, July-Sept 2017, June-July 2017). The data includes Pb concentration data, as well as calculated fraction of the Pb sourced in Asia. This data set was published in part in O’Day et al. (2020) Phosphorus Speciation in Atmospherically Deposited Particulate Matter and Implications for Terrestrial Ecosystem Productivity. ES&T, https://dx.doi.org/10.1021/acs.est.9b06150

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data used for Figure 3 of the Nature Reviews Earth and Environment (NREE) paper: "A low-to-no snow future and its impacts on water resources in the western United States

In order to synthesize western United States snowpack projections, this dataset contains the results of 18 peer-review journal articles over three periods of interest (2025-2049, 2050-2074, and 2075-2099) and over 4 mountain ranges (Cascades, Sierra Nevada, Rockies, Wasatch/Uinta) in addition to western-US wide projections. Distinction is made by model type (Earth System Models, bias-corrected statistically downscaled Earth System Models, and regional climate models). RCP4.5 and RCP8.5 emission scenarios are considered. Percent snow water equivalent (SWE) loss considers 1 April, peak SWE and/or seasonal SWE. Heterogeneity in projected snowpack changes exists across mountain ranges and for different modeling approaches, but generally indicate agreement in decreases by the end of the century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Transiting Planets Near the Snow Line from Kepler. I. Catalog

We present a comprehensive catalog of cool (period P ≳ 2 yr) transiting planet candidates in the 4 yr light curves from the prime Kepler mission. Most of the candidates show only one or two transits and have largely been missed in the original Kepler Object of Interest catalog. Our catalog is based on all known such candidates in the literature, as well as new candidates from the search in this paper, and provides a resource to explore the planet population near the snow line of Sun-like stars. We homogeneously performed pixel-level vetting, stellar characterization with Gaia parallax and archival/Subaru spectroscopy, and light-curve modeling to derive planet parameters and to eliminate stellar binaries. The resulting clean sample consists of 67 planet candidates whose radii are typically constrained to 5%, in which 23 are newly reported. The number of Jupiter-sized candidates (29 with radius r>8 R{sub ⊕}) in the sample is consistent with the Doppler occurrence. The smaller candidates are more prevalent (23 with 4 4 R{sub ⊕} have systematically higher [Fe/H] than do the Kepler field stars, providing evidence that giant planet–metallicity correlation extends to P>2 yr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River watershed during SPLASH, 2021–2023

Abstract. From autumn 2021 through summer 2023, scientists from the National Oceanic and Atmospheric Administration (NOAA) and partners conducted the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in the East River watershed of Colorado. One objective of SPLASH was to observe the transfer of energy between the atmosphere and the surface, which was done at several locations. Two remote sites were chosen that did not have access to power utilities. These were along the valley floor near the East River in the vicinity of the unincorporated town of Gothic, Colorado. Energy balance measurements were made at these locations using autonomous, single-level flux towers referred to as atmospheric surface flux stations (ASFSs). The ASFSs were deployed on 28 September 2021 at the Kettle Ponds Annex site and on 12 October 2021 at the Avery Picnic site and operated until 19 July and 21 June 2023, respectively. Measurements included basic meteorology; upward and downward longwave and shortwave radiative fluxes and subsurface conductive flux, each at 1 min resolution; 3-D winds from a sonic anemometer and H2O/CO2 from an open-path gas analyzer, both at 20 Hz from which sensible, latent heat, and CO2 fluxes were derived; and profiles of soil properties in the upper 0.5 m (both sites) and temperature profiles through the snow (at Avery Picnic), each reported between 10 min and 6 h. The system uptime was 97 % (Kettle Ponds) and 90 % (Avery Picnic), and collectively 1184 d of data was obtained between the stations. The purpose of this article is to document the ASFS deployment at SPLASH, to document the data acquisition and post-processing of measurements, and to serve as a guide for interested users of the data sets, which are archived at Zenodo (https://doi.org/10.5281/zenodo.10313363, Cox et al., 2023b; https://doi.org/10.5281/zenodo.10327409, Cox et al., 2023c; https://doi.org/10.5281/zenodo.10313894, Cox et al., 2023d; https://doi.org/10.5281/zenodo.10307825, Cox et al., 2023e; https://doi.org/10.5281/zenodo.10310520, Cox et al., 2023f) with the Creative Commons Attribution 4.0 International license.

Cox, Christopher J. (ORCID:0000000322037173)↗
DOE OSTI2024

Algorithmically detected rain-on-snow flood events in different climate datasets: a case study of the Susquehanna River basin

Abstract. Rain-on-snow (RoS) events in regions of ephemeral snowpack – such as the northeastern United States – can be key drivers of cool-season flooding. We describe an automated algorithm for detecting basin-scale RoS events in gridded climate data by generating an area-averaged time series and then searching for periods of concurrent precipitation, surface runoff, and snowmelt exceeding predefined thresholds. When evaluated using historical data over the Susquehanna River basin (SRB), the technique credibly finds RoS events in published literature and flags events that are followed by anomalously high streamflow as measured by gauge data along the river. When comparing four different datasets representing the same 21-year period, we find large differences in RoS event magnitude and frequency, primarily driven by differences in estimated surface runoff and snowmelt. Using dataset-specific thresholds improves agreement between datasets but does not account for all discrepancies. We show that factors such as meteorological forcing and coupling frequency, as well as choice of land surface model, play roles in how data products capture these compound extremes and suggest care is to be taken when climate datasets are used by stakeholders for operational decision-making.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)

Abstract. Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Snow-substrate interface temperature and air temperature for the SALVO 2019 Campaign

The springtime, surface-albedo transition in the Alaskan Arctic and the forcings that determine the duration and nature of that transition are the focus of our Snow ALbedo eVOlution (SALVO I & II) campaign. The SALVO team are assessing the “whys” and “how longs” of the stages of the spring melt during which albedo values drop from 0.8 to 0.1, the largest and most significant change of the year. The near-shore location of the ARM NSA observatory makes this an ideal place to investigate these melt stages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Snow-substrate interface temperature and air temperature for the SALVO 2022 Campaign

The springtime, surface-albedo transition in the Alaskan Arctic and the forcings that determine the duration and nature of that transition are the focus of our Snow ALbedo eVOlution (SALVO I & II) campaign. The SALVO team are assessing the “whys” and “how longs” of the stages of the spring melt during which albedo values drop from 0.8 to 0.1, the largest and most significant change of the year. The near-shore location of the ARM NSA observatory makes this an ideal place to investigate these melt stages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Snow and Surface Water Chemistry and Isotopes in Utqiagvik (Barrow), Alaska, 2013

Data include results from water chemistry and water isotope analyses for samples collected in Utqiagvik (Barrow), Alaska June through September of 2013. Snow and surface water were collected, by hand and using an ISCO sample collector, respectively from locations within the Barrow Environmental Observatory. This dataset includes one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

Remote Sensing of Snow Fields from Earth Satellites

Considerable effort has gone into snow line delineation using available satellite data. Furthermore, increasing emphasis is being put on automated extraction of such information and generation of a useable product for hydrologists. Implications are clear that the impact from future satellite and sensors systems will create an increased demand for computer processing before the data can be used by the hydrologist. If the coarse-resolution, broad spectral band data available from current satellites already create a demand by hydrologists for computer processing of the data, it is obvious there will be an even greater demand for computer analysis and evaluation when the future ERTS data become available.

Baker, D. R.↗