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At least 523 records · Page 29
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 OSTI2025

Micro Rain Radar Pro Data at the Argonne Testbed for Multiscale Observational Science obtained during the CROCUS Urban Integrated Field Laboratory

The Micro Rain Radar Pro (MRR-PRO) is a vertically pointing Ka-band Doppler radar designed to capture the fine-scale structure and evolution of precipitation. By recording the full Doppler spectrum at high temporal and spatial resolution, the MRR-PRO provides insight into both hydrometeor fall velocities and precipitation microphysics. From these spectra, key moments—reflectivity, mean Doppler velocity, spectral width, and rainfall rate—are derived and stored alongside the raw spectral data in CF/Radial 1.4-compliant files. Deployed at the Argonne Testbed for Multiscale Observational Studies (ATMOS) since November 2024, the MRR-PRO delivers vertical profiles at 70 m range resolution extending up to 4.5 km above ground level. These observations enable detailed analyses of precipitation type, intensity, and vertical structure, supporting process-level studies of cloud and precipitation dynamics in diverse weather regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗
DOE OSTI2015

Analysis of Precipitation (Rain and Snow) Levels and Straight-line Wind Speeds in Support of the 10-year Natural Phenomena Hazards Review for Los Alamos National Laboratory

This report provides site-specific return level analyses for rain, snow, and straight-line wind extreme events. These analyses are in support of the 10-year review plan for the assessment of meteorological natural phenomena hazards at Los Alamos National Laboratory (LANL). These analyses follow guidance from Department of Energy, DOE Standard, Natural Phenomena Hazards Analysis and Design Criteria for DOE Facilities (DOE-STD-1020-2012), Nuclear Regulatory Commission Standard Review Plan (NUREG-0800, 2007) and ANSI/ ANS-2.3-2011, Estimating Tornado, Hurricane, and Extreme Straight-Line Wind Characteristics at Nuclear Facility Sites. LANL precipitation and snow level data have been collected since 1910, although not all years are complete. In this report the results from the more recent data (1990–2014) are compared to those of past analyses and a 2004 National Oceanographic and Atmospheric Administration report. Given the many differences in the data sets used in these different analyses, the lack of statistically significant differences in return level estimates increases confidence in the data and in the modeling and analysis approach.

58 GEOSCIENCES↗
DOE OSTI2017

Brazil-USA Collaborative Research: Modifications by Anthropogenic Pollution of the Natural Atmospheric Chemistry and Particle Microphysics of the Tropical Rain Forest During the GoAmazon Intensive Operating Periods (IOPs)

Manaus, a city of nearly two million people, represents an isolated urban area having a distinct urban pollution plume within the otherwise pristine Amazon Basin. The plume has high concentrations of oxides of nitrogen and sulfur, carbon monoxide, particle concentrations, and soot, among other pollutants. Critically, the distinct plume in the setting of the surrounding tropical rain forest serves as a natural laboratory to allow direct comparisons between periods of pollution influence to those of pristine conditions. The funded activity of this report is related to the Brazil-USA collaborative project during the two Intensive Operating Periods (wet season, 1 Feb - 31 Mar 2014; dry season, 15 Aug - 15 Oct 2014) of GoAmazon2014/5. The project addresses key science questions regarding the modification of the natural atmospheric chemistry and particle microphysics of the forest by present and future anthropogenic pollution. The first objective of the project was to understand and quantify the interactions of biogenic and anthropogenic emissions with respect to the production of secondary organic material. In clean conditions in the Amazon basin, secondary organic material dominates the diameter distribution of the submicron particles. How and why is the diameter distribution shifted by pollution? The second objective followed from the first in that, although the diameter distribution is dominated by secondary organic material, the actual source of new particle production remains uncertain (i.e., the number concentration). The second objective was to test the hypothesis that new particles under natural conditions are produced as a result of evaporation of primary particles emitted by fungal spores as well as to investigate any shifts in this mechanism under pollution conditions, e.g., in consequence to the high concentrations of SO 2 in the pollution plume. Combined, the number-diameter distribution is the key connection to upscaling to the effects of aerosol particles on clouds and climate. Understanding this upscaling under clean and pollution conditions, including differences, was the third objective.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Brazil-USA Collaborative Research: Modifications by Anthropogenic Pollution of the Natural Atmospheric Chemistry and Particle Microphysics of the Tropical Rain Forest During the GoAmazon Intensive Operating Periods (IOPs)

Manaus, a city of nearly two million people, represents an isolated urban area having a distinct urban pollution plume within the otherwise pristine Amazon Basin. The plume has high concentrations of oxides of nitrogen and sulfur, carbon monoxide, particle concentrations, and soot, among other pollutants. Critically, the distinct plume in the setting of the surrounding tropical rain forest serves as a natural laboratory to allow direct comparisons between periods of pollution influence to those of pristine conditions. The funded activity of this report is related to the Brazil-USA collaborative project during the two Intensive Operating Periods (wet season, 1 Feb - 31 Mar 2014; dry season, 15 Aug - 15 Oct 2014) of GoAmazon2014/5. The project addresses key science questions regarding the modification of the natural atmospheric chemistry and particle microphysics of the forest by present and future anthropogenic pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Brazil-USA Collaborative Research: Modifications by Anthropogenic Pollution of the Natural Atmospheric Chemistry and Particle Microphysics of the Tropical Rain Forest During the GoAmazon Intensive Operating Periods (IOPs)

Manaus, a city of nearly two million people, represents an isolated urban area having a distinct urban pollution plume within the otherwise pristine Amazon Basin. The plume has high concentrations of oxides of nitrogen and sulfur, carbon monoxide, particle concentrations, and soot, among other pollutants. Critically, the distinct plume in the setting of the surrounding tropical rain forest serves as a natural laboratory to allow direct comparisons between periods of pollution influence to those of pristine conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Computational Analysis of Water Film Thickness During Rain Events for Assessing Hydroplaning Risk Part 2: Rough Road Surfaces

Hydroplaning occurs when a water film forms on a road during a rain event and vehicles are traveling at a speed that does not provide sufficient time for the tires to push the water film out of the tire path. Under these conditions, the tire loses contact with the road and the driver may lose control over the vehicle. The present study is a part of a multiyear research effort aimed at gaining a better understanding of the factors that contribute to hydroplaning risk in order to minimize the occurrence of hydroplaning accidents. Three-dimensional computational fluid dynamics (CFD) analysis was used to investigate the water film thickness on multilane roads, one of the key parameters in evaluating hydroplaning risk. In the first part of the study, water films forming on wide roadways, i.e. multilane highways with 2, 4, and 6 lanes per side, were analyzed, with varying cross slope, longitudinal slope, and rainfall rate. Roadways with and without curbs and drainage were included in the analysis. The analysis in the first part was limited to nearly smooth asphalt or concrete surfaces because the maximum roughness height that can be specified in a CFD model using wall functions to determine shear stress at the road surface boundary is one half the thickness of computational cell layer adjacent to the boundary and the need to resolve the vertical velocity distribution in a thin water film requires cell layers that are a fraction of a millimeter thick. In this part of the study, the analysis was extended to consider the influence of pavement roughness over a range extending up 3.6 mm on the development of water film thickness. Various methods of modeling roughness were investigated and are presented: the roughness height model, a meshed-out geometry of the macrotexture of the pavement, and a porous region model. The computational results were analyzed and compared with experimental measurements performed by Gallaway et al.

42 ENGINEERING↗
DOE OSTI2019

When the Rain Stops: Drought on Subseasonal and Longer Timescales

The Aspen Global Change Institute hosted a technical science workshop, “When the Rain Stops: Drought on Subseasonal and Longer Timescales,” on September 9-14, 2018 in Aspen, CO. Gerald Meehl (NCAR), Roger Pulwarty (NOAA), and Angeline Pendergrass (NCAR) served as co-chairs for the workshop. The meeting included the participation of 25 scientists for a total of 125 participant days. The workshop resulted in agreement on definitions for both operational and research/prediction uses. Workshop participants are in the process of testing these definitions within their work on drought modeling, and impacts assessment, with the intention that these definitions can then be evaluated for CMIP6 (and incorporated into ESMValTool), as well as for the IPCC AR6 from observations, models, and impacts. Findings from the workshop and follow on experiments are in the process of being summarized and submitted for publication in a high profile peer-reviewed journal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2025

Micro Rain Radar / Reviewed Data

This dataset contains the Micro Rain Radar data that have been reviewed by the mentor and calibrated against the Parsivel on the barge.

17 WIND ENERGY↗
DOE OSTI2016

DYNAMICS OF CORONAL RAIN AND DESCENDING PLASMA BLOBS IN SOLAR PROMINENCES. II. PARTIALLY IONIZED CASE

Coronal rain clumps and prominence knots are dense condensations with chromospheric to transition region temperatures that fall down in the much hotter corona. Their typical speeds are in the range 30–150 km s{sup −1} and of the order of 10–30 km s{sup −1}, respectively, i.e., they are considerably smaller than free-fall velocities. These cold blobs contain a mixture of ionized and neutral material that must be dynamically coupled in order to fall together, as observed. We investigate this coupling by means of hydrodynamic simulations in which the coupling arises from the friction between ions and neutrals. The numerical simulations presented here are an extension of those of Oliver et al. to the partially ionized case. We find that, although the relative drift speed between the two species is smaller than 1 m s{sup −1} at the blob center, it is sufficient to produce the forces required to strongly couple charged particles and neutrals. The ionization degree has no discernible effect on the main results of our previous work for a fully ionized plasma: the condensation has an initial acceleration phase followed by a period with roughly constant velocity, and, in addition, the maximum descending speed is clearly correlated with the ratio of initial blob to environment density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Explosive Chromospheric Evaporation and Warm Rain in a C3.1 Flare Observed by IRIS, Hinode/EIS, and RHESSI

IRIS and EIS observed a GOES C3.1 flare in stare mode on 2014 March 15. The GOES flare started at 00:21:35 and peaked at 00:26:30 UT. The IRIS slit pointed near the center of the flare, while the EIS slit pointed 35{sup ′′} to its west. About 4 minutes before the GOES flare start, the IRIS C ii and Si iv intensities became (and remained) greater than their pre-flare averages, indicating that the flare had begun and that the chromosphere and transition region were involved. IRIS first detected blueshifted Fe xxi emission at 00:22:42 UT, by which time the C ii and Si iv intensities had increased by factors around 100 and their profiles were redshifted. Simultaneous, cospatial blueshifted Fe xxi emission with redshifted C ii and Si iv emission indicates explosive chromospheric evaporation. EIS spectra reveal Fe xxiii emission that is too weak to measure velocities, and intensity enhancements by factors about 1.7 in the Fe xiv and Fe xvi emission. Lines from both of these coronal ions show redshifts ≈9 km s{sup −1} around 00:24:00 UT, and the Fe xiv 264.7/274.2 intensity ratio reveals an increase of n {sub e} from (1.03±0.20)×10{sup 9} before to (3.58±0.68)×10{sup 9} cm{sup −3} during the flare. The redshifted coronal line emission and increased n {sub e} are consistent with warm rain falling and accumulating in the remote area observed by EIS. A fit to the RHESSI hard X-ray spectrum yields a nonthermal energy injection rate of 4.9×10{sup 26} erg s{sup −1}, from which we estimate a HXR beam energy flux range consistent with explosive evaporation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S =0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ , exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.

54 ENVIRONMENTAL SCIENCES↗
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↗