Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “rain”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High Vapor Pressure Deficit Decreases the Productivity and Water Use Efficiency of Rain‐Induced Pulses in Semiarid Ecosystems

Abstract Intermittent rain events drive dynamic pulses of carbon and water exchange in many arid and semiarid ecosystems. Although soil moisture is known to control these pulses, the effect of atmospheric dryness on pulses is not well documented. Here we hypothesized that vapor pressure deficit ( VPD ) modulates net ecosystem production ( NEP ) and ecosystem‐scale water use efficiency ( WUE ) during pulse events due to its effects on canopy stomatal conductance and evapotranspiration. We quantified relationships between VPD and carbon and water exchange during growing season rain events and tested their generality across four semiarid flux sites with varied vegetation in the southwest United States. Across grassland, shrubland, and savanna sites, we found that high VPD during pulses suppressed ecosystem photosynthesis and surface conductance to a greater degree than respiration or evapotranspiration, particularly when soil moisture was high. Thus, periods of high VPD were associated with a 13–64% reduction in NEP and an 11–25% decrease in WUE , relative to moderate VPD conditions. Sites dominated by shrubs with the C3 photosynthetic pathway were more sensitive to VPD than sites dominated by C4 grasses. We found that a 1 kPa increase in VPD reduced the average NEP of pulse events by 13–56%, which illustrates the potential for projected increases in atmospheric demand to reduce the net productivity of semiarid ecosystems.

Roby, Matthew C.↗
DOE OSTI2022

Peak Rain Rate Sensitivity to Observed Cloud Condensation Nuclei and Turbulence in Continental Warm Shallow Clouds During CACTI

Abstract Warm clouds strongly affect Earth's energy budget but remain imperfectly represented in climate models, partly due to the complexity and covariability of relevant processes influencing warm rain. This work presents a detailed analysis of different factors affecting rain rate peak intensity (RR) in continental warm clouds. Clouds were identified with vertically pointing radar and lidar observations and categorized via a temperature‐based cloud type classification algorithm from which warm clouds were isolated. Observations and retrievals of liquid water path (LWP), cloud condensation nuclei concentration (N CCN ), cloud depth, and cloud duration of more than 3,000 separate warm clouds sampled during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign are analyzed in this work. Multiple linear regression (MLR) and random forest (RF) models are applied to assess the relative impact of these variables on RR. Overall, RR tends to increase as cloud depth, LWP, and cloud duration increase, or N CCN decreases. Cloud depth affects RR the most while N CCN impacts it the least. When considering over 170 warm clouds observed at least 1 hr in which in‐cloud turbulence is retrieved, the effect of N CCN on RR remains most likely suppressive, but it is not significant at a 75% level for MLR and is highly uncertain for RF. The impact of in‐cloud turbulence depends on the moment and location it is sampled. Cloud base turbulence around the time of RR suppresses RR, while cloud top turbulence effects are inconclusive. Possible difficulties in isolating robust CCN and turbulence effects on RR are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Interconnection of Aerosol‐Cloud Interactions and Cloud Feedback Through Warm Rain Process

Recent research has revealed a correlation within the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations: models exhibiting more pronounced warming due to positive cloud feedback simultaneously show enhanced cooling from aerosol‐cloud interactions (ACI). However, the interplay between ACI and cloud feedback is not well understood in these models. Our study addresses this gap by modifying the autoconversion rate in two Earth system models (ESMs), elucidating how ACI could connect with cloud feedback through the warm rain process. We find that higher autoconversion rates, which are associated with stronger ACI, suppress the increase in cloud liquid water path (LWP) and cloud optical depth with warming by enhancing the precipitation efficiency over the extratropical regions, leading to a larger positive cloud feedback. This study offers new insights into the compensatory mechanism between ACI and cloud feedback through the warm rain process and highlights the importance of constraining the autoconversion parameterization in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impacts of Bulk Microphysics Scheme Structural Choices on Simulations of Rain Initiation Through Drop Coalescence

This study examines how different structural choices in bulk microphysics schemes impact the simulation of warm rain initiation. A single liquid category (SLC) approach prognosing up to four moments of a single drop size distribution (DSD) is compared to the traditional two-category, two-moment approach with separate DSDs for cloud and rain (four total prognostic variables). Different methods for calculating tendencies of the prognostic variables from drop collision-coalescence are also tested: a discretized numerical-integration approach, machine learning via neural networks, lookup tables, and traditional power law fits. Relative to simulations using a bin microphysics model, SLC gives smaller error overall than the two-category approach when numerical integration is used to calculate the collision-coalescence tendencies for both. Replacing the numerical integration with a pre-computed lookup table reduces computational cost with little loss of accuracy. However, using fitted power laws with SLC to represent the collision-coalescence tendencies substantially reduces accuracy and leads to an order of magnitude increase in error. It is also demonstrated that with SLC, reasonably accurate solutions are obtained using only three prognostic moments, while a two-moment SLC scheme leads to substantial error. Overall, both the choice of prognostic moments (e.g., SLC vs. two-category) and method to calculate the collision-coalescence tendencies are important to consider for minimizing errors in bulk schemes. SLC with a sufficiently detailed calculation of the collision-coalescence tendencies provides accurate solutions for a reasonable computational cost, providing a viable alternative to the traditional two-category, two-moment approach for bulk microphysics.

320 (cloud physics and chemistry)↗
DOE OSTI2026

Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest

Water transit times strongly influence water quality, temperature, and seasonal hydrologic response of river systems. How water transit times may shift under future climates remains unconstrained, especially in mountainous regions experiencing rapid snowpack declines. Here, we estimated historical (2006–2013) and future (2086–2093) water transit times in five headwater catchments within the U.S. Pacific Northwest using sequential precipitation input tagging within the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model. Our results indicate water transit times are 18% (35–64 days) faster on average under the Representative Carbon Pathways (RCP) 8.5 climate scenario due to shifts in rain-snow partitioning, with higher fractions of younger water in the wet season and older water in the dry season. These results suggest shifts in rain-snow partitioning in snowmelt dominated catchments of the Pacific Northwest will shorten water transit times leading to likely impacts on regional water quality, temperature, and hydrologic seasonality.

Butler, Zachariah [Oregon State Univ., Corvallis, ↗
DOE OSTI2023

Observed increase in the peak rain rates of monsoon depressions

Most extreme precipitation in the densely populated region of central India is produced by atmospheric vortices called monsoon lows and monsoon depressions. Here we use satellite and gauge-based precipitation estimates with atmospheric reanalyses to assess 40-year trends in the rain rates of these storms, which have remained unknown. We show that rain rates increased in the rainiest quadrant of monsoon depressions, southwest of the vortex center; precipitation decreased in eastern quadrants, yielding no clear trend in precipitation averaged over the entire storm diameter. In an atmospheric reanalysis, ascent increased in the region of amplifying precipitation, but we could not detect trends in the intensity of rotational winds around the storm center. These storm changes occurred in a background environment where humidity increased rapidly over land while warming was more muted. Monsoon lows, which we show produce less precipitation than depressions, exhibit weaker trends that are less statistically robust.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

CORONAL RAIN IN MAGNETIC ARCADES: REBOUND SHOCKS, LIMIT CYCLES, AND SHEAR FLOWS

We extend our earlier multidimensional, magnetohydrodynamic simulations of coronal rain occurring in magnetic arcades with higher resolution, grid-adaptive computations covering a much longer (>6 hr) time span. We quantify how blob-like condensations forming in situ grow along and across field lines and show that rain showers can occur in limit cycles, here demonstrated for the first time in 2.5D setups. We discuss dynamical, multi-dimensional aspects of the rebound shocks generated by the siphon inflows and quantify the thermodynamics of a prominence–corona transition-region-like structure surrounding the blobs. We point out the correlation between condensation rates and the cross-sectional size of loop systems where catastrophic cooling takes place. We also study the variations of the typical number density, kinetic energy, and temperature while blobs descend, impact, and sink into the transition region. In addition, we explain the mechanisms leading to concurrent upflows while the blobs descend. As a result, there are plenty of shear flows generated with relative velocity difference around 80 km s{sup −1} in our simulations. These shear flows are siphon flows set up by multiple blob dynamics and they in turn affect the deformation of the falling blobs. In particular, we show how shear flows can break apart blobs into smaller fragments, within minutes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Increased extreme rains intensify erosional nitrogen and phosphorus fluxes to the northern Gulf of Mexico in recent decades

Abstract Soil erosion delivers enormous amounts of macro-nutrients including nitrogen (N) and phosphorus (P) from land to rivers, potentially sustaining water column bioavailable nutrient levels for decades. In this study, we represent erosional N and P fluxes in the Energy Exascale Earth System Model (E3SM) and apply the model to the continental United States. We estimate that during 1991–2019 soil erosion delivers 775 Gg yr −1 (1 Gg = 10 9 g) of particulate N (PN) and 328 Gg yr −1 of particulate P (PP) on average to the drainage basins of the northern Gulf of Mexico, including the Mississippi/Atchafalaya River and other rivers draining to the Texas Gulf and the Eastern Gulf. Our model simulation shows that in these rivers PP is the dominant P constituent and over 55% of P exported by erosion comes from soil P pools that could become bioavailable within decades. More importantly, we find that during 1991–2019 erosional N and P fluxes increase at rates of about 15 Gg N yr −1 and 6 Gg P yr −1 , respectively, due to increased extreme rains in the Mississippi/Atchafalaya river basin, and this intensification of erosional N and P fluxes drive the significant increase of riverine PN and PP yields to the northern Gulf of Mexico. With extreme rains projected to increase with warming, erosional nutrient fluxes in the region would likely continue to rise in the future, thus complicating the effort of reducing eutrophication in the inland and coastal waters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate Model (PDIR) for High-Resolution, Real-Time Satellite Precipitation Estimation

Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; and weather, climate, and hydrological forecasting. Moreover, real-time precipitation estimation with high precision is pivotal for the monitoring and managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data as input are attractive owing to their rich spatiotemporal resolution and near-instantaneous availability, their sole reliance on cloud-top brightness temperature (T b ) readings causes underestimates in wet regions and overestimates in dry regions—this is especially evident over the western contiguous United States (CONUS). We introduce an algorithm, the Precipitation Estimations from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain rate model (PDIR), which utilizes climatological data to construct a dynamic (i.e., laterally shifting) T b –rain rate relationship that has several notable advantages over other quantitative precipitation-estimation algorithms and noteworthy skill over the western CONUS. Validation of PDIR over the western CONUS shows a promising degree of skill, notably at the annual scale, where it performs well in comparison to other satellite-based products. Analysis of two extreme landfalling atmospheric rivers show that solely IR-based PDIR performs reasonably well compared to other IR- and PMW-based satellite rainfall products, marking its potential to be effective in real-time monitoring of extreme storms. This research suggests that IR-based algorithms that contain the spatiotemporal richness and near-instantaneous availability needed for rapid natural hazards response may soon contain the skill needed for hydrologic and water resource applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Seasonal Cycle of the Radiation Budget and Cloud Radiative Effect in the Amazon Rain Forest of Brazil

Changes in the climate system of the Amazon rain forest of Brazil can impact factors that influence the radiation budget such as clouds, atmospheric moisture, and the surface albedo. This study examines the relationships between clouds and radiation in this region using surface observations from the first year of the deployment of the Atmospheric Radiation Measurement (ARM) Program’s Mobile Facility 1 (AMF1) in Manacapuru, Brazil, and satellite measurements from the Clouds and the Earth’s Radiant Energy System (CERES). The seasonal cycles of the radiation budget and cloud radiative effects (CREs) are evaluated at the top of the atmosphere (TOA), at the surface, and within the atmospheric column using these observations and are placed into a regional context using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Water vapor and clouds are abundant throughout the year, even though slight decreases are observed in the dry season. The column water vapor load is large enough that the longwave radiative flux divergence is nearly constant throughout the year. Clouds produce a significant shortwave CRE at the surface and TOA, exceeding 200 W m -2 during the wet season. Discrepancies, especially in column shortwave radiative absorption, between the observations and MERRA-2 are demonstrated that warrant additional analysis of the microphysical and macrophysical cloud properties in MERRA-2. More trustworthy fields in the MERRA-2 product suggest that the expansive nearby river system impacts the regional radiation budget and thereby renders AMF1 observations potentially biased relative to regions farther removed from rivers within the Amazon rain forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CROCUS Tipping Bucket Rain Gauge Data at Argonne National Laboratory Prairie Site

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from both the Nova-Lynx 12 inch TBRG and the Met One 8-inch TBRG. The dataset contains one minute measurements for precipitation accumulation measured in that timeframe from both instruments. Each TBRG was equipped with heaters for all-season measurements. These data are helpful for identifying periods of drought, potential flooding, and general input for water budgets. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS project. Data were collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-min Precipitation Accumulation↗
DOE OSTI2023

Characterizing the Variation and Covariation of Cloud Microphysical Properties and Implications for Simulation of Subgrid-scale Warm-Rain Processes in Earth System Models (Final DOE-ASR Report)

Warm marine boundary layer (MBL) clouds constitute an important component in the global climate system, and precipitation plays a central role in controlling the water budget, radiative effects, and lifetime of these MBL clouds. Unfortunately, because of the relatively coarse effective grid resolution of the current generation of Earth system models (ESMs), the variety of cloud microphysical processes occurring inside an ESM grid cell are often oversimplified or unconstrained by observations. For example, the warm rain processes (e.g., autoconversion and accretion) are usually parameterized as nonlinear functions of grid-mean cloud properties. Because of the nonlinear nature of these functions, neglecting variability within the ESM grid volume can lead to substantial biases in precipitation production, cloud cover, and surface radiative fluxes. In state-of-the art ESMs, the influence of subgrid-scale variability is represented as an enhancement factor (EF) coefficient to the autoconversion, and accretion rates calculated from the model variables. However, EF is typically taken to be a constant or even used as a knob to tune model cloud properties to match observations, an ad hoc approach that may yield a desired cloud outcome yet introduce compensating errors. In this project, we used the combination of in situ cloud microphysics measurements from the ACE-ENA field campaign and large-eddy simulations (LES) to characterize and understand subgrid-scale variations and co-variations of cloud microphysical properties and use the results to evaluate and improve the representation of subgrid warm-rain processes in ESMs, in particular the EF used to tune the autoconversion and accretion processes. In this final report, we summarize our research activities and main findings in Section 2, provide a list of publications (Section 3) and presentations (Section 4) resulted from our research, and briefly discuss the student activities supported by this project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

An Explanation of Remarkable Emission-line Profiles in Post-flare Coronal Rain

We study broad redshifted emission in chromospheric and transition region lines that appears to correspond to a form of post-flare coronal rain. Profiles of Mg ii, C ii, and Si iv lines were obtained using IRIS before, during, and after the X2.1 flare of 2015 March 11 (SOL2015-03-11T16:22). We analyze the profiles of the five transitions of Mg ii (the 3p−3s h and k transitions, and three lines belonging to the 3d−3p transitions). We use analytical methods to understand the unusual profiles, together with higher-resolution observational data of similar phenomena observed by Jing et al. The peculiar line ratios indicate anisotropic emission from the strands that have cross-strand line center optical depths (k line) of between 1 and 10. The lines are broadened by unresolved Alfvénic motions whose energy exceeds the radiation losses in the Mg ii lines by an order of magnitude. The decay of the line widths is accompanied by a decay in the brightness, suggesting a causal connection. If the plasma is ≲99% ionized, ion–neutral collisions can account for the dissipation; otherwise, a dynamical process seems necessary. Our work implies that the motions are initiated during the impulsive phase, to be dissipated as radiation over a period of an hour, predominantly by strong chromospheric lines. The coronal “rain” we observe is far more turbulent than most earlier reports have indicated, with implications for plasma heating mechanisms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Observational Evidence for the Associated Formation of Blobs and Raining Inflows in the Solar Corona

The origin of the slow solar wind is still a topic of much debate. The continual emergence of small transient structures from helmet streamers is thought to constitute one of the main sources of the slow wind. Determining the height at which these transients are released is an important factor in determining the conditions under which the slow solar wind forms. To this end, we have carried out a multipoint analysis of small transient structures released from a north–south tilted helmet streamer into the slow solar wind over a broad range of position angles during Carrington Rotation 2137. Combining the remote-sensing observations taken by the Solar-TErrestrial RElations Observatory ( STEREO ) mission with coronagraphic observations from the SOlar and Heliospheric Observatory ( SOHO ) spacecraft, we show that the release of such small transient structures (often called blobs), which subsequently move away from the Sun, is associated with the concomitant formation of transient structures collapsing back toward the Sun; the latter have been referred to by previous authors as “raining inflows.” This is the first direct association between outflowing blobs and raining inflows, which locates the formation of blobs above the helmet streamers and gives strong support that the blobs are released by magnetic reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Evaluation of autoconversion and accretion enhancement factors in general circulation model warm-rain parameterizations using ground-based measurements over the Azores

A great challenge in climate modeling is how to parameterize subgrid cloud processes, such as autoconversion and accretion in warm-rain formation. In this study, we use ground-based observations and retrievals over the Azores to investigate the so-called enhancement factors, E auto and E accr , which are often used in climate models to account for the influence of subgrid variance of cloud and precipitation water on the autoconversion and accretion processes. E auto and E accr are computed for different equivalent model grid sizes. The calculated E auto values increase from 1.96 (30 km) to 3.2 (180 km), and the calculated E accr values increase from 1.53 (30 km) to 1.76 (180 km). Comparing the prescribed enhancement factors in Morrison and Gettleman (2008, MG08) to the observed ones, we found that a higher E auto (3.2) at small grids and lower E accr (1.07) are used in MG08, which might explain why most of the general circulation models (GCMs) produce too-frequent precipitation events but with too-light precipitation intensity. The ratios of the rain to cloud water mixing ratio ( q r / q c ) at E accr =1.07 and E accr =2.0 are 0.063 and 0.142, respectively, from observations, further suggesting that the prescribed value of E accr =1.07 used in MG08 is too small to simulate precipitation intensity correctly. Both E auto and E accr increase when the boundary layer becomes less stable, and the values are larger in precipitating clouds ( CLWP>75 gm -2 ) than those in non-precipitating clouds ( CLWP<75 gm -2 ). Therefore, the selection of E auto and E accr values in GCMs should be regime- and resolution-dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

54 ENVIRONMENTAL SCIENCES↗