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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Analyzing historical snow trends in interior Alaska

Study region The Chena River watershed in Interior Alaska, USA Study focus This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD). New hydrological insights for the region Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

New insights into the drainage of inundated ice-wedge polygons using fundamental hydrologic principles

Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.

Harp, Dylan R. (ORCID:0000000197778000)↗
DOE OSTI2025

Atmospheric River Frequency-Category Characteristics Shape U.S. West Coast Runoff

Abstractrunoff response to atmospheric rivers (ARs) over the U.S. West Coast. We focused on runoff time series variations impacted by AR characteristics (e.g., category and frequency) and land preconditions during Northern Hemisphere cool seasons in the period of 1940–2023. Results show that high-category ARs significantly increase local runoff with higher hourly precipitation rates leading to a greater incremental rate and peak runoff. Extreme runoff increases greatly with the AR category with an increase rate up to 12.5 times stronger than non-extreme runoff. Besides the AR category, land preconditions such as soil moisture and snowpack also play crucial roles in modulating runoff response. We found that runoff induced by weak-category ARs is more sensitive to land preconditions than high-category ARs, with high peak runoff occurring when soil is nearly saturated. Additionally, more than 50% of high-peak-runoff events in snow-covered grid cells are associated with rain-on-snow events particularly for the events associated with weaker ARs. Regression analysis reveals that AR precipitation and land preconditions jointly influence runoff, emphasizing the importance of including soil moisture and snowpack levels in AR impact assessments. The study also highlights the intensified runoff response to back-to-back ARs with short intervals, which may become more frequent with climate warming, posing increased flood risks via facilitating wet soil conditions. Our findings have significant implications for AR risk predictions and the development of prediction models for AR-induced runoff.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Diazotrophs Show Signs of Restoration in Amazon Rain Forest Soils with Ecosystem Rehabilitation

Biological nitrogen fixation can be an important source of nitrogen in tropical forests that serve as a major CO 2 sink. Extensive deforestation of the Amazon is known to influence microbial communities and the biogeochemical cycles they mediate. However, it is unknown how diazotrophs (nitrogen-fixing microorganisms) respond to deforestation and subsequent ecosystem conversion to agriculture, as well as whether they can recover in secondary forests that are established after agriculture is abandoned. To address these knowledge gaps, here we combined a spatially explicit sampling approach with high-throughput sequencing of nifH genes. The main objectives were to assess the functional distance decay relationship of the diazotrophic bacterial community in a tropical forest ecosystem and to quantify the roles of various factors that drive the observed changes in the diazotrophic community structure. We observed an increase in local diazotrophic diversity (α-diversity) with a decrease in community turnover (β-diversity), associated with a shift in diazotrophic community structure as a result of the forest-to-pasture conversion. Both diazotrophic community turnover and structure showed signs of recovery in secondary forests. Changes in the diazotrophic community were primarily driven by the change in land use rather than differences in geochemical characteristics or geographic distances. The diazotroph communities in secondary forests resembled those in primary forests, suggesting that at least partial recovery of diazotrophs is possible following agricultural abandonment. IMPORTANCE The Amazon region is a major tropical forest region that is being deforested at an alarming rate to create space for cattle ranching and agriculture. Diazotrophs (nitrogen-fixing microorganisms) play an important role in supplying soil N for plant growth in tropical forests. It is unknown how diazotrophs respond to deforestation and whether they can recover in secondary forests that establish after agriculture is abandoned. Using high-throughput sequencing of nifH genes, we characterized the response of diazotrophs’ β-diversity and identified major drivers of changes in diazotrophs from forest-to-pasture and pasture-to-secondary-forest conversions. Studying the impact of land use change on diazotrophs is important for a better understanding of the impact of deforestation on tropical forest ecosystem functioning, and our results on the potential recovery of diazotrophs in secondary forests imply the possible restoration of ecosystem functions in secondary forests.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?

Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, in this work, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM-MOD), and Penman–Monteith Nagler model (PM-VI). ET was predicted satisfactorily by all four models, with correlations consistently higher (R 2 > 6) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (-10 < PBIAS < 10%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Nonlinear Climate Responses to Increasing CO2 and Anthropogenic Aerosols Simulated by CESM1

Abstract Atmospheric CO2 and anthropogenic aerosols (AA) have increased simultaneously. Because of their opposite radiative effects, these increases may offset each other, which may lead to some nonlinear effects. Here the seasonal and regional characteristics of this nonlinear effect from the CO2 and AA forcings are investigated using the fully coupled Community Earth System Model. Results show that nonlinear effects are small in the global mean of the top-of-the-atmosphere radiative fluxes, surface air temperature, and precipitation. However, significant nonlinear effects exist over the Arctic and other extratropical regions during certain seasons. When both forcings are included, Arctic sea ice in September–November decreases less than the linear combination of the responses to the individual forcings due to a higher sea ice sensitivity to the CO2-induced warming than the sensitivity to the AA-induced cooling. This leads to less Arctic warming in the combined-forcing experiment due to reduced energy release from the Arctic Ocean to the atmosphere. Some nonlinear effects on precipitation in June–August are found over East Asia, with the northward-shifted East Asian summer rain belt to oppose the CO2 effect. In December–February, the aerosol loading over Europe in the combined-forcing experiment is higher than that due to the AA forcing, resulting from CO2-induced circulation changes. The changed aerosol loading results in regional thermal responses due to aerosol direct and indirect effects, weakening the combined changes of temperature and circulation. This study highlights the need to consider nonlinear effects from historical CO2 and AA forcings in seasonal and regional climate attribution analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Synoptic Typing of Multiduration, Heavy Precipitation Records in the Northeastern United States: 1895–2017

Much of the previous research on total and heavy precipitation trends across the northeastern United States (herein, the Northeast) used daily precipitation totals over relatively short periods of record, which do not capture the full range of climate variability and change. Less well understood are the characteristics of long-term changes and synoptic patterns in longer-duration heavy precipitation events across the Northeast. A multiduration (1, 2, 3, 7, 14, and 30 days), multi-return-interval (2, 5, 10, and 50 years) precipitation dataset was used to diagnose changes in various types of precipitation events across the Northeast from 1895 to 2017. Increasing trends were found in all duration and return-interval event combinations with the rarest, longest duration events increasing at faster rates than more-frequent, shorter-duration ones. Daily 850-hPa geopotential height patterns associated with precipitation events were extracted from rotated principal component analysis and k -means clustering analysis, which allowed for the main synoptic types present as well as their structure and evolution to be analyzed. The daily synoptic patterns thus identified were found to be similar across all durations and return intervals and included coastal low (Northeasters, tropical cyclones, and predecessor rain events), deep trough, East Coast trough, zonal, and high pressure patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spatiotemporal Variations in the Characteristics of Mesoscale Convective Systems Over Indian Monsoon Zone

Here, this study examines cloud and precipitation properties of mesoscale convective systems (MCSs) in the Indian monsoon zone using 6 years of high-resolution satellite-based tracking data. MCSs exhibit strong regional and seasonal variations, peaking during the summer monsoon (June–September). Concentrated along a southeast-northwest band of the monsoon trough, MCS contribute 40%–70% of total precipitation and predominantly move westward at an average speed of 6.3 m s -1 . Long-lived MCSs (> 40 hr), although 10 times less frequent than short-lived MCSs (5–20 hr), produce 2–3 times more rainfall. Longer MCS lifespans and higher rainfall are associated with stronger deep-layer wind shear and enhanced lower free-tropospheric moisture at initiation. Land and ocean MCSs exhibit distinct diurnal cycles. Most land-based MCSs initiate around 16 LT and mature at 18 LT, whereas Bay of Bengal (BoB) MCSs initiate between 04 and 06 LT and peak by 14 LT. Convective precipitations from MCSs significantly surpasses that from non-MCSs systems, emphasizing their critical role in intense monsoon rainfall. Short- and long-lived MCSs showed distinct lifecycle evolution. Long-lived MCSs over the BoB show 37% larger cold-cloud shields, 44% larger precipitation feature areas, and 33% higher rain rates than their land counterparts, yielding 67% more total rainfall. These BoB MCSs also grow faster and experience more frequent cloud mergers early in their lifecycle. These findings offer critical insights into monsoonal MCSs lifecycle evolution, providing observational constraints for improving model simulations of monsoonal convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Linking Flood Frequency With Mesoscale Convective Systems in the US

Mesoscale convective systems (MCSs) with larger rain areas and higher rainfall intensity than non-MCS events can produce severe flooding. Flooding occurrences associated with MCS and non-MCS rainfall in the US east of 110°W are examined by linking a high-resolution MCS data set and reported floods in the warm season (April-August) between 2007 and 2017. MCSs account for the majority of slow-rising and hybrid floods, while non-MCS rainfall explains about half of flash floods in July and August as individual thunderstorms occur frequently in the Rocky Mountains and Appalachian Mountains. The event-total rainfall area of MCSs is the dominant factor of flood occurrences: MCSs with greater rainfall areas tend to produce more floods. While not related to flood frequency, propagating MCSs tend to produce flash floods with longer durations. These established links can improve our confidence in interpreting flood risks and their future changes due to changes in MCS characteristics with warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The development of rainfall retrievals from radar at Darwin

Abstract. The U.S. Department of Energy Atmospheric Radiation Measurement program Tropical Western Pacific site hosted a C-band polarization (CPOL) radar in Darwin, Australia. It provides 2 decades of tropical rainfall characteristics useful for validating global circulation models. Rainfall retrievals from radar assume characteristics about the droplet size distribution (DSD) that vary significantly. To minimize the uncertainty associated with DSD variability, new radar rainfall techniques use dual polarization and specific attenuation estimates. This study challenges the applicability of several specific attenuation and dual-polarization-based rainfall estimators in tropical settings using a 4-year archive of Darwin disdrometer datasets in conjunction with CPOL observations. This assessment is based on three metrics: statistical uncertainty estimates, principal component analysis (PCA), and comparisons of various retrievals from CPOL data. The PCA shows that the variability in R can be consistently attributed to reflectivity, but dependence on dual-polarization quantities was wavelength dependent for 1 10mmh-1. Rainfall estimates during these conditions primarily originate from deep convective clouds with median drop diameters greater than 1.5 mm. An uncertainty analysis and intercomparison with CPOL show that a Colorado State University blended technique for tropical oceans, with modified estimators developed from video disdrometer observations, is most appropriate for use in all cases, such as when 1 10mmh-1 (deeper convective rain).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Codon bias, nucleotide selection, and genome size predict in situ bacterial growth rate and transcription in rewetted soil

In soils, the first rain after a prolonged dry period represents a major pulse event impacting soil microbial community function, yet we lack a full understanding of the genomic traits associated with the microbial response to rewetting. Genomic traits such as codon usage bias and genome size have been linked to bacterial growth in soils—however, often through measurements in culture. Here, we used metagenome-assembled genomes (MAGs) with 18 O-water stable isotope probing and metatranscriptomics to track genomic traits associated with growth and transcription of soil microorganisms over one week following rewetting of a grassland soil. We found that codon bias in ribosomal protein genes was the strongest predictor of growth rate. We also found higher growth rates in bacteria with smaller genomes, suggesting that reduced genome size enables a faster response to pulses in soil bacteria. Faster transcriptional upregulation of ribosomal protein genes was associated with high codon bias and increased nucleotide skew. We found that several of these relationships existed within phyla, indicating that these associations between genomic traits and activity could be generalized characteristics of soil bacteria. Finally, we used publicly available metagenomes to assess the distribution of codon bias across a pH gradient and found that microbial communities in higher pH soils—which are often more water limited and pulse driven—have higher codon usage bias in their ribosomal protein genes. Together, these results provide evidence that genomic characteristics affect soil microbial activity during rewetting and pose a potential fitness advantage for soil bacteria where water and nutrient availability are episodic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Drop Size Distribution Variability in Central Argentina during RELAMPAGO-CACTI

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logN w ), the mean volume diameter (D 0 ), the mean mass diameter (D m ), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logN w , lower D 0 , and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D 0 : the lower values of D 0 were associated with higher values of logN w and were found more frequently during the afternoon, while the higher D 0 were associated with lower logN w and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logN w -D 0 and LWC-D 0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment (BIRDIE) (Field Campaign Report)

The Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment or BIRDIE was a precipitation collection campaign designed to measure cosmogenic isotopes of beryllium in rainfall and other forms of precipitation across the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) atmospheric observatory. Precipitation samples were collected over three weeks (May 21-June 10, 2022) at 11 SGP sites across a 120-km 2 domain in northern and central Oklahoma. The field campaign targeted summertime convection rain events. We aimed to capture any spatial and/or temporal variability in the concentrations of beryllium-10 (10Be) and beryllium-7 (7Be) across the ARM SGP site during these rainfall events. The ratio of 10Be to 7Be (10/7Be) has been shown to be a powerful tracer for transport processes in the stratosphere-troposphere exchange (STE) system (e.g., Koch and Rind 1998). Any observed variability is analyzed to see if it could be linked to STE processes, including overshooting of deep convection clouds that penetrate the lower stratosphere. Six wet weather system events were collected within our three-week span. Five out of six of these rainfall events are classified as moderately to strongly convective. Those events are studied in more detail. The five systems also follow each other over a short period of 11 days. In our rainfall samples we observed spatial and event variability in the concentrations of beryllium-10 and -7 that resulted in variability of 10/7Be ratios. Each weather event appeared to exhibit a unique 10/7Be pattern across the domain that was not directly linked to storm total precipitation amount. To better understand the causes for this spatial variability, cloud characteristics in the domain were looked at to assess cloud type, cloud height, and depth information. We also ran Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model back trajectories to identify possible air mass and moisture origins across our events. Detailed analysis is ongoing. The purpose of this technical report is to provide background on using cosmogenic isotopes as atmospheric tracers, describe the experimental design, and present the beryllium concentration and ratio data. Lastly, we note that BIRDIE coincided with two other deep convection field campaigns in the area: The National Aeronautics and Space Administration (NASA)’s Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) experiment (https://dcotss.org/) centered in Salina, Kansas, and the Targeted Observation by Radars and (uncrewed aerial systems) UAS of Supercells (TORUS) experiment (https://catalog.eol.ucar.edu/torus_2022) across the U.S. Central Plains. Additionally, a Lawrence Livermore National Laboratory ( LLNL) team at DCOTSS attempted to measure 10Be/7Be ratios on aerosols collected in situ in the lower and mid-stratosphere over Kansas using high-altitude balloons. Precipitation samples were also collected on the ground in Salina, Kansas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment (BIRDIE) (Final Report)

The Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment or BIRDIE was a precipitation collection campaign designed to measure cosmogenic isotopes of beryllium in rainfall and other forms of precipitation across the DOE Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site. Precipitation samples were collected over three weeks (May 21-June 10, 2022) at 11 SGP sites across a 120 km 2 domain in northern and central Oklahoma. The field campaign targeted summer-time convection rain events. We aimed to capture any spatial and/or temporal variability in the concentrations of beryllium-10 (10Be) and beryllium-7 (7Be) across the SGP ARM site during these rainfall events. The ratio of 10Be to 7Be (10/7Be) has been shown to be a powerful tracer for transport processes in the stratosphere-troposphere exchange (STE) system (e.g., Koch and Rind 1998). Any observed variability is analyzed to see if it could be linked to STE processes, including overshooting of deep convection clouds which penetrate the lower stratosphere. Six wet weather system events were collected within our three-week span. Five out of six of these rainfall events are classified as moderately to strongly convective. Those events are studied in more detail. The five systems also follow each other over a short time period of eleven days. In our rainfall samples we observed spatial and event variability in the concentrations of beryllium-10 and -7 which resulted in variability of 10/7 Be ratios. Each weather event appeared to exhibit a unique 10/7Be pattern across the domain that was not directly linked to storm total precipitation amount. To better understand the causes for this spatial variability, cloud characteristics in the domain were looked at to assess cloud type, cloud height and depth information. We also ran Hysplit back trajectories to identify possible air mass and moisture origins across our events. Detailed analysis is still on-going. The purpose of this technical report is to provide background on using cosmogenic isotopes as atmospheric tracers, describe the experimental design, and present the beryllium concentration and ratio data.

58 GEOSCIENCES↗
DOE OSTI2020

A Polarimetric Radar Analysis of Ice Microphysical Processes in Melting Layers of Winter Storms Using S-Band Quasi-Vertical Profiles

Quasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization Z H . QVP ML statistics are examined for two regimes in the ML data: Z H ≥ 20 dB Z and Z H < 20 dB Z . Regions of Z H ≥ 20 dB Z indicate locations of MLs collocated with enhanced differential reflectivity Z DR and reduced copolar correlation coefficient ρ hv , while for Z H < 20 dB Z a well-defined ML is difficult to discern using Z H alone. Evidence of large Z DR up to 4 dB, backscatter differential phase δ up to 8°, and low ρ hv down to 0.80 associated with lower Z H (from -10 to 20 dB Z ) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase K DP and maximum Z H in the ML; these are the first QVP observations of K DP in MLs documented at S band. Negative correlation occurs between minimum ρ hv in the ML and ML depth and between minimum ρ hv in the ML and the corresponding enhancement of Z H (Δ Z H = Z H max - Z H rain ).

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

A typological framework of non-floodplain wetlands for global collaborative research and sustainable use

Non-floodplain wetlands (NFWs) are important but vulnerable inland freshwater systems that are receiving increased attention and protection worldwide. However, a lack of consistent terminology, incohesive research objectives, and inherent heterogeneity in existing knowledge hinder cross-regional information sharing and global collaboration. To address this challenge and facilitate future management decisions, we synthesized recent work to understand the state of NFW science and explore new opportunities for research and sustainable NFW use globally. Results from our synthesis show that although NFWs have been widely studied across all continents, regional biases exist in the literature. We hypothesize these biases in the literature stem from terminology rather than real geographical bias around existence and functionality. To confirm this observation, we explored a set of geographically representative NFW regions around the world and characteristics of research focal areas. We conclude that there is more that unites NFW research and management efforts than we might otherwise appreciate. Furthermore, opportunities for cross-regional information sharing and global collaboration exist, but a unified terminology will be needed, as will a focus on wetland functionality. Based on these findings, we discuss four pathways that aid in better collaboration, including improved cohesion in classification and terminology, and unified approaches to modeling and simulation. In turn, legislative objectives must be informed by science to drive conservation and management priorities. Finally, an educational pathway serves to integrate the measures and to promote new technologies that aid in our collective understanding of NFWs. Our resulting framework from NFW synthesis serves to encourage interdisciplinary collaboration and sustainable use and conservation of wetland systems globally.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The high-power helicon program at DIII-D: gearing up for first experiments

Helicon current drive, also called fast wave current drive in the lower hybrid range of frequencies, has long been regarded as a promising current drive tool for reactor grade plasmas. A newly installed MW-level system at DIII-D will be the first test of this technology in reactor-relevant plasmas, in the sense that full single-pass absorption is expected. A 30-module traveling wave antenna has been installed and optimized in-vessel in early 2020. The linear electromagnetic characteristics of the unloaded module array have been extensively tested both on the bench and in the vessel at instrumentation power levels. Excellent performance has been achieved, ~2% reflected power and ~1.5% dissipated power per module in air, in a 10 MHz band around 476 MHz. Stripline feeds on both ends of the antenna allow either co or counter current drive. The installation of a 1.2 MW klystron and associated high-power electronics was completed in Fall 2020. Commissioning of the antenna is ongoing. An important goal of this experiment is to validate the helicon current drive physics basis using an extensive set of new and upgraded diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗