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At least 1,117 records · Page 62

Tall Precipitation Cells in Tropical Cyclone Eyewalls Are Associated with Tropical Cyclone Intensification

The association between tall precipitation and tropical cyclone intensification may have implications for the difficult task of forecasting the destructive potential of these storms. We propose a novel way to use radar-observed rain height to help predict tropical cyclone intensity. Then, we adapt this technique for use on the much more plentiful data from infrared and microwave instruments.

Kelley, Owen A.↗

How Cities Make Their Own Weather

Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in d e near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. We will also present results from experiments using a regional atmospheric-land surface modeling system. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

Shepherd, J. Marshall↗

A Regional, Integrated Monitoring System for the Hydrology of the Pan-Arctic Land Mass

Work under this NASA contract developed a system for monitoring and historical analysis of the major components of the pan-Arctic terrestrial water cycle. It is known as Arctic-RIMS (Regional Integrated Hydrological Monitoring System for the Pan-Arctic Landmass). The system uses products from EOS-era satellites, numerical weather prediction models, station records and other data sets in conjunction with an atmosphere-land surface water budgeting scheme. The intent was to compile operational (at 1-2 month time lags) gridded fields of precipitation (P), evapotranspiration (ET), P-ET, soil moisture, soil freeze/thaw state, active layer thickness, snow extent and its water equivalent, soil water storage, runoff and simulated discharge along with estimates of non-closure in the water budget. Using "baseline" water budgeting schemes in conjunction with atmospheric reanalyses and pre-EOS satellite data, water budget fields were conjunction with atmospheric reanalyses and pre-EOS satellite data, water budget fields were compiled to provide historical time series. The goals as outlined in the original proposal can be summarized as follows: 1) Use EOS data to compile hydrologic products for the pan-Arctic terrestrial regions including snowcover/snow water equivalent (SSM/A MODIS, AMSR) and near-surface freeze/thaw dynamics (Sea Winds on QuikSCAT and ADEOS I4 SSMI and AMSR). 2) Implement Arctic-RIMS to use EOS data streams, allied fields and hydrologic models to produce allied outputs that fully characterize pan-Arctic terrestrial and aerological water budgets. 3) Compile hydrologically-based historical products providing a long-term baseline of spatial and temporal variability in the water cycle.

Serreze, Mark↗

Variation in Nest Temperatures of the American Alligator Found on the Kennedy Space Center Merritt Island National Wildlife Refuge

Information on nest temperatures of the American Alligator (Alligator mississippiensis) constructed in the wild is limited. Nesting temperatures during a critical thermal sensitive period determine the sex of alligators and are therefore critical in establishing the sex biases in recruitment efforts of alligators within a given community. Nest components, varying environmental conditions, and global warming could have a significant impact on nest temperatures, thus affecting future generations of a given population. One hundred and seventy four programmable thermistors were inserted into fifty eight nests from 2010 through 2015 nesting cycles. Three thermistors were placed inside each nest cavity (one on top of the eggs, one in the middle of the eggs, and one at the bottom of the clutch of the eggs) to collect temperature profiles in the incubation chamber and throughout the entire incubation period. One thermistor was also placed near or above these nests to obtain an ambient air temperature profile. Once retrieved, data from these thermistors were downloaded to examine temperature profiles throughout the incubation period as well as during the period of sexual determination. These data would help establish survival rates related to nest temperature and predict sex ratio of recruited neonates at the Kennedy Space Center. Over three million temperatures have been recorded since 2010 for the alligator thermistor study giving us insight to the recruitment efforts found here. Precipitation was the largest influence on nesting temperatures outside of daily photoperiod, with immediate changes of up to eight degrees Celsius.

Alligator↗

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation

Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of “seasonally variable regimes becoming more variable”. Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation.

54 ENVIRONMENTAL SCIENCES↗

Historical and future trends in South Asian monsoon low pressure systems in a high-resolution model ensemble

Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K −1 , which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.

54 ENVIRONMENTAL SCIENCES↗

Data from: "Soil moisture mediates alpine life form and community productivity responses to warming"

This dataset contains values that were used to support conclusions drawn in the publication “Soil moisture mediates alpine life form and community productivity responses to warming”, originally published in 2016 by Winkler et al. All data were collected in the alpine site of the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains, USA. The file types in this archive include comma-separated-values (.csv) files, and two types of geospatial files: .kml and shapefiles (.shp). The csv files can be opened by R, Microsoft Excel, or any simple text editor software. The geospatial files can be opened by Google Earth/Google Maps, and the ESRI shapefiles can be opened by geographic information systems softwares that can read shapefiles, including ESRI’s ArcGIS Desktop suite, and QGIS.Climate warming is expected to alter primary production and community composition in alpine systems around the globe. Whether production will increase in response to warming in the absence of additional precipitation remains underexplored. We experimentally warmed an alpine plant community on Niwot Ridge, Colorado to test whether warming increases or decreases productivity of multiple plant life form groups and the entire plant community. We also provided supplemental water to a subset of plots to alleviate potential drying effects of warming. We predicted alpine community above-ground productivity would increase in response to warming only when combined with supplemental water to limit soil drying. We also predicted plant life form groups would vary in their responses and would like buffer changes in community productivity.

54 ENVIRONMENTAL SCIENCES↗

Shape Control of Colloidal Semiconductor Nanocrystals through Thermodynamically Driven Aggregative Growth

The optoelectronic properties of colloidal semiconductor nanocrystals (NCs) can be manipulated by changing their geometric shapes. The precise synthetic control over particle morphologies, however, has remained elusive. Conventional growth techniques rely on the kinetic assembly of atomic units, where supersaturation and precipitation processes can lead to a broad distribution of particle shapes. In this paper, we demonstrate that replacing atomic precursors with small-size nanocrystals as building blocks for larger colloids offers an easier, more predictive control over nanoparticle shape evolution. The reported growth strategy is illustrated via shape-selective syntheses of CdSe and CdS NC cubes, spheres, rods, as well as unprecedented “donut” and ring-like structures. Growth of desired particle morphologies was achieved by choosing an appropriate reaction solvent that minimizes the surface free energy through a unique shape formation. This so-called "aggregative growth mechanism" is explained using a thermodynamic model for interacting viscous colloids. We expect that this novel growth strategy will offer a viable platform for shape–selective synthesis of many inorganic colloids, providing pathways to optimizable optoelectronic materials.

36 MATERIALS SCIENCE↗

Estimating and Forecasting Time-Varying Groundwater Recharge in Fractured Rock: A State-Space Formulation with Preferential and Diffuse Flow to the Water Table

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

groundwater, Recharge, infiltration, recursive est↗

Using root and soil traits to forecast woody encroachment dynamics in mesic grassland

Grasslands are a widespread and globally important biome providing key ecosystem services including C storage and regulation of the water cycle. Grasslands face multiple threats, including changes in drought intensity and woody encroachment - a process that results in increased woody plant abundance corresponding with decreased herbaceous plant abundance. The combination of reduced soil moisture and shifts in plant dominance from herbaceous to woody are likely to alter C pools in the soil profile. We currently do not have the capacity to predict either the magnitude or rates of change in these C pools. In order to predict changes in grassland vegetation structure and the associated impacts on C cycling requires greater understanding of changes in soil C pools at multiple soil depths, and the responses of these pools to changes in precipitation. To support and perform this parameterization of Land Surface Models, we performed detailed investigations of root (anatomical and physiological) and soil traits (microbial function) at varying soil depths, to capture the belowground impacts of changing dominant plant growth forms (grasses to shrubs) and the impacts of frequent drought.

54 ENVIRONMENTAL SCIENCES↗

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗

Preliminary evaluation of Nimbus-6 sounding data

Preliminary results on Nimbus-6 moisture and temperature soundings are discussed. The satellite takes readings of cloud-tracked winds and temperatures (with vertical resolution) in microwave and IR (15 micron and 4 micron) channels. The data are compared with ground-based radiosonde data. Isotherm patterns and thickness patterns derived from satellite data and radiosonde data are compared, as well as data on precipitable water. Satellite soundings are found to present a realistic picture of thermal and moisture fields in the vicinity of large-scale disturbances, and can be useful in initialization for large-scale numerical prediction models when properly combined with data from other sources. Limitations in vertical resolution are noted.

Tracton, M. S.↗

Superalloy composition modeling

Development of a predictive method for determination of the gamma/gamma prime phase fields, i.e., gamma prime volume fraction as a function of the multicomponent composition, is described. The cluster variation method used for binary alloys in which the precipitated phase is coherent with the matrix phase is extended for application to the multicomponent coherent gamma/gamma prime nickel-based superalloys. It is shown that the cluster variation method can accurately describe the equilibrium (incoherent) gamma/gamma prime phase fields in the binary Ni-Al phase diagram. The gamma/gamma prime phase field for the Ni-Cr-Al ternary phase diagram is computed as a function of temperature. A reasonable fit results between the calculated and the experimental diagrams. The modeling of the six-component Ni-Cr-Al-Co-Mo-Ti base superalloy and the effect of Ni substitution of Co are discussed.

Barefoot, J.↗

Late-Quaternary climatic change on the American North Pacific Coast

The late Quaternary climate of the North Pacific, where according to modelling the solar radiation in the early Holocene at the time of the summer solstice is high and in the late Holocene is relatively low, is investigated. Quantitative temperature and precipitation estimates from southern Alaska are compared with estimates from western Washington and British Columbia. Data extending over more than 10,000 years show a broadly consistent pattern of climatic change in general agreement with predicted variations in solar radiation and their effect on atmospheric circulation and seasonal duration of pressure systems over the North Pacific Ocean. In the early Holocene, the subtropical North Pacific anticyclone annually regulated climate for a longer period at higher latitudes than at present, so that warmth and dryness increased in southern Alaska. The Aleutian low-pressure center intensified during the late Holocene, resulting in colder and more humid coastal climate and increased frequency of glacier growth in the cordillera.

Heusser, C. J.↗

Atomistic Simulations of Ti Additions to NiAl

The development of more efficient engines and power plants for future supersonic transports depends on the advancement of new high-temperature materials with temperature capabilities exceeding those of Ni-based superalloys. Having theoretical modelling techniques to aid in the design of these alloys would greatly facilitate this development. The present paper discusses a successful attempt to correlate theoretical predictions of alloy properties with experimental confirmation for ternary NiAl-Ti alloys. The B.F.S. (Bozzolo-Ferrante-Smith) method for alloys is used to predict the solubility limit and site preference energies for Ti additions of 1 to 25 at.% to NiAl. The results show the solubility limit to be around 5% Ti, above which the formation of Heusler precipitates is favored. These results were confirmed by transmission electron microscopy performed on a series of NiAl-Ti alloys.

Bozzolo, Guillermo↗

Structure and Evolution of an Oceanic Squall Line During South China Sea Monsoon Experiment

The South China Sea Monsoon Experiment (SCSMEX) was conducted in South China Sea (SCS) and surrounding areas during May - June 1998. The primary goal of the experiment is to provide a better understanding of the key physical processes for the onset, maintenance and variability of the monsoon over the Southeast Asia and southern China leading to improved monsoon predictions. As the first comprehensive field experiment aiming on the SCS summer monsoon, the goals of the mesoscale program associated with the primary objective are: (1) to define the initiation, structure, evolution and dynamics of precipitation processes associated with the onset and mature phase of the SCS monsoon, and (2) to obtain quantitative rainfall estimates, vertical air motion and inferences on microphysical structure over a tropical oceanic site.

Wang, Jian-Jian↗

Overview of Mount Washington Icing Sensors Project

NASA, the FAA, the Department of Defense, the National Center for Atmospheric Research and NOAA are developing techniques for retrieving cloud microphysical properties from a variety of remote sensing technologies. The intent is to predict aircraft icing conditions ahead of aircraft. The Mount Washington Icing Sensors Project MWISP), conducted in April, 1999 at Mt. Washington, NH, was organized to evaluate technologies for the prediction of icing conditions ahead of aircraft in a natural environment, and to characterize icing cloud and drizzle environments. April was selected for operations because the Summit is typically in cloud, generally has frequent freezing precipitation in spring, and the clouds have high liquid water contents. Remote sensing equipment, consisting of radars, radiometers and a lidar, was placed at the base of the mountain, and probes measuring cloud particles, and a radiometer, were operated from the Summit. NASA s Twin Otter research aircraft also conducted six missions over the site. Operations spanned the entire month of April, which was dominated by wrap-around moisture from a low pressure center stalled off the coast of Labrador providing persistent upslope clouds with relatively high liquid water contents and mixed phase conditions. Preliminary assessments indicate excellent results from the lidar, radar polarimetry, radiosondes and summit and aircraft measurements.

Ryerson, Charles C.↗