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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Projecting end-of-century climate extremes and their impacts on the hydrology of a representative California watershed

Abstract. In California, it is essential to understand the evolution of water resources in response to a changing climate to sustain its economy and agriculture and to build resilient communities. Although extreme conditions have characterized the historical hydroclimate of California, climate change will likely intensify hydroclimatic extremes by the end of the century (EoC). However, few studies have investigated the impacts of EoC extremes on watershed hydrology. We use cutting-edge global climate and integrated hydrologic models to simulate EoC extremes and their effects on the water-energy balance. We assess the impacts of projected driest, median, and wettest water years under Representative Concentration Pathway (RCP) 8.5 on the hydrodynamics of the Cosumnes River basin. Substantial changes to annual average temperature (>+2.5 ∘C) and precipitation (>+38 %) will characterize the EoC extreme water years compared to their historical counterparts. A shift in the dominant form of precipitation, mostly in the form of rain, is projected to fall earlier. These changes reduce snowpack by more than 90 %, increase peak surface water and groundwater storages up to 75 % and 23 %, respectively, and drive the timing of peak storage to occur earlier in the year. Because EoC temperatures and soil moisture are high, both potential and actual evapotranspiration (ET) increase. The latter, along with the lack of snowmelt in the warm EoC, causes surface water and groundwater storages to significantly decrease in summer, with groundwater showing the highest rates of decrease. These changes result in more ephemeral EoC streams with more focused flow and increased storage in the mainstem of the river network during the summer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Solidification of undercooled Ni-Sn eutectic alloy under microgravity conditions in the Space Shuttle

The Space Shuttle Columbia carried an Alloy Undercooling Experiment on its STS 61-C mission in January, 1986. The experiment was performed in an electromagnetic levitator. A sample of Ni-32.5 wt pct Sn eutectic was melted and solidified under microgravity conditions in the Space Shuttle. The specimen achieved only a fairly small undercooling, probably less than 30 K. The specimen was examined by optical and scanning electron microscopy. The surface and cross-sectional microstructures were primarily composed of normal lamellar eutectic, but showed several interesting features, including an apparent surface nucleation site, curved dendrites with nonorthogonal secondary arms, dendrite fragments with extremely fine arm spacing, submicron precipitates, and faceted crystals. The results of the space experiment are presented and compared with ground-based results obtained with the same alloy.

Piccone, T. J.↗
NASA NTRS1995

17-4 PH and 15-5 PH

17-4 PH and 15-5 PH are extremely useful and versatile precipitation-hardening stainless steels. Armco 17-4 PH is well suited for the magnetic particle inspection requirements of Aerospace Material Specification. Armco 15-5 PH and 17-4 PH are produced in billet, plate, bar, and wire. Also, 15-5 PH is able to meet the stringent mechanical properties required in the aerospace and nuclear industries. Both products are easy to heat treat and machine, making them very useful in many applications.

Johnson, Howard T.↗
NASA NTRS2007

Detailed Analysis of Indian Summer Monsoon Rainfall Processes with Modern/High-Quality Satellite Observations

We examine, in detail, Indian Summer Monsoon rainfall processes using modernhigh quality satellite precipitation measurements. The focus here is on measurements derived from three NASA cloud and precipitation satellite missionslinstruments (TRMM/PR&TMI, AQUNAMSRE, and CLOUDSATICPR), and a fourth TRMM Project-generated multi-satellite precipitation measurement dataset (viz., TRMM standard algorithm 3b42) -- all from a period beginning in 1998 up to the present. It is emphasized that the 3b42 algorithm blends passive microwave (PMW) radiometer-based precipitation estimates from LEO satellites with infi-ared (IR) precipitation estimates from a world network of CEO satellites (representing -15% of the complete space-time coverage) All of these observations are first cross-calibrated to precipitation estimates taken from standard TRMM combined PR-TMI algorithm 2b31, and second adjusted at the large scale based on monthly-averaged rain-gage measurements. The blended approach takes advantage of direct estimates of precipitation from the PMW radiometerequipped LEO satellites -- but which suffer fi-om sampling limitations -- in combination with less accurate IR estimates from the optical-infrared imaging cameras on GEO satellites -- but which provide continuous diurnal sampling. The advantages of the current technologies are evident in the continuity and coverage properties inherent to the resultant precipitation datasets that have been an outgrowth of these stable measuring and retrieval technologies. There is a wealth of information contained in the current satellite measurements of precipitation regarding the salient precipitation properties of the Indian Summer Monsoon. Using different datasets obtained from the measuring systems noted above, we have analyzed the observations cast in the form of: (1) spatially distributed means and variances over the hierarchy of relevant time scales (hourly I diurnally, daily, monthly, seasonally I intra-seasonally, and inter-annually), (2) time series at these different time scales taken as area-averages over the hierarchy of relevant space scales (Indian sub-Division, Indian sub-continent, and Circumambient Indian Ocean), (3) principal autocorrelation and cross-correlation structures over various monsoon space-time domains, (4) diurnally modulated amplitude-phase properties of rain rates over different monsoon space-time domains, (5) foremost rain rate probability distributions intrinsic to monsoon precipitation, and (6) behavior of extreme events including occurrences of flood and drought episodes throughout the course of inter-annual monsoon processes.

Smith, Eric A.↗
NASA NTRS2015

Rift Valley Fever Prediction and Risk Mapping: 2014-2015 Season

Extremes in either direction (+-) of precipitation temperature have significant implications for disease vectors and pathogen emergence and spread Magnitude of ENSO influence on precipitation temperature cannot be currently predicted rely on average history and patterns. Timing of event and emergence disease can be exploited (GAP) in to undertake vector control and preparedness measures. Currently - no risk for ecologically-coupled RVFV activity however we need to be vigilant during the coming fall season due the ongoing buildup of energy in the central Pacific Ocean. Potential for the dual-use of the RVF Monitor system for other VBDs Need to invest in early ground surveillance and the use of rapid field diagnostic capabilities for vector identification and virus isolation.

RVF↗
NASA NTRS2017

The Benefits of Incorporating Shipping Containers into the Climate Change Adaption Plans at NASA Wallops Flight Facility

The National Aeronautics and Space Administration has several centers and facilities located near the coast that are undoubtedly susceptible to climate change. One of those facilities is Wallops Flight Facility on the Eastern Shore of Virginia which is separated into three areas: Main Base, Mainland, and the Island. Wallops Island has numerous buildings and assets that are vulnerable to flood inundation, intense storms, and storm surge. The shoreline of Wallops Island is prone to beach erosion and is slated for another beach replenishment project in 2019. In addition, current climate projections for NASAs centers and facilities, conducted by the Climate Adaptation Science Investigators, warn of inevitable increases in annual temperature, precipitation, sea level rise, and extreme events such as heat waves. The aforementioned vulnerabilities Wallops Island faces in addition to the projections of future climate change reveal an urgency for NASA to adjust how new buildings at its centers and facilities near the coast are built to adapt to the inevitable effects of climate change. Although the agency has made strides to mitigate the effects of climate change by incorporating L.E.E.D. into new buildings that produce less greenhouse gas, the strides for the agency to institute clear climate adaptation policies for the buildings at its centers and facilities near the coast seem to lag behind. As NASA continues to formulate formidable climate change adaptation plans for its centers and facilities, an architectural trend that should be examined for its potential to replace several old buildings at Wallops Island is shipping containers buildings. Shipping containers or Intermodal Steel Building Units offer an array of benefits such as strength, durability, versatility, modular, and since they can be upcycled, they are also eco-friendly. Some disadvantages of shipping containers are they contain harmful chemicals, insulation must be added, fossil fuels must be used to transport them to the site, and multiple ISBUs are needed. However, the benefits of shipping container buildings could be utilized at NASA centers or facilities near the coast such as Wallops Island on new buildings that are designed to adapt to the impending effects of climate change. Thus, this Masters Research Project will explore how those benefits can be incorporated into the climate change adaptation plans at Wallops Island and make recommendations for policy guidelines and shipping container buildings specific to Wallops Island.

Sustainable Design↗
NASA NTRSDate not supplied

Stellar Energetic Particle-driven Production of Biologically Relevant Molecules in Atmospheres of Young Earth-like Exoplanets Around Active G-K Stars

The chemistry of N2, CO2, CH4-rich atmospheres of terrestrial-type exoplanets around active G-K stars is a complex problem: the star's ionizing radiation in the form of X-ray and Extreme UV radiation and the precipitating energetic particles accelerated in coronal mass ejection driven shocks can drive complex chemistry in the exoplanetary atmosphere, and ignite the production of complex molecules (Airapetian et al., 2016). We developed a set of atmospheric models to simulate the formation of organic molecules that can be considered as atmospheric pre-biosignatures from exoplanets around active stars. The model has recently been extended to account for the production of ions, their role in the enhanced chemistry in the lower atmosphere, as well as the interaction of these ions with the aerosols. We applied the photochemical-collisional model to simulate the chemistry of a young terrestrial-type exoplanets resembling the Hadean Earth to highlight the creation of atmospheric pre-biosignatures, relevant greenhouse gases, and the presence of aerosols driven by stellar activity sources. We also discuss the impact of that modified atmospheric chemistry on the exoplanetary climate.

Guillaume Philippe Gronoff↗
NASA NTRSDate not supplied

Stellar Energetic Particle-driven Production of Biologically Relevant Molecules in Atmospheres of Young Earth-like Exoplanets

The chemistry of N2, CO2, CH4-rich atmospheres of terrestrial-type exoplanets around active G-K stars is a complex problem. The star's energetic inputs in the atmospheres take the form of ionizing radiation in the form of X-ray, Extreme UV, as well as precipitating energetic particles that were accelerated in coronal mass ejection-driven shocks. These inputs lead to the ionization and dissociation of the atmospheric species, which enable complex chemical processes resulting in the creation of molecules of interest for both astrobiology and climate (Airapetian et al., 2016; Hayworth et al. 2022). We developed a set of atmospheric models to simulate the formation of organic molecules that can be considered as atmospheric pre-biosignatures from exoplanets around active stars. They take into account the dissociations and ionizations from all the energetic inputs in the atmosphere as well as their role in the enhanced chemistry in the lower atmosphere. In addition, the evaluation of stellar energetic particle fluxes is done using the latest techniques to accurately highlight the depth at which the chemistry is enabled. These models were used to simulate the chemistry of several young terrestrial-type exoplanets resembling the Hadean Earth to highlight the creation of atmospheric pre-biosignatures and relevant greenhouse gases, in function of different scenarios for its atmospheric evolution. This work shows the importance of space weather in the chemical evolution of atmospheres of astrobiological interest.

Guillaume Gronof↗
DOE OSTI2023

Subseasonal Clustering of Atmospheric Rivers Over the Western United States

Abstract The serial occurrence of atmospheric rivers (ARs) along the US West Coast can lead to prolonged and exacerbated hydrologic impacts, threatening flood‐control and water‐supply infrastructure due to soil saturation and diminished recovery time between storms. Here a statistical approach for quantifying subseasonal temporal clustering among extreme events is applied to a 41‐year (1979–2019) wintertime AR catalog across the western United States (US). Observed AR occurrence, compared against a randomly distributed AR timeseries with the same average event density, reveals temporal clustering at a greater‐than‐random rate across the western US with a distinct geographical pattern. Compared to the Pacific Northwest, significant AR clusters over the northern Coastal Range of California and Sierra Nevada are more frequent and occur over longer time periods. Clusters along the California Coastal Range typically persist for 2 weeks, are composed of 4–5 ARs per cluster, and account for over 85% of total AR occurrence. Across the northwest Coast‐Cascade Ranges, clusters account for ∼50% of total AR occurrence, typically last 8–10 days, and contain 3–4 individual AR events. Based on precipitation data from a high‐resolution dynamical downscaling of reanalysis, the fractions of total and extreme hourly precipitation attributable to AR clusters are largest along the northern California coast and in the Sierra Nevada. Interannual variability among clusters highlights their importance for determining whether a particular water year is anomalously wet or dry. The mechanisms behind this unusual clustering are unclear and require further research.

Meteorology & Atmospheric Sciences↗
NASA NTRS2022

File Specification for MERRA-2 Climate Statistics Products

The Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contains a wealth of information that can be used for weather and climate studies. By combining the assimilation of observations with a frozen version of the Goddard Earth Observing System (GEOS), a global analysis is produced at an hourly temporal resolution spanning from January 1980 through present (Gelaro et al., 2017). It can be difficult to parse through a multidecadal dataset such as MERRA-2 to evaluate the interannual variability of weather that occurs on a daily timescale, let alone determine the occurrence of an extreme weather event. Furthermore, it was recognized that standard metrics were needed to evaluate climate change among climate models and international research efforts. As a result of these concerns, the Expert Team on Climate Change Detection and Indices (ETCCDI) developed a set of indices that represent the frequency and intensity of extreme weather events using a daily time series of 2-m air temperature (T2m) and precipitation (Alexander et al., 2016). These indices were used as a basis to comprise a list of fields that represent daily extreme temperature and precipitation events, heatwaves, multi-day precipitation, as well monthly percentile statistics from the MERRA-2 dataset. Also included in this data product is a climatological long term mean and standard deviation representing the interannual variability on a monthly timescale.

MERRA-2↗
DOE OSTI2023

Evaluating the Representations of Atmospheric Rivers and Their Associated Precipitation in Reanalyses With Satellite Observations

Atmospheric rivers (ARs) are filaments of enhanced horizontal moisture transport in the atmosphere. Due to their prominent role in the meridional moisture transport and regional weather extremes, ARs have been studied extensively in recent years. Yet, the representations of ARs and their associated precipitation on a global scale remains largely unknown. In this study, we developed an AR detection algorithm specifically for satellite observations using moisture and the geostrophic winds derived from 3D geopotential height field from the combined retrievals of the Atmospheric Infrared Sounder and the Advanced Microwave Sounding Unit on NASA Aqua satellite. This algorithm enables us to develop the first global AR catalog based solely on satellite observations. The satellite–based AR catalog is then combined with the satellite–based precipitation (Integrated Muti–SatellitE Retrievals for GPM) to evaluate the representations of ARs and AR–induced precipitation in reanalysis products. Here our results show that the spreads in AR frequency and AR length distribution are generally small across data sets, while the spread in AR width is relatively larger. Reanalysis products are found to consistently underestimate both mean and extreme AR–related precipitation. However, all reanalyses tend to precipitate too often under AR conditions, especially over low latitude regions. This finding is consistent with the “drizzling” bias which has plagued generations of climate models. Overall, the findings of this study can help to improve the representations of ARs and associated precipitation in reanalyses and climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Electron precipitation and related aeronomy of the Jovian thermosphere and ionosphere

A comprehensive theoretical model of both the auroral and nonauroral atmosphere and ionosphere of Jupiter is presented and used to study particle precipitation effects in the Jovian upper atmosphere, both at middle and high latitudes. The sources of energy in the model include extreme ultraviolet radiation and energetic electrons. The precipitation of monoenergetic beams of both one and ten keV electrons at high Jovian latitudes are treated in detail, and the effects of higher energy electrons and soft electrons at middle and low latitudes are considered. The effects of this precipitation, such as airglow excitation, ionization, dissociation, and heating are examined. Calculations of the densities of hydrogen, hydrocarbons, and the important ions as well as the temperatures of the neutral, electron, and ion species are included.

Waite, J. H., Jr.↗
NASA NTRS2017

Changing Circulation Structure and Precipitation Characteristics in Asian Monsoon Regions: Greenhouse Warming vs. Aerosol Effects

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land-sea thermal contrast from 1870's to present. During the same period, a mid tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areas of anomalous subsidence associated with the Deep Tropical Squeeze (DTS) [Lau and Kim, 2015]. The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellar overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Rainfall characteristics analyses indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.

Asian monsoon↗
NASA NTRS2020

A Composite Analysis of Snowfall Modes from Four Winter Seasons in Marquette, Michigan

Presented are four winter seasons of data from an enhanced precipitation instrument suite based at the National Weather Service (NWS) Office in Marquette (MQT), Michigan (250–500 cm of annual snow accumulation). In 2014 the site was augmented with a Micro Rain Radar (MRR) and a Precipitation Imaging Package (PIP). MRR observations are utilized to partition large-scale synoptically driven (deep)and surface-forced (shallow) snow events. Coincident PIP and NWS MQT meteorological surface observations illustrate different characteristics with respect to snow event category. Shallow snow events are often extremely shallow, with MRR-indicated precipitation heights of less than 1500 m above ground level. Large vertical reflectivity gradients indicate efficient particle growth, and increased boundary layer turbulence inferred from observations of spectral width implies increased aggregation in shallow snow events. Shallow snow events occur 2 times as often as deep events; however, both categories contribute approximately equally to estimated annual accumulation. PIP measurements reveal distinct regime-dependent snow microphysical differences, with shallow snow events having broader particle size distributions and comparatively fewer small particles and deep snow events having narrower particle size distributions and comparatively more small particles. In addition, coincident surface meteorological measurements indicate that most shallow snow events are associated with surface winds originating from the northwest (over Lake Superior), cold temperatures, and relatively high surface pressures, which are characteristics that are consistent with cold-air outbreaks. Deep snow events have meteorologically distinct conditions that are accordant with midlatitude cyclones and frontal structures, with mostly southwest surface winds, warmer temperatures approaching freezing, and lower surface pressures.

Claire Pettersen↗
NASA NTRS1993

Acclimatization and tolerance to extreme altitude

During the last ten years, two major experiments have elucidated the factors determining acclimatization and tolerance to extreme altitude (over 7000 m). These were the American Medical Research Expedition to Everest, and the low pressure chamber simulation, Operation Everest II. Extreme hyperventilation is one of the most important responses to extreme altitude. Its chief value is that it allows the climber to maintain an alveolar PO2 which keeps the arterial PO2 above dangerously low levels. Even so, there is evidence of residual impairment of central nervous system function after ascents to extreme altitude, and maximal oxygen consumption falls precipitously above 7000 m. The term 'acclimatization' is probably not appropriate for altitudes above 8000 m, because the body steadily deteriorates at these altitudes. Tolerance to extreme altitude is critically dependent on barometric pressure, and even seasonal changes in pressure probably affect climbing performance near the summit of Mt Everest. Supplementary oxygen always improves exercise tolerance at extreme altitudes, and rescue oxygen should be available on climbing expeditions to 8000 m peaks.

NASA Discipline Number 14-10↗
NASA NTRS1986

Altitude variation of EUV emissions and evidence for proton precipitation at low latitudes in the Saturnian atmosphere

Extreme ultraviolet observations of Saturn from Voyager 1 and 2 are analyzed. The Lyman alpha and H2 band emissions extend throughout the upper atmosphere, from the hydrocarbon homopause to well above the exobase. Analysis of the Lyman alpha emissions with a radiative transfer model indicates that the Lyman alpha source temperature is very high. This suggests that energetic protons or hydrogen atoms are responsible for a fraction of the emissions. Calculation of the solar-scattered component of the emissions based on the neutral atmosphere of Smith et al. (1983) reveals that only 1-2 kR out of a total of 3.5 kR of the observed Lyman alpha intensity is due to solar scatter for the Voyager 2 disk observations; the remainder of the Lyman alpha emissions are collisionally excited. The Lyman alpha and H2 bands are constant in longitude but decrease in local time by a factor of 2 from dawn to dusk. This correlation of the Lyman alpha and H2 band intensities is further evidence that most of the Lyman alpha is collisionally excited.

Yelle, R. V.↗
DOE OSTI2021

Machine learning based algorithms for uncertainty quantification in numerical weather prediction models

Complex numerical weather prediction models incorporate a variety of physical processes, each described by multiple alternative physical schemes with specific parameters. The selection of the physical schemes and the choice of the corresponding physical parameters during model configuration can significantly impact the accuracy of model forecasts. There is no combination of physical schemes that works best for all times, at all locations, and under all conditions. It is therefore of considerable interest to understand the interplay between the choice of physics and the accuracy of the resulting forecasts under different conditions. This paper demonstrates the use of machine learning techniques to study the uncertainty in numerical weather prediction models due to the interaction of multiple physical processes. The first problem addressed herein is the estimation of systematic model errors in output quantities of interest at future times, and the use of this information to improve the model forecasts. The second problem considered is the identification of those specific physical processes that contribute most to the forecast uncertainty in the quantity of interest under specified meteorological conditions. In order to address these questions we employ two machine learning approaches, random forests and artificial neural networks. The discrepancies between model results and observations at past times are used to learn the relationships between the choice of physical processes and the resulting forecast errors. Numerical experiments are carried out with the Weather Research and Forecasting (WRF) model. The output quantity of interest is the model precipitation, a variable that is both extremely important and very challenging to forecast. The physical processes under consideration include various micro-physics schemes, cumulus parameterizations, short wave, and long wave radiation schemes. The experiments demonstrate the strong potential of machine learning approaches to aid the study of model errors.

97 MATHEMATICS AND COMPUTING↗