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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Emulating climate extreme indices

We use simple pattern scaling and time-shift to emulate changes in a set of climate extreme indices under future scenarios, and evaluate the emulators' accuracy. We propose a metric for the error in emulation in the context of initial condition ensembles, to specifically characterize the role of internal variability in the emulation performance. Our metric separates systematic emulation errors from unavoidable discrepancies between emulated and target values due to internal variability. We compute the metricis at grid-point scale, and we show geographically resolved results, or aggregate them at global scale. We demonstrate the use of our error metric in the emulation of a suite of temperature and precipitation extreme indices. We test and compare simple pattern scaling and time-shift using a range of trajectories spanning targets inspired by the Paris agreement -- warming to 1.5C and 2.0C from the pre-industrial baseline -- and two of the longer-established trajectories, RCP4.5 and RCP8.5. With this suite of scenarios we can test the effects on the performance of the size of the temperature gap between emulation origin and target. We find that for most indices emulation the dominant source of discrepancy is internal variability. For at least one index, however, counting exceedances of a high temperature threshold, significant portions of the globally aggregated discrepancy and its regional pattern originate from the systematic emulation error. This error exceeds internal variability of both the target and the emulated quantities in large coherent regions at low latitudes, and the explanation can be found in the differential behavior of temperature distributions across latitudes. The metric also highlights a fundamental difference in the two methods related to the simulation of internal variability, which is dampened significantly by simple pattern scaling. This aspect is of consequence when using these methods for specific applications, where preserving variability for uncertainty quantification is deemed important. With this study we offer our metric as a diagnostic tool, facilitating the formulation of scientific hypotheses on the reasons for the error. In the meantime, we show that for many impact relevant indices by now traditional emulation techniques can be accurate within the variations unavoidably introduced by internal variability, establishing the fundamental condition for using their emulation in impact modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Historical and Future Extreme Event Indices for the Colorado River Basin

Extremes events are occurring more frequently and are projected to increase in the future. This data set includes extreme event indices that were generated for the Colorado River basin using data from the Variable Infiltration Capacity hydrologic model. VIC simulations were run using six CMIP5 earth system models (ESMs), two different time periods, (historical, 1970-1999) and future (2070-2099), and for one Representative Concentration Pathway (RCP 8.5). ESMs available are MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR, GFDL-ESM2M, and GFDL-ESM2G. The different indicators include temperature (min/max, freezing days, heating days), precipitation (dry days, max), runoff (min, max), soil moisture (min, max), evapotranspiration (max), snow water equivalent (SWE, max), wind speeds (max), and pressure (min). Detailed information on the indicators, file names, and how they were calculated is included in the README.txt document. Data sets were used to calculate results are in related references Bennett et al. 2020 and Talsma et al. 2021. Details on the VIC model configuration is described in related references Bennett et al. 2018 and Bennett et al. 2017.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Seasonal representation of extreme precipitation indices over the United States in CMIP6 present-day simulations

Realistically representing the present-day characteristics of extreme precipitation has been a challenge for global climate models, which is due in part to deficiencies in model resolution and physics, but is also due to a lack of consistency in gridded observations. In this study, we use three observation datasets, including gridded rain gauge and satellite data, to assess historical simulations from sixteen Coupled Model Intercomparison Project Phase 6 (CMIP6) models. We separately evaluate summer and winter precipitation over the United States (US) with a comprehensive set of extreme precipitation indices, including an assessment of precipitation frequency, intensity and spatial structure. The observations exhibit significant differences in their estimates of area-average intensity distributions and spatial patterns of the mean and extremes of precipitation over the US. In general, the CMIP6 multi-model mean performs better than most individual models at capturing daily precipitation distributions and extreme precipitation indices, particularly in comparison to gauge-based data. Also, the representation of the extreme precipitation indices by the CMIP6 models is better in the summer than winter. Although the ‘standard’ horizontal-resolution can vary significantly across CMIP6 models, from ~0.7° to ~2.8°, we find that resolution is not a good indicator of model performance. Overall, our results highlight common biases in CMIP6 models and demonstrate that no single model is consistently the most reliable across all indices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Indices of extremes: geographic patterns of change in extremes and associated vegetation impacts under climate intervention

Extreme weather events have been demonstrated to be increasing in frequency and intensity across the globe and are anticipated to increase further with projected changes in climate. Solar climate intervention strategies, specifically stratospheric aerosol injection (SAI), have the potential to minimize some of the impacts of a changing climate while more robust reductions in greenhouse gas emissions take effect. However, to date little attention has been paid to the possible responses of extreme weather and climate events under climate intervention scenarios. We present an analysis of 16 extreme surface temperature and precipitation indices, as well as associated vegetation responses, applied to the Geoengineering Large Ensemble (GLENS). GLENS is an ensemble of simulations performed with the Community Earth System Model (CESM1) wherein SAI is simulated to offset the warming produced by a high-emission scenario throughout the 21st century, maintaining surface temperatures at 2020 levels. GLENS is generally successful at maintaining global mean temperature near 2020 levels; however, it does not completely offset some of the projected warming in northern latitudes. Some regions are also projected to cool substantially in comparison to the present day, with the greatest decreases in daytime temperatures. The differential warming–cooling also translates to fewer very hot days but more very hot nights during the summer and fewer very cold days or nights compared to the current day. Extreme precipitation patterns, for the most part, are projected to reduce in intensity in areas that are wet in the current climate and increase in intensity in dry areas. We also find that the distribution of daily precipitation becomes more consistent with more days with light rain and fewer very intense events than currently occur. In many regions there is a reduction in the persistence of long dry and wet spells compared to present day. However, asymmetry in the night and day temperatures, together with changes in cloud cover and vegetative responses, could exacerbate drying in regions that are already sensitive to drought. Overall, our results suggest that while SAI may ameliorate some of the extreme weather hazards produced by global warming, it would also present some significant differences in the distribution of climate extremes compared to the present day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiple Indicators of Extreme Changes in Snow-Dominated Streamflow Regimes, Yakima River Basin Region, USA

Snow plays a major role in the hydrological cycle. Variations in snow duration and timing can have a negative impact on water resources. Excluding predicted changes in snowmelt rates and amounts could result in deleterious infrastructure, military mission, and asset impacts at military bases across the US. A change in snowpack can also lead to water shortages, which in turn can affect the availability of irrigation water. We performed trend analyses of air temperature, snow water equivalent (SWE) at 22 SNOTEL stations, and streamflow extremes for selected rivers in the snow-dependent and heavily irrigated Yakima River Basin (YRB) located in the Pacific Northwest US. There was a clear trend of increasing air temperature in this study area over a 30 year period (water years 1991–2020). All stations indicated an increase in average air temperatures for December (0.97 °C/decade) and January (1.12 °C/decade). There was also an upward trend at most stations in February (0.28 °C/decade). In December–February, the average air temperatures were 0.82 °C/decade. From these trends, we estimate that, by 2060, the average air temperatures for December–February at most (82%) stations will be above freezing. Furthermore, analysis of SWE from selected SNOTEL stations indicated a decreasing trend in historical SWE, and a shift to an earlier peak SWE was also assumed to be occurring due of the shorter snow duration. Decreasing trends in snow duration, rain-on-snow, and snowmelt runoff also resulted from snow modeling simulations of the YRB and the nearby area. We also observed a shift in the timing of snowmelt-driven peak streamflow, as well as a statistically significant increase in winter maximum streamflow and decrease in summer maximum and minimum streamflow trends by 2099. From the streamflow trends and complementary GEV analysis, we show that the YRB basin is a system in transition with earlier peak flows, lower snow-driven maximum streamflow, and higher rainfall-driven summer streamflow. This study highlights the importance of looking at changes in snow across multiple indicators to develop future infrastructure and planning tools to better adapt and mitigate changes in extreme events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗
DOE OSTI2024

Floods of Egypt’s Nile in the 21st century

Extreme precipitation and flooding events are rising globally, necessitating a thorough understanding and sustainable management of water resources. One such setting is the Nile River’s source areas, where high precipitation has led to the filling of Lake Nasser (LN) twice (1998–2003; 2019–2022) in the last two decades and the diversion of overflow to depressions west of the Nile, where it is lost mainly to evaporation. Using temporal satellite-based data, climate models, and continuous rainfall-runoff models, we identified the primary contributor to increased runoff that reached LN in the past two decades and assessed the impact of climate change on the LN’s runoff throughout the twenty-first century. Findings include: (1) the Blue Nile subbasin (BNS) is the primary contributor to increased downstream runoff, (2) the BNS runoff was simulated in the twenty-first century using a calibrated (1965–1992) rainfall-runoff model with global circulation models (GCMs), CCSM4, HadGEM3, and GFDL-CM4.0, projections as model inputs, (3) the extreme value analysis for projected runoff driven by GCMs’ output indicates extreme floods are more severe in the twenty-first century, (4) one adaptation for the projected twenty-first century increase in precipitation (25–39%) and flood (2%-20%) extremes is to recharge Egypt’s fossil aquifers during high flood years.

Climate change↗
NASA NTRSDate not supplied

Applied Uses of MERRA Reanalyses: Current and Future Prospects

During the initial planning of the Modern Era Retrospective-analysis for Research and Applications (MERRA), the project was envisioned to become a tool for applied sciences and decision makers, as well as weather and climate research. MERRA was the first reanalysis to provide data at 1 hourly frequencies. After discussions with wind energy users, 50m above the surface winds were included in the data collection to begin to represent the environment at the turbine height. MERRA-2 was the first reanalysis to include interactive and assimilated aerosols. From these, PM 1, 2.5 and 10 records have been computed and contribute to the climate and health sector. The US Center for Disease Control is accessing MERRA-2 data for comparison along with their health data. MERRA-2 Extreme Indices have been computed from the high frequency data (e.g. precipitation maxima, heat waves and fire weather). These have been used to characterize the changing extremes in the United States and around the globe as well as the weather associated with the extremes. The next-generation, MERRA-21C, includes increased resolution (25km) and continues to provide innovative Earth system data. For example, a boundary layer collection will provide constant height level data starting at 100m, continuing up to 4000m. This will provide detailed information about the boundary layer processes that greatly affect the biosphere. Chemical tracers for constituents are included in the system. The ensemble data assimilation is run with 32 members, and the variance for critical variables are stored. We will explore the use of this variance as one measure of uncertainty relevant for applied uses, which has not been included in any MERRA reanalysis. We will discuss use case scenarios developed to engage with the energy and financial sectors, to better understand their needs for climate data. Prospects for further downscaling of reanalyses will also be explored.

Michael Bosilovich↗
NASA NTRS1988

Dynamics of exploding magma chambers: Implications for K-T volcanism and mass extinctions

Although it is well known that unconfined chemical explosives may yield pressures to several megabars on detonation in air, the explosive literature has yet to be accessed by some contributors to the volcanological literature who've indicated that pressures in excess of the overburden and/or tensile cannot be obtained. Idealized ballistic assessments of pressures internal to volcanoes yield pressures in the hundreds of kilobar range upon correction by addition of friction, etc. Previous assessments of exploding magma chamber pressure have been made from the characteristics of the Mt. St. Helens explosion. A variety of methods yield pressures of similar value: at least hundreds of kilobars. Such results are consistent with free energy requirements for quench supersaturation explosion, a process occurring in solidifying industrial melts. Several reviews of geochemical literature emphasize the carbon event at the Cretaceous-Tertiary (K-T) boundary as being an indicator of a massive dump of CO2 derived from the mantle and entering the atmosphere by extensive global volcanism. Oxygen isotope data indicates extreme warming at the end of the Cretaceous which is consistent with a greenhouse effect attending the CO2 event. Reaction rate equations for the quench supersaturation explosion mechanism indicated, are consistent with the rise in pressure to 30 kbar on solidification of magmatic melts, these pressures limited by the strength of the experimental apparatus.

Rice, A. R.↗
NASA NTRS2016

Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

MERRA↗
DOE OSTI2025

High-Resolution Fire Weather Index Data for the Conterminous US (1980–2099), Version 1

This dataset presents a suite of high-resolution fire weather index datasets calculated from observation (gridMet, Livneh, Daymet V4), reanalysis (AgERA5), downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Aside from the daily FWI datasets, we also include a set of FWI extreme indicators at annual, seasonal, and monthly scales, including 1) fwixx: maximum FWI; 2) fwisa: mean FWI. For annual fwisa, it refers to the season with the maximum seasonal average; 3) fwils: Length of fire season over a specified period, where fire season is defined as the days exceeding the median value of the normalized FWI during the reference period (1980-1984); 4) fwixd: Number of extreme fire weather days over a specified period, where extreme day is defined as the day with FWI > the 95th percentile of the FWI during the reference period (1980-1984). All FWI datasets cover 1980-2020 baseline and the model simulated products including the downscaled products additionally include 2021-2099 near-future periods under the high-end (SSP585) emission scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mechanisms of Projected Changes in Thunderstorm Downburst Environments Across the United States

Responses of downdraft convective available potential energy (DCAPE) to global warming were investigated using the Community Earth System Model (CESM2) under a high‐emission scenario through the year 2100. DCAPE is projected to increase by 5%–12% on average in most areas, independently of wind shear. A diagnostic of downdraft buoyancy is introduced to understand the mechanisms of DCAPE responses. Much of the increase in mean DCAPE is temperature‐driven, with additional contributions from changes in relative humidity and downdraft origin heights. However, extreme values increase at much faster rates than can be explained by local warming. In winter, the latitude of significant DCAPE and CAPE shifts poleward by more than 5° due to larger changes in downburst environments within midlatitude cyclones. The projected increase in cold‐season extremes indicates an interaction between weather events and warming trends that increases the potential for downbursts and straight‐line winds in winter.

Williams, Ian N. [Iowa State Univ., Ames, IA (Unit↗
DOE OSTI2026

Effect of non-stoichiometry and pressure on superconductivity in topological semimetal PdTe

Research into topological superconductivity has been at the forefront of condensed matter physics due to both fundamental interest and potential applications in quantum computing. PdTe, is such a superconductor with a transition temperature T c ∼ 4.5 K and exhibits a nontrivial topological electronic structure, thus receiving significant attention. We report an experimental and theoretical investigation of the pressure effect on superconductivity by applying chemical non-stoichiometry and hydrostatic pressure. While T c decreases with increasing pressure through electrical resistivity, magnetization, and specific heat measurements, chemical pressure has a distinct impact from hydrostatic pressure, which could increase T c by creating negative pressure via non-stoichiometric Pd x Te with x > 1. Accompanied with this is a sign change of the Hall coefficient from negative at x < 1 to positive at x > 1. This indicates extreme sensitivity of the electronic structure to chemical non-stoichiometry, which occurs as a Pd vacancy for x < 1 and Pd interstitial for x > 1.

nonstoichiometry↗
DOE OSTI2023

Superconducting properties and gap structure of the topological superconductor candidate Ti 3 Sb

Here, we present a study of the superconducting properties of the candidate topological superconductor Ti 3 Sb. Electrical transport measurements show zero resistance with a T c,onset of ≈ 5.9 K with a transition width ΔT c ≈ 0.6 K. The superconducting phase boundaries as derived from magnetotransport and magnetic susceptibility measurements agree well. We estimate an upper critical field B c2 (0) ≈ 4.5 T. A Ginzburg-Landau (GL) analysis yields values of the coherence length and penetration depth of ξ = 6.2 nm and λ = 340 nm, respectively, and a GL parameter κ ≈ 55, indicating extreme type-II behavior. Furthermore, we observe a step height in the specific heat $\frac{Δ C_e}{γ T_c}$ ≈ 1.61 ± 0.24 (with T c = 4.8 ± 0.4 K), a value larger than the Bardeen-Cooper-Schrieffer value of 1.43, suggesting modest coupling. Measurements of the temperature dependence of the London penetration depth via the tunnel-diode oscillator technique down to ≈ 450 mK show a full superconducting gap, consistent with a conventional s-wave gap structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

The CORDEX-CORE EXP-I Initiative: Description and Highlight Results from the Initial Analysis

Here we describe the first effort within the Coordinated Regional Climate Downscaling Experiment–Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of twenty-first-century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over nine CORDEX domains at ~25-km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, and energy production. They show that the CORDEX-CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX-CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors, and climate service activities. The future of the CORDEX-CORE initiative is also discussed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1965

Ground testing at MSFC

The large-scale field collection of acoustic data and their analysis are described in this review. The entire sound-field program has the purpose of solving complex problems of excessive noise propagation associated with the static test firing of large space-booster powerplants. The site of data collection has been Mississippi Test Facility (MTF), where far-field sound-propagation and correlated meteorological measurements were initiated in 1962. The statistical evaluation of sound-measurement data shows that the polar distribution of sound in the springtime (at MTF) is determined mainly by the temperature field of the atmosphere. Greater deformation of sound-intensity polar distribution occurs in the autumn as a result of the influence of the wind field. The data on sound attenuation as a function of distance from its source revealed attenuation in excess of the expected magnitude. The excess was mainly between 1 and 10 kilometers from the source, with maximum attenuation (17 to 18 decibels) near 6 kilometers. Excess sound attenuation was compared with calculated sound dispersion. For all sound frequencies in all seasons the deviation between reference and empirical attenuation values formed a bell-shaped distribution on a semilogarithmic plot. The physical causes for the sound- attenuation behavior are considered to be atmospheric diffraction and scattering effects. Statistical analysis of sod-intensity extremes indicated amplification of the sound signals by focusing which could be expected along selected azimuths. Empirical amplification values showed the maximum occurring in winter (50 decibels at 22 kilometers). For the analysis of correlation between empirical sound data and local atmospheric sound- propagation conditions, #e concept of analytical classification of sound-velocity profiles has been developed. Examination of over a quarter-million individual sound-velocity profiles indicates that 33 profile types for heights up to 3 kilometers constitute the empirical possibilities of sound-propagation conditions in southeastern United States. Since the focusing qualities of each sound- velocity profile can be determined as a class characteristic, the overall probabilities of focusing occurrence can he obtained. The severity of focusing, as based upon lateral spread of focusing areas, has been determined. The data for MTF indicate focusing is most severe in winter, with the direction toward east being most affected. Sound propagation is a fluctuating phenomenon because atmospheric conditions vary continuously. A measuring system for analyzing the nonstationary sound-propagation phenomena has been established. The analysis of the acoustic fluctuation data is sup- posed to provide "dynamic” perturbation functions of sound, which are to be superimposed on the related characteristic sound-velocity-profile type. The ultimate result of the program will be the establishment of reliable contingency tables showing the relationship between atmospheric parameters and far-field sound intensities. These data will be the basis for more accurate sound-propagation forecasting for static firing tests.

STATIC TESTING↗
NASA NTRS1976

Surface slope probabilities from the spectra of weak radar echoes - Application to Mars

A method is described for stabilizing the inversion of the power spectra of comparatively weak radar echoes from Mars. It is noted that such stabilization is necessary for echoes with S/N power-spectral densities of order unity as well as for those with broad spectral distributions. The method is applied to the Martian surface, using two data sets obtained with radars of approximately 12.5-cm wavelength. The resulting slope probabilities are interpreted in terms of diffuse and quasi-specular scatter, and values of rms slope are calculated. The results for a sample of Martian locations clearly indicate extreme variations in the local nature of the surface and yield evidence for an apparent planetwide distribution of roughness that may be due to extreme slopes, surface or subsurface rock populations, or a combination of these.

Lipa, B.↗