Engineering topics

Chang, Y.

Publications and source records attributed to Chang, Y..

13 records

DOE OSTI2024

Demonstration of the HeRALD superfluid helium detector concept

The SPICE/HeRALD collaboration is performing research and development to enable studies of sub-GeV dark matter models using a variety of target materials. Here we report our recent progress on instrumenting a superfluid 4 He target mass with a transition-edge sensor based calorimeter to detect both atomic signals (scintillation) and 4 He quasiparticle (phonon and roton) excitations. The sensitivity of HeRALD to the critical “quantum evaporation” signal from 4 He quasiparticles requires us to block the superfluid film flow to the calorimeter. We have developed a heat-free film-blocking method employing an unoxidized Cs film, which we implemented in a prototype “HeRALD v0.1” detector of ~10 g target mass. This article reports initial studies of the atomic and quasiparticle signal channels. Here, a key result of this work is the measurement of the quantum evaporation channel’s gain of 0.15±0.01, which will enable 4 He-based dark matter experiments in the near term. With this gain the HeRALD detector reported here has an energy threshold of 145 eV at 5⁢σ, which would be sensitive to dark matter masses down to 220 MeV/c 2 .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Measurement of Electron Antineutrino Oscillation Amplitude and Frequency via Neutron Capture on Hydrogen at Daya Bay

This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958 days of data. With over 3.6 million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative ν ¯ e rates and energy spectra variation among the near and far detectors gives sin 2 2 θ 13 = 0.075 9 − 0.0049 + 0.0050 and Δ m 32 2 = ( 2.7 2 − 0.15 + 0.14 ) × 10 − 3 eV 2 assuming the normal neutrino mass ordering, and Δ m 32 2 = ( − 2.8 3 − 0.14 + 0.15 ) × 10 − 3 eV 2 for the inverted neutrino mass ordering. This estimate of sin 2 2 θ 13 is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields sin 2 2 θ 13 = 0.0833 ± 0.0022 , which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2020

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the NASA/GMAO Seasonal Forecast System

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO assimilating the different satellite SSS. In general, for all phases of ENSO, SSS assimilation improves forecasts. The far right column compares ensemble means for assimilation of individual and combined SMOS, Aquarius, and SMAP SSS forecasts. Finally, the latest forecasts are presented comparing assimilation versus no- assimilation of satellite SSS for single forecasts over the last year.

Hackert, E.↗

NASA NTRS2019

A Systematic Approach to Isolating the Causes and Impacts of Climate Model Bias Employing Analysis Increments

One of the most promising approaches to isolating the causes and understanding the impacts of climate model formulation errors is through the utilization of information contained in short-term forecast errors. The underlying assumption being that by capturing the errors at the very early stages of growth (before nonlinearities develop), we should be able to associate those errors with specific deficiencies in the model's formulation of the relevant physical processes. Here, we provide an example of utilizing the long-term mean of the 6-hourly analysis increments (first guess forecast minus analysis) produced by MERRA-2 to correct the NASA/GEOS AGCM over well-defined regions, thereby allowing us to quantify how the reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections to reduce the model's climatological biases. We extend previous work (focused on boreal summer) to address the full annual cycle of model bias. A key result is the large seasonality of the errors over the Tibet region and their impacts on the Northern Hemisphere jet biases, and related precipitation and temperature biases over North American. Attempts to correct the phase and amplitude errors of the climatological boreal winter ridge over western North America (a likely key requirement for improving winter climate forecasts over North America) reveal a surprising complexity in the sources of the errors in what is otherwise manifest as a rather simple PNA-like bias structure.

Schubert, S.↗

NASA NTRS2019

Observing System Experiments for Evaluating the Impact of Satellite Sea Surface Salinity on Seasonal Predictions from the GMAO S2S System

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO (El Nino-Southern Oscillation) forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO assimilating the different satellite SSS. In general, for all phases of ENSO, SSS assimilation improves forecasts. The far right column compares ensemble means for assimilation of individual and combined SMOS, Aquarius, SMAP (Soil Moisture and Ocean Salinity, NASA Aquarius, Soil Moisture Active Passive) SSS forecasts. Finally, the latest forecasts are presented comparing assimilation versus no- assimilation of satellite SSS for single forecasts over the last year.

Hackert, E.↗

NASA NTRS2018

Local Versus Remote Contributions of Soil Moisture to Near-Surface Temperature Variability

Soil moisture variations have a straightforward impact on overlying air temperatures, wetter soils can induce higher evaporative cooling of the soil and thus, locally, cooler temperatures overall. Not known, however, is the degree to which soil moisture variations can affect remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various soil moisture states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.

Koster, R.↗

NASA NTRS2017

The North Pacific Summer Jet and Climate Extremes over North America: Mechanisms and Model Biases

The North Pacific summer jet (NPSJ) plays a critical role as a waveguide for weather systems and other sub-seasonal Rossby waves entering North America and therefore has a controlling influence on the warm season weather and climate extremes over much of the continent. In particular, much of the warm season precipitation that occurs over the central United States depends on subseasonal transients that are able to tap moisture from the Gulf of Mexico as they propagate across the continent. The GEOS-5 atmospheric general circulation model (AGCM), like many AGCMs, is deficient in the simulation of the NPSJ. It is shown that the deficiency is composed of: 1) a stunted jet in which the strongest winds are confined to the Asian continent, failing to extend across the North Pacific into the Gulf of Alaska as observed, and 2) a zonally symmetric poleward shift in the jet. These biases combine to impede the eastward propagation of the weather systems into the continent (the stunted jet), and deprive those systems that do enter the continent access to the moisture from the Gulf (the northward shift), leading to a dry bias over the central US. It is shown that the stunted jet bias is the result of too strong heating that occurs just south of the jet core over and near Tibet. Furthermore, it is shown that the poleward shift of the NPSJ can be corrected in the current GEOS-5 AGCM by increasing the vertical resolution. The implications of these results for improving warm season forecasts of extreme events will be discussed.

NPS↗

NASA NTRS2012

A Modeling Study of the Spring 2011 Extreme US Weather Activity

The spring of 2011 was characterized by record-breaking tornadic activity with substantial loss of life and destruction of property. While a waning La Nina and other atmospheric teleconnections have been implicated in the development of these extreme weather events, a quantitative assessment of their causes is still lacking. This study uses high resolution (1/4 lat/lon) GEOS-5 AGCM experiments to quantify the role of SSTs and soil moisture in the development of the extreme weather activity with a focus on April - the month of peak tornadic activity. The simulations, consisting of 22-member ensembles of three-month long simulations (initialized March 1st) reproduce the main features of the observed large-scale changes including the below-normal temperature and above-normal precipitation in the Central US, and the hot and dry conditions to the south. Various sensitivity experiments are conducted to separate the roles of the SST, soil moisture and the initial atmospheric conditions in the development and predictability of the atmospheric conditions (wind shear, moisture, etc.) favoring the severe weather activity and flooding.

Schubert, S.↗

NASA NTRS2003

Perspectives on Forced Predictability

This talk addresses the relationships between weather and El Nino/Southern Oscillation (ENSO) and various other low frequency atmospheric variations such as the Pacific/North American pattern. We focus, in particular, on the predictability of extreme wintertime precipitation events over the continental United States. We first examine fifty years of daily precipitation observations and quantify the leading patterns of winter weather variability. These weather systems, familiar to operational weather forecasters, account for many of the major flooding events on the west coast as well as the major winter snowstorms along the east coast. We next examine the statistics of these storm systems with a particular focus on the occurrence of extreme events. The leading weather systems show varying degrees of linkages to low frequency atmospheric variability. We show, for example, that on seasonal time scales the probability of occurrence of certain types of west coast storms is strongly enhanced by El Nino, while it is reduced during winters with an anomalous trough to the west of the dateline. ENSO also has a strong impact on storms that develop over the Gulf of Mexico and affect much of the eastern United States, with enhanced storminess during El Nino, and reduced storminess during La Nina conditions. We conclude with an example of how well current climate models are able to reproduce the basic linkages between weather and low frequency variability.

Schubert, S.↗

NASA NTRS1999

Seasonal Prediction with the GEOS GCM

A number of ensembles of seasonal forecasts have recently been completed as part of NASA's Seasonal to Interannual Prediction Project (NSIPP). The focus is on the extratropical response of the atmosphere to observed SST anomalies during boreal winter. Each prediction consists of nine forecasts starting from slightly different initial conditions. Forecasts are done for every winter from 1981 to 1995 using Version 2 of the GEOS GCM. Comparisons with six long-term integrations (1978-1995) using the same model are used to separate the contributions of initial and boundary conditions to forecast skill. The forecasts also allow us to isolate the SSt forced response (the signal) from the atmosphere's natural variability (the noise).

Suarez, Max↗

NASA NTRS1999

Potential Predictability of the Monsoon Subclimate Systems

While El Nino/Southern Oscillation (ENSO) phenomenon can be predicted with some success using coupled oceanic-atmospheric models, the skill of predicting the tropical monsoons is low regardless of the methods applied. The low skill of monsoon prediction may be either because the monsoons are not defined appropriately or because they are not influenced significantly by boundary forcing. The latter characterizes the importance of internal dynamics in monsoon variability and leads to many eminent chaotic features of the monsoons. In this study, we analyze results from nine AMIP-type ensemble experiments with the NASA/GEOS-2 general circulation model to assess the potential predictability of the tropical climate system. We will focus on the variability and predictability of tropical monsoon rainfall on seasonal-to-interannual time scales. It is known that the tropical climate is more predictable than its extratropical counterpart. However, predictability is different from one climate subsystem to another within the tropics. It is important to understand the differences among these subsystems in order to increase our skill of seasonal-to-interannual prediction. We assess potential predictability by comparing the magnitude of internal and forced variances as defined by Harzallah and Sadourny (1995). The internal variance measures the spread among the various ensemble members. The forced part of rainfall variance is determined by the magnitude of the ensemble mean rainfall anomaly and by the degree of consistency of the results from the various experiments.

Yang, Song↗

NASA NTRS1986

Simultaneous iterations algorithm for general eigenvalue problems on parallel processors

The method of simultaneous iteration with shift is extended to extraction of m-eigenpairs of a general eigenvalue problem of large order n in a parallel processing environment. The algorithm combines the power method and the Jacobi technique, and reduces to performing four basic operations. Parallel implementation of the algorithm is discussed in detail. The analysis accounts for computation and communication costs, and utilizes a parallel processing architecture of the ensemble type. Expressions for the computational efficiency and speedup are defined as a function of the problem and hardware parameters. Selected representative problems exhibit efficiencies ranging from 60 to 98 percent.

Utku, S.↗

NASA NTRS1969

Information science

Information processing techniques and systems reliability by coding, digital designed methods, retrieval, and communication

Ash, R. B.↗