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At least 1,567 records · Page 87

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗

Inferring the photolysis rate of NO 2 in the stratosphere based on satellite observations

NO and NO 2 (NO x ) play major roles in both tropospheric and stratospheric chemistry. This paper provides a novel method to obtain a global and accurate photolysis rate for NO 2 based on satellite data. The photolysis rate J(NO 2 ) dominates the daytime diurnal variation of NO x photochemistry. Here the spatial variation of J(NO 2 ) at 50–90°S in December from 20–40km is obtained using data from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) experiment. Because NO and NO 2 rapidly exchange with one another in the daytime, J(NO 2 ) can be attained assuming steady state, and the results are shown to be consistent with model results. The J(NO 2 ) value decreases as the solar zenith angle increases and has a weak altitude dependence. A key finding is that satellite-derived J(NO 2 ) increases in the polar regions, in good agreement with model predictions, due to the effects of ice and snow on surface albedo. Thus, the method presented here provides an observation-based check on the role of albedo in driving polar photochemistry.

54 ENVIRONMENTAL SCIENCES↗

Interplanetary gas. XXVII - A catalog of disconnection events in cometary plasma tails

A catalog of 72 disconnection event (DES) in cometary plasma tails is presented as a basic data source for cometary and solar wind analysis. The events span the period 1892-1976, and are characterized on the basis of photographic observations. From the observed kinematics of rejected tails, methods are derived to calculate an estimated time of tail disconnection for each DE, either from the average law of motion for DEs lacking velocity measurements, or from the observed velocities. The geometric circumstances of each DE at the times of separation and observation are also tabulated, and a brief description of each event is presented.

Niedner, M. B., Jr.↗

An analysis of nearfield normal mode amplitude anomalies of the Landers earthquake

The 1992 Landers earthquake (M(sub w) = 7.3) occurred in the middle of the TERRAscope network. Long-period Rayleigh waves recorded at the TERRAscope stations (delta less than or = 3 deg) after traveling around the Earth show large amplitude anomalies, one order of magnitude larger than spherical Earth predictions up to a period of about 600 s. The ground motions over the epicentral region at and after the arrival of R4-5 are in phase at all stations. These observations are inconsistent with the nearly vertical strike slip mechanism of the Landers earthquake. Synthetic seismograms for a rotating, elliptic, and laterally heterogeneous Earth model calculated by the variational method agree well with the observed waveforms. Calculations for various 3D Earth models demonstrate that the amplitudes are very sensitive to the large scale aspherical structure in the crust and the mantle. The anomalies for modes shorter than 300 s period can be explained by lateral heterogeneity shallower than the upper mantle. Rotation of the Earth and lower mantle heterogeneity are required to explain mode amplitudes at longer periods. Current whole mantle seismic tomographic models can fully explain the observed amplitudes longer than 300 s. To assess the effect of the high order lateral heterogeneity in the mantle more precise estimate of the crustal correction is required.

Watada, Shingo↗

Infalling Envelopes and Pre-Main Sequence Disks

The goal of this project is to understand the observed infrared emission of young stellar objects, and explore the implications of this emission for the evolution of dusty envelopes and circumstellar disks. We are using sophisticated radiative transfer methods to compare models with observations, thereby making critical tests of the standard picture of low-mass star formation.

Hartmann, Lee W.↗

Characterizing the Reproducibility of Noisy Quantum Circuits

The ability of a quantum computer to reproduce or replicate the results of a quantum circuit is a key concern for verifying and validating applications of quantum computing. Statistical variations in circuit outcomes that arise from ill-characterized fluctuations in device noise may lead to computational errors and irreproducible results. While device characterization offers a direct assessment of noise, an outstanding concern is how such metrics bound the reproducibility of a given quantum circuit. Here, we first directly assess the reproducibility of a noisy quantum circuit, in terms of the Hellinger distance between the computational results, and then we show that device characterization offers an analytic bound on the observed variability. We validate the method using an ensemble of single qubit test circuits, executed on a superconducting transmon processor with well-characterized readout and gate error rates. The resulting description for circuit reproducibility, in terms of a composite device parameter, is confirmed to define an upper bound on the observed Hellinger distance, across the variable test circuits. This predictive correlation between circuit outcomes and device characterization offers an efficient method for assessing the reproducibility of noisy quantum circuits.

97 MATHEMATICS AND COMPUTING↗

DC-Ripple-Energy Adaptive-Minimization (DREAM) Modulation Scheme for a High Power Density Inverter

The DC bus capacitor is one of the major power-density and reliability hurdles of electric drive systems. It is hard to shrink because it is constrained by the DC bus RMS ripple current, which is only load dependent. A dual-inverter based segmented drive can reduce the ripple current by ~50% compared to a non-segmented case. This paper analyzes the origin of this ripple current and points out the path for minimization. An optimal DC-ripple-energy adaptive-minimization (DREAM) modulation method is proposed to further reduce the ripple current. It is observed in experimental results that the proposed method can achieve additional 38% reduction over the traditional segmented drive system.

Xue, Lincoln↗

Utilization of nuclear methods for materials analysis and the determination of concentration gradients

The various types of nuclear chemical analysis methods are discussed. The possibilities of analysis through activation and direct observation of nuclear reactions are described. Such methods make it possible to analyze trace elements and impurities with selectivity, accuracy, and a high degree of sensitivity. Such methods are used in measuring major elements present in materials which are available for analysis only in small quantities. These methods are well suited to superficial analyses and to determination of concentration gradients; provided the nature and energy of the incident particles are chosen judiciously. Typical examples of steels, pure iron and refractory metals are illustrated.

Darras, R.↗

Separating Magnetospheric and Heliospheric SWCX in X-ray Spectra

Solar wind charge exchange (SWCX) emission contaminates all astrophysical observations in X-rays regardless of the direction. This contamination is particularly problematic when measuring astrophysical plasma temperatures due to the similar spectral distribution of the two phenomena. Since its discovery, literature has distinguished between SWCX emission resulting from solar wind-neutral interactions within the Earth’s magnetosphere, called magnetospheric SWCX, and similar interactions occurring more generally throughout the heliosphere, called heliospheric SWCX. Previous work demonstrated accurate modeling of the heliospheric SWCX contribution for astrophysical observations performed at low ecliptic latitude with HaloSat, a CubeSat X-ray mission of medium spectral resolution. Here, we apply this model to similarly orchestrated observations to measure the magnetospheric SWCX contribution separately from the heliospheric SWCX and the astrophysical background contributions. We describe our observational strategy, the heliospheric SWCX model used, and our spectral fitting methods. In particular, we report on four observations with lines of sight through the Earth’s magnetospheric flank with total O VII line fluxes at least 3σ above that predicted by the heliospheric SWCX model and the astrophysical background, possibly indicative of magnetospheric SWCX. We then discuss the excess emission in comparison with available magnetospheric SWCX simulations requested through the Community Coordinated Modeling Center.

X-ray↗

Modeling active region transient brightenings observed with X-ray telescope as multi-stranded loops

Strong evidence exists that coronal loops as observed in extreme ultraviolet and soft X-rays may not be monolithic isotropic structures, but can often be more accurately modeled as bundles of independent strands. Modeling the observed active region transient brightenings (ARTBs) within this framework allows for the exploration of the energetic ramifications and characteristics of these stratified structures. Here we present a simple method of detecting and modeling ARTBs observed with the Hinode X-Ray Telescope (XRT) as groups of zero-dimensional strands, which allows us to probe parameter space to better understand the spatial and temporal dependence of strand heating in impulsively heated loops. This partially automated method can be used to analyze a large number of observations to gain a statistical insight into the parameters of coronal structures, including the number of heating events required in a given model to fit the observations. In this article, we present the methodology and demonstrate its use in detecting and modeling ARTBs in a sample data set from Hinode/XRT. These initial results show that, in general, multiple heating events are necessary to reproduce observed ARTBs, but the spatial dependence of these heating events cannot yet be established.

79 ASTRONOMY AND ASTROPHYSICS↗

Secondary Crash Identification using Crowdsourced Waze User Reports

Secondary crashes are crashes that occur as a result of the nonrecurrent congestion originating from primary crashes, and always have a greater impact on safety and traffic than a single crash. A better understanding of secondary crashes would benefit traffic incident management, and this requires accurate identification of secondary crashes. This study explores using crowdsourced Waze user reports to identify secondary crashes. Here, a network-based clustering algorithm is proposed to extract the primary crash cluster, including all user reports originating from the primary crash, and any crash that occurred within the cluster would be a secondary crash. This method works as a filter to select accurate primary–secondary relationships, thus precisely identifying secondary crashes. A case study is performed with crashes occurring from June to December 2019 on a 30-mi stretch of I-40 in Knoxville, TN. A static threshold method (crash duration and 10 mi) was used to preselect the potential primary–secondary crash pairs, and 75 out of 708 crashes were identified as potential secondary crashes. Based on the preselected primary–secondary crash pairs, 17 secondary crashes were obtained with the proposed method and the results were compared with one of the commonly used methods, the speed contour plot method. Though the proposed method captured fewer secondary crashes, it did identify several secondary crashes that could not be observed with the speed contour plot method. The results showed the applicability of the method and the potential of crowdsourced Waze user reports in secondary crash identification.

99 GENERAL AND MISCELLANEOUS↗

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Uncertainty↗

Separating Cloud and Drizzle Signals in Radar Doppler Spectra Using a Parametric Time Domain Method

The ability to separate cloud and drizzle returns in active remote sensing observations is important for understanding the microphysics of clouds and precipitation. Yet, robust separations remain challenging in radar remote sensing. Prior methods for cloud and drizzle separation for radar observations use the properties of the Doppler spectra such as skewness. However, these methods have challenges when the drizzle becomes dominant in the observation volume. This paper presents a parametric time domain method (PTDM) that separates cloud and drizzle using the Doppler spectra measurements without assuming any prior properties of cloud and drizzle. The advantage of PTDM is that it can estimate the signal properties in the time domain and can obtain the cloud and drizzle estimates simultaneously. Based on our radar signal simulations, the uncertainty in estimated power and velocity from PTDM are within 2 dB and 0.02 m s -1 , respectively. We have also evaluated the PTDM algorithm using observations from the Atmospheric Radiation Measurement (ARM) Program W-band cloud radar in the Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP-MBL) campaign at the Azores in 2009–10. Two cases corresponding to light and moderate drizzling conditions are considered for the study. The statistics of the estimates obtained show that the PTDM method performs well in separating the cloud and drizzle returns. Finally, the estimated cloud and drizzle reflectivity from PTDM were used to retrieve their corresponding microphysical properties, showing that the retrieved liquid water path agrees to 25 g m -2 with the benchmark microwave method.

Engineering↗

A new ionospheric electron precipitation module coupled with RAM-SCB within the geospace general circulation model

Electron precipitation down to the atmosphere due to wave-particle scattering in the magnetosphere contributes significantly to the auroral ionospheric conductivity. In order to obtain the auroral conductivity in global MHD models that are incapable of capturing kinetic physics in the magnetosphere, MHD parameters are often used to estimate electron precipitation flux for the conductivity calculation. Such an MHD approach, however, lacks self-consistency in representing the magnetosphere-ionosphere coupling processes. In this study we improve the coupling processes in global models with a more physical method. We calculate the physics-based electron precipitation from the ring current and map it to the ionospheric altitude for solving the ionospheric electrodynamics. In particular, we use the BATS-R-US (Block Adaptive Tree Scheme-Roe type-Upstream) MHD model coupled with the kinetic ring current model RAM-SCB (Ring current-Atmosphere interaction Model with Self-Consistent Magnetic field (B)) that solves pitch angle-dependent electron distribution functions, to study the global circulation dynamics during the 25–26 January 2013 storm event. Since the electron precipitation loss is mostly governed by wave-particle resonant scattering in the magnetosphere, we further investigate two loss methods of specifying electron precipitation loss associated with wave-particle interactions: (1) using pitch angle diffusion coefficients D αα (E,α) determined from the quasi-linear theory, with wave spectral and plasma density obtained from statistical observations (named as “diffusion coefficient method”) and (2) using electron lifetimes τ(E) independent on pitch angles inferred from the above diffusion coefficients (named as “lifetime method”). We found that both loss methods demonstrate similar temporal evolution of the trapped ring current electrons, indicating that the impact of using different kinds of loss rates is small on the trapped electron population. Furthermore, for the precipitated electrons, the lifetime method hardly captures any precipitation in the large L shell (i.e., 4 < L < 6.5) region, while the diffusion coefficient method produces much better agreement with NOAA/POES measurements, including the spatial distribution and temporal evolution of electron precipitation in the region from the premidnight through the dawn to the dayside. Further comparisons of the precipitation energy flux to DMSP observations indicates that the new physics-based precipitation approach using diffusion coefficients for the ring current electron loss can explain the diffuse electron precipitation in the dawn sector, such as the enhanced precipitation flux at auroral latitudes and flux drop near the subauroral latitudes, but the traditional MHD approach largely overestimates the precipitation flux at lower latitudes.

58 GEOSCIENCES↗

Linear Accelerator-Based Radiosurgery Alone for Arteriovenous Malformation: More Than 12 Years of Observation

Purpose: Although radiosurgery is an accepted treatment method for intracranial arteriovenous malformations (AVMs), its long-term therapeutic effects have not been sufficiently evaluated, and many reports of long-term observations are from gamma-knife facilities. Furthermore, there are few reported results of treatment using only linear accelerator (LINAC)-based radiosurgery (LBRS). Methods and Materials: Over a period of more than 12 years, we followed the long-term results of LBRS treatment performed in 51 AVM patients. Results: The actuarial obliteration rates, after a single radiosurgery session, at 3, 5, 10, and 15 years were 46.9%, 54.0%, 64.4%, and 68.0%, respectively; when subsequent radiosurgeries were included, the rates were 46.9%, 61.3%, 74.2%, and 90.3%, respectively. Obliteration rates were significantly related to target volumes ≥4 cm{sup 3}, marginal doses ≥12 Gy, Spetzler-Martin grades (1 vs other), and AVM scores ≥1.5; multivariate analyses revealed a significant difference for target volumes ≥4 cm{sup 3}. The postprocedural actuarial symptomatic radiation injury rates, after a single radiation surgery session, at 5, 10, and 15 years were 12.3%, 16.8%, and 19.1%, respectively. Volumes ≥4 cm{sup 3}, location (lobular or other), AVM scores ≥1.5, and the number of radiosurgery were related to radiation injury incidence; multivariate analyses revealed significant differences associated with volumes ≥4 cm{sup 3} and location (lobular or other). Conclusions: Positive results can be obtained with LBRS when performed with a target volume ≤4 cm{sup 3}, an AVM score ≤1.5, and ≥12 Gy radiation. Bleeding and radiation injuries may appear even 10 years after treatment, necessitating long-term observation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Anthropogenic influence on extreme precipitation over global land areas seen in multiple observational datasets

The intensification of extreme precipitation under anthropogenic forcing is robustly projected by global climate models, but highly challenging to detect in the observational record. Large internal variability distorts this anthropogenic signal. Models produce diverse magnitudes of precipitation response to anthropogenic forcing, largely due to differing schemes for parameterizing subgrid-scale processes. Meanwhile, multiple global observational datasets of daily precipitation exist, developed using varying techniques and inhomogeneously sampled data in space and time. Previous attempts to detect human influence on extreme precipitation have not incorporated model uncertainty, and have been limited to specific regions and observational datasets. Using machine learning methods that can account for these uncertainties and capable of identifying the time evolution of the spatial patterns, we find a physically interpretable anthropogenic signal that is detectable in all global observational datasets. Machine learning efficiently generates multiple lines of evidence supporting detection of an anthropogenic signal in global extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗

Fluctuations of the gluon distribution from the small- x effective action

The computation of observables in high-energy QCD involves an average over stochastic semiclassical small-x gluon fields. The weight of various configurations is determined by the effective action. We introduce a method to study fluctuations of observables, functionals of the small-x fields, which does not explicitly involve dipoles. We integrate out those fluctuations of the semiclassical gluon field under which a given observable is invariant. Thereby we obtain the effective potential for that observable describing its fluctuations about the average. Here, we determine explicitly the effective potential for the covariant gauge gluon distribution both for the McLerran-Venugopalan (MV) model and for a (nonlocal) Gaussian approximation for the small-x effective action. This provides insight into the correlation of fluctuations of the number of hard gluons versus their typical transverse momentum. We find that the spectral shape of the fluctuations of the gluon distribution is fundamentally different in the MV model, where there is a pileup of gluons near the saturation scale, versus the solution of the small-x JIMWLK renormalization group, which generates essentially scale-invariant fluctuations above the absorptive boundary set by the saturation scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗