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Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

Sun-Mack, Sunny↗

Probing strangeness canonical ensemble with K - , Φ(1020) and Ξ - production in Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV

We report on the first multi-differential measurement of φ meson and Ξ - hyperon production as well as the φ/K - and φ/Ξ - ratio in Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV with the STAR experiment under its fixed target configuration at RHIC. φ mesons and Ξ - hyperons are measured through their hadronic decay channels, φ → K+K - and Ξ - → Λπ - . The transverse kinetic energy spectra of K - , φ and Ξ - are presented in different centrality and rapidity intervals. The total production yields and the ratios within a 4π coverage are calculated and compared to thermal model predictions. A calculation within the grand canonical ensemble framework shows a clear discrepancy from our measurement. Our data favor the canonical ensemble approach employing local strangeness conservation with a small strangeness correlation length (r c ≤ 4.2 fm) in 0–10% central Au+Au collisions at $\sqrt{^S{NN}}$ = 3 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Surface Biology and Geology Imaging Spectrometer: A Case Study to Optimize the Mission Design Using Intrinsic Dimensionality

The information content that can be derived from spectroscopic imagery tends to increase with finer ground sampling distance, finer spectral sampling, more frequent revisit, and higher signal-to-noise ratios (SNRs). However, these parameters are not independent, and it is thus impossible to design a space-borne imaging spectrometer to maximize all of them simultaneously. We present an instrument model and simulation environment that enable us to find the optimal combination of these four mission design parameters, using intrinsic dimensionality (ID) as the metric. ID is the size of the signal subspace – the maximum degrees of freedom when noise can be disregarded – and is a metric that is independent of any one particular algorithm or application area. This study is important for upcoming missions such as NASA's Earth System Observatory mission to study the Earth's Surface Biology and Geology (SBG), which will comprise a visible to shortwave infrared spectrometer in addition to a multi-channel thermal radiometer on a separate platform. When evaluating a desert site and a tropical forested site, we find that spectral resolution drives information content, with a significant drop in normalized ID (15–45% decrease) when simulating 15 nm spectral sampling as opposed to 10 nm spectral sampling. However, there was some variation between sites, with the forested site benefiting from 5 nm spectral sampling, whereas the desert site had poorer results at this resolution, due to the impact on noise. At 10 nm spectral sampling, ground sampling distances in the range 30–50 m provided the optimal balance between spatial resolution and SNR, although more frequent revisit, potentially by combining data from multiple missions, would maximize total information content.

Mission design↗

The Multi-Stage History of Mt. Sharp

The Curiosity rover is exploring Gale crater and Mt. Sharp, Gale's 5‐km high central mound. We are investigating the history of alteration and erosion of Mt. Sharp using orbital imagery, spectroscopy and rover observations. Our results suggest a significant time gap between emplacement of the upper and lower sections of the mound. Crater counts show that the lower mound was formed soon after Gale itself, and that it contains distinct units ranging in altitude from approximately ‐4,500 to ‐1,800 m. Spectral data suggest that many units contain phyllosilicates. We found that these clay‐bearing rocks occur in distinct layers concentrated below ‐2,900 m. Parts of the lower mound exhibit a transition from clays to sulfates with increasing altitude. The lower mound shows evidence of flowing water, including canyons and inverted channels. Wind erosion produced km‐scale yardangs and scalloped cliffs. Our mapping shows that many yardangs in the lower mound are clay‐bearing, with a predominant orientation of around N‐S. Curiosity's ground‐level images show myriad fine‐scale, mainly horizontal layers in the lower mound. The rover has found stream beds and conglomerates, indicating that water once flowed on the crater floor. Drilling near the deepest point in Gale produced abundant clay, providing additional evidence of aqueous alteration. Upper mound units range in altitude from ‐2,100 m to +500 m, and mantle the lower mound above an angular unconformity. Most upper mound units are composed of layers. The formation age of the upper mound is unknown, since few craters are preserved. Clay‐bearing layers are detectable in several locations, mainly at altitudes near ‐2,000 m. There is no evidence of water flow, but wind erosion has scalloped the surfaces and edges of layers, and fine‐scale yardangs are common. Correlations between yardangs and clay spectra are apparent only in the lowermost units of the upper mound. Yardang orientations vary, and include N‐S, NW‐SE, and NE‐SW. Upper mound units resemble the planet‐wide Medusae Fossae formation, dated as Hesperian and argued to be composed of ignimbrites. Medusae Fossae layers are easily eroded by wind, and our mapping demonstrates their resemblance to upper mound fine‐scale yardangs. The history of Mt. Sharp started with deposition and lithification of sediments shortly after crater formation. Some lower mound layers were partially altered to clays and sulfates, and water formed streams and canyons. Wind erosion of the lower mound produced large‐scale yardangs, particularly in clay‐rich layers, oriented generally N‐S. Upper mound units were emplaced following a considerable period of wind erosion. The absence of water flow on the upper mound suggests that these units were emplaced after atmospheric loss rendered water unstable at the surface. The shift in dominant wind direction, as indicated by yardang orientations, also argues for a time gap between erosion of the lower and upper mound. These observations are consistent with upper mound units being related to the Hesperian Medusae Fossae formation. During 2014 Curiosity is expected to reach the foot of Mt. Sharp and ascend through the clay‐rich layers, into the sulfate‐rich layers, and possibly past the interface with the upper mound. This will be a unique opportunity to field check geologic models on the surface of Mars.

Allen, C.↗

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗

Generation of Land Surface Reflectance with Combined Geo-KOMPSAT-2A AMI and Himawari 8 AHI Observations

The latest generation of geostationary satellites has opened a new era of Earth observations with unprecedented spatiotemporal resolution and spectral range. Together with GOES 16/17 ABI, FY4-A AGRI, and Himawari-8 AHI, a new Korean geostationary satellite (Geo-KOMPSAT-2A AMI) has operationally collected a full-disk image in 16 channels every ten minutes since July 2019, allowing diurnal land surface monitoring over a large proportion of Asia and all of Oceania. Retrieving accurate surface reflectance (SR) over land from GK-2A/AMI is a challenging but high priority objective. One of the challenges is the absence of a spectral band in the 2.2 m SWIR range from AMI, which is required by many atmospheric correction algorithms to retrieve atmospheric aerosol properties. To remedy this issue, we adopt a strategy that combines concurrent GK-2A/AMI and Himawari 8/AHI observations in order to derive AMI SR. We have adapted the NASA Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to process the data stream from Himawari 8/AHI. The advantages of the MAIAC algorithm is its capability to exploit the high temporal frequency and varying illumination geometry of the geostationary data for advanced cloud/snow detection, aerosol retrieval, and characterization of surface bidirectional reflectance properties. Leveraging the similarities of spectral bands and the sun-target-sensor geometry between AMI and AHI, we are able to create denser time series of observations and enhanced BRDF samples over most of the spatial coverage of AMI (and AHI). The combined stereo-type observations not only help derive SR for AMI but also enhance retrievals of the corresponding AHI surface products. We evaluate the resulting AMI SR using ground (AERONET) observations and corresponding MODIS products. Further, we discuss potential challenges in utilizing the geostationary satellite data for land surface monitoring.

geostationary satellite↗

Imaging by time-tagging photons with the multi-anode microchannel array detector system

The capability and initial use of the Multi-Anode Microchannel Array (MAMA) detector in the time-tag mode is reported. The detector hardware currently in use consists of a visible-light detector tube with a semitransparent photocathode proximity-focused to a high-gain curved-channel microchannel plate MCP. The photoevents are detected by a (256 x 1024)-pixel coincidence-anode array with pixel dimensions of 25 x 25 microns connected to charge-sensitive amplifiers and event-detection circuitry. In the time-lag mode, the detector delivers the pixel address and the time of arrival for each detected photon to an accuracy of 10 microns. The maximum count rate is limited by the speed of data-acquisition hardware. The MAMA detector in the time-lag mode is currently being evaluated in programs of astrometry and speckle imaging.

Timothy, J. G.↗

Characteristics Of Ferroelectric Logic Gates Using a Spice-Based Model

A SPICE-based model of an n-channel ferroelectric field effect transistor has been developed based on both theoretical and empirical data. This model was used to generate the I-V characteristic of several logic gates. The use of ferroelectric field effect transistors in memory circuits is being developed by several organizations. The use of FFETs in other circuits, both analog and digital needs to be better understood. The ability of FFETs to have different characteristics depending on the initial polarization can be used to create logic gates. These gates can have properties not available to standard CMOS logic gates, such as memory, reconfigurability and memory. This paper investigates basic properties of FFET logic gates. It models FFET inverter, NAND gate and multi-input NAND gate. The I-V characteristics of the gates are presented as well as transfer characteristics and timing. The model used is a SPICE-based model developed from empirical data from actual Ferroelectric transistors. It simulates all major characteristics of the ferroelectric transistor, including polarization, hysteresis and decay. Contrasts are made of the differences between FFET logic gates and CMOS logic gates. FFET parameters are varied to show the effect on the overall gate. A recodigurable gate is investigated which is not possible with CMOS circuits. The paper concludes that FFETs can be used in logic gates and have several advantages over standard CMOS gates.

MacLeod, Todd C.↗

Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The Fast Plasma Investigation (FPI) on NASAs Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30 ms for electrons; 150 ms for ions) and spatially differentiated measurements of the full 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity, the reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions of magnetically reconnecting plasmas. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated using the plateau curve technique. In this, a fixed detection threshold is set. The detection system count rate is then measured as a function of MCP voltage to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection system discrimination threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully describe the behavior of the detection system and individually characterize each of its fundamental parameters. To improve this situation, we have developed a detailed phenomenological description of the detection system, its behavior and its signal, crosstalk and noise sources. Based on this, we have devised a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. More precise calibration is highly desirable as the instruments will produce higher quality raw data that will require less post-acquisition data correction using results from in-flight pitch angle distribution measurements and ground calibration measurements. The detection system description and the fundamental concepts of this new calibration method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters and how to choose the optimum detection system operating point. This new method has been successfully applied to achieve a highly accurate calibration of the DESs and DISs of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown that, with further detailed modeling, this method can be extended for use in flight to achieve and maintain a highly accurate detection system calibration across a large number of instruments during the mission.

detection system↗

Results of a Long-Term Demonstration of an Optical Multi-Gas Monitor on ISS

Previously at SAMAP we reported on the development of tunable diode laser spectroscopy (TDLS) based instruments for measuring small gas molecules in real time. TDLS technology has matured rapidly over the last 5 years as a result of advances in low power diode lasers as well as better detection schemes. In collaboration with two small businesses Vista Photonics, Inc. and Nanoracks LLC, NASA developed a 4 gas TDLS based monitor for an experimental demonstration of the technology on the International Space Station (ISS). Vista invented and constructed the core TDLS sensor. Nanoracks designed and built the enclosure, and certified the integrated monitor as a payload. The device, which measures oxygen, carbon dioxide, ammonia and water vapor, is called the Multi-Gas Monitor (MGM). MGM measures the 4 gases every few seconds and records a 30 second moving average of the concentrations. The relatively small unit draws only 2.5W. MGM was calibrated at NASA-Johnson Space Center in July 2013 and launched to ISS on a Soyuz vehicle in November 2013. Installation and activation of MGM occurred in February 2014, and the unit has been operating nearly continuously ever since in the Japanese Experiment Module. Data is downlinked from ISS about once per week. Oxygen and carbon dioxide data is compared with that from the central Major Constituents Analyzer. Water vapor data is compared with dew point measurements made by sensors in the Columbus module. The ammonia channel was tested by the crew using a commercial ammonia inhalant. MGM is remarkably stable to date. Results of 18 months of operation are presented and future applications including combustion product monitoring are discussed.

Mudgett, Paul↗

Use of Collocated KWAJEX Satellite, Aircraft, and Ground Measurements for Understanding Ambiguities in TRMM Radiometer Rain Profile Algorithm

Coordinated ground, aircraft, and satellite observations are analyzed from the 1999 TRMM Kwajalein Atoll field experiment (KWAJEX) to better understand the relationships between cloud microphysical processes and microwave radiation intensities in the context of physical evaluation of the Level 2 TRMM radiometer rain profile algorithm and uncertainties with its assumed microphysics-radiation relationships. This talk focuses on the results of a multi-dataset analysis based on measurements from KWAJEX surface, air, and satellite platforms to test the hypothesis that uncertainties in the passive microwave radiometer algorithm (TMI 2a12 in the nomenclature of TRMM) are systematically coupled and correlated with the magnitudes of deviation of the assumed 3-dimensional microphysical properties from observed microphysical properties. Re-stated, this study focuses on identifying the weaknesses in the operational TRMM 2a12 radiometer algorithm based on observed microphysics and radiation data in terms of over-simplifications used in its theoretical microphysical underpinnings. The analysis makes use of a common transform coordinate system derived from the measuring capabilities of the aircraft radiometer used to survey the experimental study area, i.e., the 4-channel AMPR radiometer flown on the NASA DC-8 aircraft. Normalized emission and scattering indices derived from radiometer brightness temperatures at the four measuring frequencies enable a 2-dimensional coordinate system that facilities compositing of Kwajalein S-band ground radar reflectivities, ARMAR Ku-band aircraft radar reflectivities, TMI spacecraft radiometer brightness temperatures, PR Ku-band spacecraft radar reflectivities, bulk microphysical parameters derived from the aircraft-mounted cloud microphysics laser probes (including liquid/ice water contents, effective liquid/ice hydrometeor radii, and effective liquid/ice hydrometeor variances), and rainrates derived from any of the individual ground, aircraft, or satellite algorithms applied to the radar or radiometer measurements, or their combination. The results support the study's underlying hypothesis, particularly in context of ice phase processes, in that the cloud regions where the 2a12 algorithm's microphysical database most misrepresents the microphysical conditions as determined by the laser probes, are where retrieved surface rainrates are most erroneous relative to other reference rainrates as determined by ground and aircraft radar. In reaching these conclusions, TMI and PR brightness temperatures and reflectivities have been synthesized from the aircraft AMPR and ARMAR measurements with the analysis conducted in a composite framework to eliminate measurement noise associated with the case study approach and single element volumes obfuscated by heterogeneous beam filling effects. In diagnosing the performance of the 2a12 algorithm, weaknesses have been found in the cloud-radiation database used to provide microphysical guidance to the algorithm for upper cloud ice microphysics. It is also necessary to adjust a fractional convective rainfall factor within the algorithm somewhat arbitrarily to achieve satisfactory algorithm accuracy.

Smith, Eric A.↗

Studies of the Interactions Between Vestibular Function and Tactual Orientation Display Systems

When humans experience conditions in which internal vestibular cues to movement or spatial location are challenged or contradicted by external visual information, the result can be spatial disorientation, often leading to motion sickness. Spatial disorientation can occur in any situation in which the individual is passively moved in the environment, but is most common in automotive, aircraft, or undersea travel. Significantly, the incidence of motion sickness in space travel is great: The majority of individuals in Shuttle operations suffer from the syndrome. Even after the space-sickness-producing influences of spatial disorientation dissipate, usually within several days, there are other situations in which, because of the absence of reliable or familiar vestibular cues, individuals in space still experience disorientation, resulting in a reliance on the already preoccupied sense of vision. One possible technique to minimize the deleterious effects of spatial disorientation might be to present attitude information (including orientation, direction, and motion) through another less-used sensory modality - the sense of touch. Data from experiences with deaf and blind persons indicate that this channel can provide useful communication and mobility information on a real-time basis. More recently, technologies have developed to present effective attitude information to pilots in situations in which dangerously ambiguous and conflicting visual and vestibular sensations occur. This summers project at NASA-Johnson Space Center will evaluate the influence of motion-based spatial disorientation on the perception of tactual stimuli representing veridical position and orientation information, presented by new dynamic vibrotactile array display technologies. In addition, the possibility will be explored that tactile presentations of motion and direction from this alternative modality might be useful in mitigating or alleviating spatial disorientation produced by multi-axis rotatory systems, monitored by physiological recording techniques developed at JSC.

Cholewiak, Roger W.↗

MM-Wave Radiometric Measurements of Low Amounts of Precipitable Water Vapor

An experiment was conducted during March, 1999 to study ways in which to improve techniques for measuring low amounts of total-column precipitable water vapor (PWV). The experiment was conducted at the DOE's ARM program's North Slope of Alaska/Adjacent Arctic Ocean Cloud and Radiation Testbed site (DoE ARM NSA/AAO CaRT) located just outside Barrow, Alaska. NASA and NOAA deployed a suite of radiometers covering 25 channels in the frequency range of 20 GHz up to 340 GHz including 8 channels around the 183 GHz water vapor absorption line. In addition to the usual CaRT site instrumentation the NOAA Depolarization and Backscatter Unattended Lidar (DABUL), the SUNY Rotating Shadowband Spectroradiometer (RSS) and other surface based meteorological instrumentation were deployed during the intensive observation period. Vaisala RS80 radiosondes were launched daily as well as nearby National Weather Service VIZ sondes. Atmospheric conditions ranged from clear calm skies to blowing snow and heavy multi-layer cloud coverage. Measurements made by the radiosondes indicate the PWV varied from approx. 1 to approx. 5 mm during the experiment. The near-surface temperature varied between about -40 C to - 15 C. In this presentation, an overview of the experiment with examples of data collected will be presented. Application of the data for assessing the potential and limitations of millimeter-wave radiometry for retrieving very low amounts of PWV will be discussed.

Racette, P.↗

Global Freeze/Thaw Product from L-Band Radiometer Data

The NASA Soil Moisture Active Passive (SMAP) mission has been successfully operated for almost three years. The SMAP freeze/thaw algorithm is based on a seasonal threshold approach. It’s important to have a stable and self-consistent freeze and thaw reference that can be applied for multi-year dataset. The three-year long radiometer datasets allow us to reassess the criteria of reference setup and evaluate its stability. In this paper, we first refined the freeze reference requirements and compare three different methods of setting up the thaw reference to minimize the false flags. The original freeze/thaw products is in the polar grid and only cover the region north of 45° N latitude. The limitation is due to lack of enough freezing days in the lower latitude, where the freezing reference cannot be generated. To extend the freeze/thaw product to global region, we combine the single channel algorithm in the lower latitude and southern atmosphere. The global results have been validated through WMO air temperature.

Colliander, Andreas↗

Measuring the neutrino-oxygen neutral current quasielastic cross section using the accelerator neutrino neutron interaction experiment

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton gadolinium-doped water Cherenkov detector located on-axis to Fermilab’s Booster Neutrino Beam (BNB). ANNIE is uniquely positioned to perform high-statistics measurements of neutrino-nucleus interactions in water, benefiting from a large neutrino flux due to a short (100-meter) baseline. A central focus of ANNIE’s physics program is the measurement of both charged current (CC) and neutral current (NC) cross sections on water, including neutral current quasielastic (NCQE) and CC-inclusive channels. The NCQE measurement is particularly critical for constraining uncertainties in rare-event searches such as the Diffuse Supernova Neutrino Background (DSNB), where atmospheric $\nu$NCQE interactions constitute a significant and poorly constrained background. This dissertation presents a measurement of the flux-averaged neutrino-oxygen neutral current quasielastic ($\nu$NCQE) cross section using $2.573 \times 10^{20}$~POT of BNB exposure from the 2022 and 2023 beam years. The $\nu$NCQE interaction is identified through the primary $\gamma$-rays produced by nuclear de-excitation of the residual $^{15}$N$^*$ or $^{15}$O$^*$ nucleus following nucleon knockout from $^{16}$O. A dedicated Monte Carlo (MC) re-tuning campaign was conducted using an americium-beryllium (AmBe) calibration source, Michel electrons from stopped muons, and throughgoing dirt muons originating upstream of the detector. This multi-sample approach provided a wide-ranging $\mathcal{O}(\text{MeV})$--$\mathcal{O}(\text{GeV})$ dataset for tuning the simulated detector response, which was subsequently validated against AmBe neutron and Michel electron data for use in the $\nu$NCQE analysis. A dedicated laser calibration campaign was carried out to reduce timing uncertainties across the PMT system, enabling reconstruction of the BNB bunch substructure with sufficient resolution to serve as a background rejection tool. By selecting events in-time with individual neutrino bunches, beam-correlated $\nu$NCQE events are separated from diffuse and accelerator-induced backgrounds, notably skyshine neutrons and externally-originating events, that would otherwise dominate traditional charge-based selections within a small-scale, surface-level, short-baseline detector. A data-driven estimation of the skyshine neutron and external background rates was performed and incorporated into the systematic uncertainty budget. The flux-averaged $\nu$NCQE cross section on oxygen is measured to be $1.57 \pm 0.06\,(\text{stat.})$ $^{+0.91}_{-0.67}\,(\text{syst.})$ $\times 10^{-38}\ \text{cm}^{2}$. A full systematic budget is constructed by propagating uncertainties in the secondary hadronic interaction modeling, background cross section normalizations, detector response, neutrino flux, and the primary $\gamma$-ray emission probabilities from oxygen nuclear de-excitation. An idealized de-excitation model, constructed from existing measurements in the literature is developed to benchmark the predictions of the \textsc{GENIE} event generator. A comparison reveals that \textsc{GENIE} systematically overpredicts the primary $\gamma$-ray emission probability from oxygen de-excitation by a factor of $1.49\times$ for $E_\gamma > 6$~MeV and $3.07\times$ in the $3$--$6$~MeV band. This comparison motivates the dominant systematic uncertainty in this analysis, where a conservative uncertainty of $^{+39.9\%}_{-0\%}$ on the primary $\gamma$-ray signal prediction is assigned. The ANNIE result is consistent with and complementary to existing flux-averaged $\nu$NCQE cross section measurements from T2K and Super-Kamiokande, providing an independent measurement with a different detector, neutrino beam, and analysis methodology. Looking ahead, an upgrade to the ANNIE DAQ infrastructure enabling continuous extended readout will allow a complementary $\nu$NCQE neutron multiplicity measurement, directly relevant to constraining the NCQE background in DSNB searches, competitive with the recent T2K measurement at SK-Gd. The planned Super-SANDI upgrade, deploying a large Water-based Liquid Scintillator (WbLS) volume, will further extend ANNIE's reach to hadronic final states and exclusive NC channels, and enable joint measurements with liquid argon detectors sharing the BNB beamline ahead of DUNE and Hyper-Kamiokande.

Doran, Steven [Iowa State U.]↗

CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Flux Improvement based on Machine Learning for the CERES FluxByCldTyp Data Product

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗

Improvement of Radiative Fluxes for the CERES FluxByCldTyp Data Product Based on Machine Learning Technique

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

Moguo Sun↗