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At least 109 records · Page 6

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Koster, Randal↗

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗

SWIPE: Spectral Water Inversion Processor and Emulator

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will be discussing the progress made developing SWIPE: Spectral Water Inversion Processor and Emulator. SWIPE is a platform for advanced modeling of coastal and inland aquatic habitats. The goal is create a comprehensive and cohesive system to leverage recent advancements in computation and machine learning to develop a synthetic training ground for sensitivity studies and algorithm development. The four principal facets of SWIPE include: 1. Advanced two-layer coated sphere bio-optical modeling and GPU radiative transfer modeling, 2. Big Data involving massive synthetic spectral libraries of optical properties of various global aquatic particles, surface reflectance, and top-of-atmosphere reflectance, all at hyperspectral resolution leveraging high-end computing systems at NASA Ames Research Center, 3. Deep Learning for algorithm development for water quality inversion of concentrations of common biogeophysical variables as well as optics, full uncertainty characterization by water type, and forward emulation, and lastly, 4. Image Processing for application of developed retrieval algorithms for both hyperspectral and multispectral sensors with experimental corrections for global adjacency, noise, sunglint, and benthic reflectance. This presentation will demonstrate the Equivalent Algal Populations (EAP) two-layer coated sphere scattering model which has been used develop spectral libraries of hyperspectral inherent optical properties of roughly 80 species of phytoplankton, covering 15 different classes and nine taxonomic functional types. The EAP model was also used to derive spectral properties of 10 different non-algal particle functional types. Examples of how the SMART-G (Speed-up Monte-carlo Advanced Radiative Transfer using GPU) radiative transfer code is used to model optically complex aquatic signals will be presented and discussed in the context of creating a massive synthetic database which can leverage the full power of next generation machine learning techniques and high end computing for water quality inversion. We will discuss our active investigation in things like appropriate model architectures, dimensionality reduction techniques such as PCA and autoencoders, uncertainty quantification and abstaining, and which variables actually benefit most from hyperspectral information versus multispectral resolution. We are also curious about questions relating to cost/benefit analysis in terms of computation resources, neural network complexity, and data volumes. Answers to these questions will hopefully elaborate on cost efficiency for potential future sensor design considerations.

SWIPE↗

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗

Research in Theoretical Particle Physics: Neutrino Masses and The Origin of CP-Violation

The main goal of this project was to investigate the theories of neutrino masses at the low scale and the origin of CP-violation in physics beyond the Standard Model. The origin of neutrino masses is one of the most pressing issues in particle physics. In this proposal, we investigated the theories for neutrino masses based on local total lepton number. In these theories anomaly cancellation predicts the existence of extra fermions with lepton number, and one of them is a good dark matter (DM) candidate. The cosmological constraints on the DM relic density implies that the lepton number symmetry breaking scale must be below the multi-TeV scale. Therefore, one can hope to test the origin of neutrino masses in current or future experiments. We investigated in great detail the anomaly cancellation in these gauge theories, study the different mechanisms for neutrino masses, study the predictions for direct and indirect dark matter experiments. Since these theories predict new sources of CP violation, we investigated the predictions for the electric dipole moments (EDM). The Higgs decays and the different signatures at the Large Hadron Collider were investigated in great detail. Finally, we studied the possible baryogenesis mechanisms in these theories in agreement with the EDM, DM and collider constraints. The origin of CP violation in the Standard Model is unknown. In this proposal, we investigated the simplest mechanisms for spontaneous CP-violation to explain the CP-violation in the CKM matrix and the value of the QCD vacuum angle. We discussed the Nelson-Barr mechanism in gauge theories predicting vector-like quarks from anomaly cancellation such as theories for local baryon number. We discussed the Bento-Branco-Parada mechanism in gauge theories to explain the CP-Violation in the CKM matrix. We will investigate models with two Higgs doublets in the context of the minimal theory for quark-lepton unification. We will show the non-decoupling effects in the Higgs sector, the main constraints coming from flavour violating processes when the Yukawa couplings are related by the gauge symmetry in theories for quark-lepton unification. We will investigate the predictions for electric dipole moments in these theories. The possibility to have successful baryogenesis was investigated. Finally, we investigated the relation between CP-violation in the quark and leptonic sectors. The future results from these studies could help us to understand two main issues in physics beyond the Standard Model: The Origin of Neutrino Masses and CP-violation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Anomaly Detection and Mitigation for Wide-Area Damping Control using Machine Learning

In an interconnected multi-area power system, wide-area measurement based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power flows below to their transmission capacity. The effect of wide-area damping control (WADC) significantly depends on both power and cyber systems. At the cyber system layer, an adversary can inflict the WADC process by compromising either measurement signals, control signals or both. Stealthy and coordinated cyber-attacks may bypass the conventional cybersecurity measures to disrupt the seamless operation of WADC. This paper proposes an anomaly detection (AD) algorithm using supervised Machine Learning and a model-based logic for mitigation. The proposed AD algorithm considers measurement signals (input of WADC) and control signals (output of WADC) as input to evaluate the type of activity such as normal, perturbation (small or large signal faults), attack and perturbation-and-attack. Upon anomaly detection, the mitigation module tunes the WADC signal and sets the control status mode as either wide-area mode or local mode. The proposed anomaly detection and mitigation (ADM) module works inline with the WADC at the control center for attack detection on both measurement and control signals and eliminates the need for ADMs at the geographically distributed actuators. Here, we consider coordinated and primitive data-integrity attack vectors such as pulse, ramp, relay-trip and replay attacks. The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for 2-area 4-machine power system. The ADM module shows effective performance with 96:5% accuracy to detect anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. II - Dynamical analysis

The heating associated with equatorial, subtropical, and midlatitude ocean temperature anamolies in the Held-Suarez climate model is analyzed. The local and downstream response to the anomalies is analyzed, first by examining the seasonal variation in heating associated with each ocean temperature anomaly, and then by combining knowledge of the heating with linear dynamical theory in order to develop a more comprehensive explanation of the seasonal variation in local and downstream atmospheric response to each anomaly. The extent to which the linear theory of propagating waves can assist the interpretation of the remote cross-latitudinal response of the model to the ocean temperature anomalies is considered. Alternative hypotheses that attempt to avoid the contradictions inherent in a strict application of linear theory are investigated, and the impact of sampling errors on the assessment of statistical significance is also examined.

Phillips, T. J.↗

A remanent and induced magnetization model of Magsat vector anomalies over the west African craton

Scalar and vector Magsat anomalies over the west African craton are analyzed by forward and inverse models. A forward model of the Man shield is based on Liberia. Induced magnetization contrasts due to sporadic iron-formations and to regional metamorphic rocks, and a contrast in remanent magnetization within the lower crust are included. This combination reproduces the location, magnitude and adopted local zero level of anomalies in the initial Magsat maps. An inverse model of the Reguibat shield estimates the magnetization contrast of its lithosphere, and when magnetism is restricted to shallower than 75 km both shields can be represented by a susceptibility contrast of +0.02. A residual anomaly between the shields involves a relative deficiency of induced magnetization along with other causes.

Toft, P. B.↗

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Clouds↗

Decadal Air-Sea Interaction in the North Atlantic Based on Observations and Modeling Results

The decadal, 12-14 year, cycle observed in the North Atlantic SST and tide gauge data was examined using the NCEP/NCAR reanalyses, COADS data and an ocean model simulation. Besides this decadal mode, a shorter, subdecadal period of about 8 years exists in tide gauge data north of 40N, in the subpolar SST and in the winter North Atlantic Oscillation (NAO) index and in subpolar winter heat flux values. The decadal cycle is a well separated mode in a singular spectrum analysis (SSA) for a time series of SST EOF mode 1 with a center over the Gulf Stream extension. Tide gauge and SST data are consistent in that both show a significant subdecadal periodicity exclusively in the subpolar gyre, but in subtropics the 12-14 year period is the prominent, but nonstationary, decadal signal. The main finding of this study is that this 12-14 year cycle can be constructed based on the leading mode of the surface heat flux. This connection to the surface heat flux implicates the participation of the thermohaline circulation in the decadal cycle. During the cycle starting from the positive index phase of NAO, SST and oceanic heat content anomalies are created in subtropics due to local heat flux and intensification of the thermohaline circulation. The anomalies advect to the subpolar gyre where they are amplified by local heat flux and are part of the negative feedback of thermohaline circulation on itself. Consequently the oceanic thermohaline circulation slows down and the opposite cycle starts. The oscillatory nature would not be possible without the active atmospheric participation in the cycle, because it provides the unstable interaction through heat flux, without it, the oceanic mode would be damped. This analysis suggests that the two principal modes of heat flux variability, corresponding to patterns similar to North Atlantic Oscillation (NAO) and Western Atlantic (WA), are part of the same decadal cycle and an indirect measure of the north-south movement of the storm tracks.

Hakkinen, Sirpa↗

DPOD2020: A DORIS Extension of the ITRF2020 for Precise Orbit Determination

As one of the tracking systems used to determine orbits of the altimeter mission satellites (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/Altika, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), DORIS (Doppler Orbitography Radiopositionning Integrated by Satellite) allows to determine positions and velocities of tracking stations that define a stable reference for the estimation of the precise orbits and thus are fundamental for the quality of the altimeter data and derived mean sea level products. Due to the time evolution of the DORIS ground network, some stations included in the 2020 realization of the International Terrestrial Reference Frame (ITRF2020) have been decommissioned and since 2021.0 a few new stations were added to the tracking network. Therefore, to satisfy operational requirements for POD (Precise Orbit Determination) and routine delivery of geodetic products, the International DORIS Service (IDS) regularly updates the DPOD (DORIS terrestrial reference frame for Precise Orbit Determination). The DPOD solutions include mean positions and velocities of all the DORIS stations since 1993.0 derived from the stacking of the latest IDS weekly combined series aligned to the current ITRF. In this paper, we first present the stacking process of the DPOD2020 version 1.0. Then, we address the validation procedure of the DPO2020 including comparison with ITRF2020 and POD tests. For eighty percent of all the time segments of all the DORIS stations, the station position differences between DPOD2020 version 1.0 and ITRF2020 are smaller than ten millimeters. The major position differences between these two solutions are associated with the DORIS sites either localized in the South Atlantic Anomaly region or with time spans smaller than one year. Compared to DPOD2014, the DPOD2020 shows reduction of the main statistics of the DORIS-to-DORIS tie residuals (differences between the estimated and measured ties). The POD tests showed similar results for DPOD2020 and DPOD2014 for most of the altimetric satellites (TOPEX/Poseidon, Jason-1, CryoSat-2, Jason-3). In addition, we observed better POD results with DPOD2020 for the latest altimetric satellite Sentinel-3A as well as a slight degradation for Jason-2. That degradation was fully explained by slightly worst results for the stations localized in the South Atlantic Anomaly region.

DORIS↗

Neutral temperature anomaly in the equatorial thermosphere - A source of vertical winds

Data obtained from the Wind and Temperature Spectrometer on the Dynamics Explorer during high solar activity show new evidence for the presence of vertical winds of a significant magnitude in the equatorial thermosphere. They reveal a latitudinal structure that can be related to the recently discovered equatorial temperature and wind anomaly (ETWA). In the local evening hours, the vertical winds usually are downward around the dip equator and collocated with the temperature minimum of ETWA. In general, they are upward at about 24 deg dip latitude away from the dip equator and are collocated with the ETWA temperature crests. The magnitude of the vertical winds is in the 10-40 m/s range. It is proposed that the temperature and pressure ridges, formed by the excess ion drag on the zonal winds around the two crests and ordered by the relatively lower ion drag at the trough of the well known equatorial ionization anomaly, drive a new wind system in the meridional plane and that the measured vertical winds form part of this wind system.

Raghavarao, R.↗

Removing the Effects of Tropical Dynamics from North Pacific Climate Variability

Teleconnections from the Tropics energize variations of the North Pacific climate, but detailed diagnosis of this relationship has proven difficult. Simple univariate methods, such as regression on El Niño-Southern Oscillation (ENSO) indices, may be inadequate since the key dynamical processes involved -- including ENSO diversity in the Tropics, re-emergence of mixed layer thermal anomalies, and oceanic Rossby wave propagation in the North Pacific -- have a variety of overlapping spatial and temporal scales. Here we use a multivariate Linear Inverse Model to quantify tropical and extra-tropical multi-scale dynamical contributions to North Pacific variability, in both observations and CMIP6 models. In observations, we find that the Tropics are responsible for almost half of the seasonal variance, and almost three quarters of the decadal variance, along the North American coast and within the subtropical front region northwest of Hawaii. SST anomalies that are generated by local dynamics within the Northeast Pacific have much shorter time scales, consistent with transient weather forcing by Aleutian low anomalies. Variability within the Kuroshio-Oyashio Extension (KOE) region is considerably less impacted by the Tropics, on all time scales. Consequently, without tropical forcing the dominant pattern of North Pacific variability would be a KOE pattern, rather than the Pacific Decadal Oscillation (PDO). In contrast to observations, most CMIP6 historical simulations produce North Pacific variability that maximizes in the KOE region, with amplitude significantly higher than observed. Correspondingly, the simulated North Pacific in all CMIP6 models is shown to be relatively insensitive to the Tropics, with a dominant spatial pattern generally resembling the KOE pattern, not the PDO.

54 ENVIRONMENTAL SCIENCES↗

Experimental determination of Mercury's mass and oblateness

The ratio of the mass of the sun to that of Mercury deduced from the first and third flybys of Mercury by Mariner 10 is 6,023,600 plus or minus 600 and 6,023,700 plus or minus 300, respectively. Additional analysis should improve these uncertainties by a factor of 2 to 5. Assuming an equatorial radius of 2439 km, the mean density of the planet is 5.44 g/cu cm. The gravitational oblateness deduced from the first encounter is discussed. Data received from the third encounter are better suited for this determination and yield J2 of 0.00008 plus or minus 0.00006. In addition, the third-encounter data are sensitive to local gravity effects or anomalies.

Esposito, P. B.↗

Improvement of the Earth's gravity field from terrestrial and satellite data

The terrestrial gravity data base was updated. Studies related to the Geopotential Research Mission (GRM) have primarily considered the local recovery of gravity anomalies on the surface of the Earth based on satellite to satellite tracking or gradiometer data. A simulation study was used to estimate the accuracy of 1 degree-mean anomalies which could be recovered from the GRM data. Numerous procedures were developed for the intent of performing computations at the laser stations in the SL6 system to improve geoid undulation calculations.

Source record↗

Kupier prize lecture: Sources of solar-system carbon

We have tried to deconvolve Solar-System carbon into its sources, on the basis of C-12/C-13 ratios (equivalent to R). Interstellar SiC in meteorites, representing greater than 4.6-Ga-old stardust from carbon stars, is isotopically heavier (bar R = 38 +/- 2) than Solar-System carbon (89), implying that the latter contains an additional, light component. A likely source are massive stars, mainly Type II supernovae and Wolf-Rayet stars, which, being O-rich, eject their C largely as CO rather than carbonaceous dust. The fraction of such light C in the Solar System depends on R(sub light) in the source. For R(sub light) = 180-1025 (as in 'Group 4' meteoritic graphite spherules, which apparently came from massive stars greater than 4.6 Ga ago), the fraction of light C is 0.79-0.61. Similar results are obtained for present-day data on red giants and interstellar gas. Although both have become enriched in C-13 due to galactic evolution (to bar-R = 20 and 57), the fraction of the light component in interstellar gas again is near 0.7. (Here bar R represents the mean of a mixture calculated via atom fractions; it is not identical to the arithmetic mean R). Interstellar graphite, unlike SiC, shows a large peak at R approximately equal 90, near the solar value. Although some of the grains may be of local origin, others show anomalies in other elements and hence are exotic. Microdiamonds, with R = 93, also are exotic on the basis of their Xe and N. Apparently R approximately 90 was a fairly common composition 4.6 Ga ago, of stars as well as the ISM.

Anders, Edward↗

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.

Lucey, Paul G.↗