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NASA NTRS1992

The Global Ocean Observing System

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Kester, Dana↗

NASA NTRS1995

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

Ripple, William J.↗

NASA NTRS1996

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗

DOE OSTI2017

System and method for preventing stator permanent magnet demagnetization during vacuum pressure impregnation

A permanent magnet electrical machine includes a stator having conductive windings wound thereon and one or more permanent magnets embedded in the stator. A magnetic keeper element is positioned on the stator so as to form a magnetic flux path with the permanent magnets, with the magnetic keeper element closing the magnetic flux path of the permanent magnets by providing a low reluctance flux path to magnetic flux generated by the permanent magnets. A vacuum pressure impregnation (VPI) process is performed on the stator to increase a thermal conductivity of the windings, with the VPI process including a curing step that is performed at a selected temperature. The magnetic keeper element sets an operating point of the permanent magnets to an internal flux density level above a demagnetization threshold associated with the selected temperature at which the curing step is performed.

42 ENGINEERING↗

NASA NTRS2018

Impacts of Snow and Cloud Covers on Satellite-Derived PM 2.5 Levels

Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM 2.5 ) levels, whereas snow/cloud covers often lead to a large proportion of non-random missing AOD. As a result, the fully covered and unbiased PM 2.5 estimates will be hard to generate. Among the current approaches to deal with the data gap issue, few have considered the cloud-AOD relationship and none of them have considered the snow-AOD relationship. This study examined the impacts of snow and cloud covers on AOD and PM 2.5 and made full-coverage PM 2.5 predictions with the consideration of these impacts. To estimate the missing AOD, daily gap-filling models with snow/cloud fractions and meteorological covariates were developed using the random forest algorithm. By using these models in New York State, a daily AOD data set with a 1-km resolution was generated with a complete coverage. The“out-of-bag” R 2 of the gap-filling models averaged 0.93 with an interquartile range from 0.90 to 0.95. Subsequently, a random forest-based PM 2.5 prediction model with the gap-filled AOD and covariates was built to predict fully covered PM 2.5 estimates. A ten-fold cross-validation for the prediction model showed a good performance with an R 2 of 0.82. In the gap-filling models, the snow fraction was of higher significance in the snow season compared with the rest of the year. The prediction models fitted with/without the snow fraction also suggested the discernible changes in PM 2.5 patterns, further confirming the significance of this parameter. Compared with the methods without considering snow and cloud covers, our PM 2.5 prediction surfaces showed more spatial details and reflected small-scale terrain-driven PM 2.5 patterns. The proposed methods can be generalized to the areas with extensive snow/cloud covers and large proportions of missing satellite AOD for predicting PM 2.5 levels with high resolutions and complete coverage.

AOD↗

DOE OSTI2016

Anharmonic modeling of the conformation-specific IR spectra of ethyl, n-propyl, and n-butylbenzene

In this paper, conformation-specific UV-IR double resonance spectra are presented for ethyl, n-propyl, and n-butylbenzene. With the aid of a local mode Hamiltonian that includes the effects of stretch-scissor Fermi resonance, the spectra can be accurately modeled for specific conformers. These molecules allow for further development of a first principles method for calculating alkyl stretch spectra. Across all chain lengths, certain dihedral patterns impart particular spectral motifs at the quadratic level. However, the anharmonic contributions are consistent from molecule to molecule and conformer to conformer. This transferability of anharmonicities allows for the Hamiltonian to be constructed from only a harmonic frequency calculation, reducing the cost of the model. Finally, the phenyl ring alters the frequencies of the CH 2 stretches by about 15 cm -1 compared to their n-alkane counterparts in trans configurations. Conformational changes in the chain can lead to shifts in frequency of up to 30 cm -1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Taxonomy of USA east coast fishing communities in terms of social vulnerability and resilience

Increased concern with the impacts that changing coastal environments can have on coastal fishing communities led to a recent effort by NOAA Fisheries social scientists to develop a set of indicators of social vulnerability and resilience for the U.S. Southeast and Northeast coastal communities. A goal of the NOAA Fisheries social vulnerability and resilience indicator program is to support time and cost effective use of readily available data in furtherance of both social impact assessments of proposed changes to fishery management regulations and climate change adaptation planning. The use of the indicators to predict the response to change in coastal communities would be enhanced if community level analyses could be grouped effectively. This study examines the usefulness of combining 1130 communities into 35 relevant subgroups by comparing results of a numerical taxonomy with data collected by interview methods, a process herein referred to as “ground-truthing.” The validation of the taxonomic method by the method of ground-truthing indicates that the clusters are adequate to be used to select communities for in-depth research. - Highlights: • We develop a taxonomy of fishing communities based on vulnerability indicators. • We validate the community clusters through the use of surveys (“ground-truthing”). • Clusters differ along important aspects of fishing community vulnerability. • Clustering communities allows for accurate and timely social impact assessments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

X-ray-line coincidence photopumping in a potassium-chlorine mixed plasma

Exploiting the multiple long pulse capability and suite of x-ray diagnostics of the Orion laser, we have set out to explore line coincidence photopuming—the enhancement in population of an atomic level brought on by resonant absorption of x rays from a different emitting ion. Unlike previous work, the two ions are in the same plasma and so the experiment is an x-ray analog of the well-known Bowen resonance fluorescence mechanism that operates in astrophysical situations in the optical region. Herein, our measurements have shown enhanced fluorescence in a chlorine plasma, attributable to line coincident photopumping from co-mixed potassium ions. To detect this relatively low signal-to-noise phenomenon, the data from multiple shots are combined, and the statistical method of bootstrapping is used to assign a confidence value to the measured enhancement, resulting in an estimate of the enhancement of 39 ± 18 16 % compared to the null case, where no pumping occurs. The experimental results have been compared to coupled radiation-transport and radiation hydrodynamics simulations using the CRETIN code together with the NYM radiation hydrodynamics model and agreement has been found, with the simulations also predicting modest enhancement.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Electronic and Spectral Properties of RRhSn (R = Gd, Tb) Intermetallic Compounds

The investigations of electronic structure and optical properties of GdRhSn and TbRhSn were carried out. The calculations of band spectrum, taking into account the spin polarization, were performed in a local electron density approximation with a correction for strong correlation effects in 4f shell of rare earth metal (LSDA + U method). The optical studies were done by ellipsometry in a wide range of wavelengths, and the set of spectral and electronic characteristics was determined. It was shown that optical absorption in a region of interband transitions has a satisfactory explanation within a scope of calculations of density of electronic states carried out.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Quantum Mechanical Simulations of Complex Nanostructures for Photovoltaic Applications

A quantitative understanding of the electronic excitations in nanostructures, especially complex nanostructures, is crucial for making new-generation photovoltaic (PV) cells based on nanotechnology, which have high efficiency and low cost. Yet current quantum mechanical simulation methods are either computationally too expensive or not accurate and reliable enough, hindering the rational design of the nanoscale PV cells. The PI seeks to develop new methodologies to overcome the challenges in this very difficult and long-lasting problem, pushing the field forward so that electronic excitations can be accurately predicted for systems involving thousands of atoms. The primary objective of this project is to develop new approaches for electronic excitation calculations that are more accurate than traditional density functional theory (DFT) and are applicable to systems larger than what current beyond-DFT methods can treat. In this proposal, the PI will first address the excited-state problem within the DFT framework to obtain quasiparticle energies from both Kohn-Sham (KS) eigenvalues and orbitals; and the electron-hole binding energy will be computed based on screened Coulomb interaction of corresponding DFT orbitals. The accuracy of these approaches will be examined against many-body methods of GW/BSE and quantum Monte Carlo (QMC). The PI will also work on improving the accuracy and efficiency of the GW/BSE and QMC methods in electronic excitation computations by using better KS orbitals obtained from orbital-dependent DFT as inputs. Then an extended QMC database of ground- and excited-state properties will be developed, and this will be spot checked and supplemented with data from GW/BSE calculations. The investigation will subsequently focus on the development of an improved exchange-correlation (XC) density functional beyond the current generalized gradient approximation (GGA) level of parameterization, with parameters fitted to the QMC database. This will allow the ground-state properties of focus systems to be more precisely predicted using DFT. These new developments will then be applied to investigate a chosen set of complex nanostructures that have great potential for opening new routes in designing materials with improved transport, electronic, and optical properties for PV and other optoelectronic usages: (1) Hybrid interfaces between materials with distinct electronic and optical properties, such as organic molecules (conjugated polymers, e.g. P3HT) and inorganic semiconducting materials (Si and ZnO). Complicated interface structures, including interface bonding configurations, compositional and geometrical blending patterns, interfacial defects, and various sizes and shapes of inorganic nanomaterials, will be considered for the purpose of understanding the working mechanisms of present organic/nano PV systems and designing optimum interface structures for fast charge separation and injection. (2) Complex-structured semiconducting nanomaterials that could induce charge separation without pn- or hetero-junctions. The new methodology will allow the PI to investigate the performance of realistic semiconducting nanomaterials of internal (impurities, defects, etc.) and external (uneven surface, mechanical twisting and bending, surface chemistry, etc.) complexities on optical absorption and charge transport against charge trapping and recombination. Of particular interest is whether such structural complexity in a single material could even be beneficial for PV usage, for example, charge separation through morphology control. Successful completion of the proposed DFT methodology would have a far-reaching impact on our ability to study and exploit the nature of electronic excitations in complex materials, advancing the design of next-generation electronic and optoelectronic devices in all facets of renewable energy conversion and storage, including photovoltaics, thermoelectricity, photochemistry, etc.

14 SOLAR ENERGY↗

DOE OSTI2022

Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data

The wind energy industry is continuously improving their operational and maintenance practice for reducing the levelized costs of energy. Anticipating failures in wind turbines enables early warnings and timely intervention, so that the costly corrective maintenance can be prevented to the largest extent possible. It also avoids production loss owing to prolonged unavailability. One critical element allowing early warning is the ability to accumulate small-magnitude symptoms resulting from the gradual degradation of wind turbine systems. Inspired by the cumulative sum control chart method, this study reports the development of a wind turbine failure detection method with such early warning capability. Specifically, the following key questions are addressed: what fault signals to accumulate, how long to accumulate, what offset to use, and how to set the alarm-triggering control limit. We apply the proposed approach to 2 years’ worth of Supervisory Control and Data Acquisition data recorded from five wind turbines. We focus our analysis on gearbox failure detection, in which the proposed approach demonstrates its ability to anticipate failure events with a good lead time.

17 WIND ENERGY↗

NASA NTRS1988

Monthly mean global climatology of temperature, wind, geopotential height, and pressure for 0 - 120 km

A monthly mean climatology is presented of temperature, wind, and geopotential height with nearly pole-to-pole coverage (80 S to 80 N) for 0 to 210 km, which can be used as a function of altitude and pressure. The purpose is to provide a reference for various atmospheric research and analysis activities. Data sources and methods of computation are described; in general, hydrostatic and thermal wind balance are maintained at all levels and latitudes. As observed in a series of cross-sectional plots, this climatology accurately reproduces most of the characteristic features of the atmosphere such as equatorial wind and the general structure of the tropopause, stratopause, and mesopause. A series of zonal wind profiles is also represented comparing this climatological wind with monthly mean climatological direct wind measurements in the upper mesosphere and lower thermosphere. The temperature and zonal wind climatology at stratospheric levels is compared with corresponding data from the National Meteorological Center, and general agreement is observed between the two data sets. Tables of the climatological values as a function of latitude and height for each month are contained in Appendix B, and are also available in floppy disk.

Fleming, Eric L.↗

NASA NTRS2003

Reusable Rack Interface Controller Common Software for Various Science Research Racks on the International Space Station

The purpose of the EXPRESS (Expedite the PRocessing of Experiments to Space Station) rack project is to provide a set of predefined interfaces for scientific payloads which allow rapid integration into a payload rack on International Space Station (ISS). VxWorks' was selected as the operating system for the rack and payload resource controller, primarily based on the proliferation of VME (Versa Module Eurocard) products. These products provide needed flexibility for future hardware upgrades to meet everchanging science research rack configuration requirements. On the International Space Station, there are multiple science research rack configurations, including: 1) Human Research Facility (HRF); 2) EXPRESS ARIS (Active Rack Isolation System); 3) WORF (Window Observational Research Facility); and 4) HHR (Habitat Holding Rack). The RIC (Rack Interface Controller) connects payloads to the ISS bus architecture for data transfer between the payload and ground control. The RIC is a general purpose embedded computer which supports multiple communication protocols, including fiber optic communication buses, Ethernet buses, EIA-422, Mil-Std-1553 buses, SMPTE (Society Motion Picture Television Engineers)-170M video, and audio interfaces to payloads and the ISS. As a cost saving and software reliability strategy, the Boeing Payload Software Organization developed reusable common software where appropriate. These reusable modules included a set of low-level driver software interfaces to 1553B. RS232, RS422, Ethernet buses, HRDL (High Rate Data Link), video switch functionality, telemetry processing, and executive software hosted on the FUC computer. These drivers formed the basis for software development of the HRF, EXPRESS, EXPRESS ARIS, WORF, and HHR RIC executable modules. The reusable RIC common software has provided extensive benefits, including: 1) Significant reduction in development flow time; 2) Minimal rework and maintenance; 3) Improved reliability; and 4) Overall reduction in software life cycle cost. Due to the limited number of crew hours available on ISS for science research, operational efficiency is a critical customer concern. The current method of upgrading RIC software is a time consuming process; thus, an improved methodology for uploading RIC software is currently under evaluation.

Lu, George C.↗

NASA NTRS2014

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångstrom exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6C calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra- Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6C approach removed an additional negative decadal trend of Terra (Delta)NDVI approx.0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Terra and Aqua↗

NASA NTRS2015

Development of an Infrared Lamp Array for the Smap Spacecraft Thermal Balance Test

NASA launched the SMAP observatory in January 2015 aboard a Delta II into a sun-synchronous orbit around Earth. The science payload of a radar and a radiometer utilizes a shared rotating six-meter antenna to provide a global map of the Earth's soil moisture content and its freeze/thaw state on a global, high-resolution scale in this three-year mission. An observatory-level thermal balance test conducted in May/June 2014 validated the thermal design and demonstrated launch readiness as part of the planned environmental test campaign. An infrared lamp array was designed and used in the thermal balance test to replicate solar heating on the solar array and sunlit side of the spacecraft that would normally be seen in orbit. The design, implementation, and operation of an infrared lamp array used for this nineteen-day system thermal test are described in this paper. Instrumental to the smooth operation of this lamp array was a characterization test performed in the same chamber two months prior to the observatory test to provide insight into its array operation and flux uniformity. This knowledge was used to identify the lamp array power settings that would provide the worst case predicted on-orbit fluxes during eclipse, cold, and hot cases. It also showed the lamp array variation when adjustments in flux were needed. Calorimeters calibrated prior to testing determined a relationship between calorimeter temperature and lamp array flux. This allowed the team to adjust the lamp output for the desired absorbed flux on the solar array. Flux levels were within 10% of the desired value at the center of the solar array with an ability to maintain these levels within 5% during steady state cases. All tests demonstrated the infrared lamp array functionality and furthered lamp array understanding for modeling purposes. This method contributed to a high-fidelity environmental simulation, which was required to replicate the extreme on-orbit thermal environments.

Miller, Jennifer R.↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Reliability↗

NASA NTRS2024

Assessing the Impact of Climate Change on Atmospheric Rivers: A Modeling Perspective

Atmospheric rivers (ARs) play a crucial role in the poleward transport of water vapor, and the AR-associated precipitation is a critical component of global water supplies, making it critical that we understand how ARs may change in the future. To approach this issue, integrations of the NASA Goddard Institute for Space Studies global climate model ModelE version 2.1 (GISSE2.1) are employed. Multiple configurations of the model simulating different climates are analyzed: (1) the last-glacial maximum; (2) present day; (3) the end of the 21st century. The thermodynamic and dynamic components of changes to AR frequency are analyzed using a decomposition method. This method utilizes differences in distinct AR seasonal climatology frequencies derived from various vertically integrated water vapor transport (IVT) thresholds to resolve AR frequency into its components. Global mean state changes in poleward AR frequency for different climates are dominated by precipitable water vapor (PWV) changes. A set of idealized cold and warm climates in which present day sea surface temperatures are uniformly changed are considered for a targeted analysis of the south Pacific Ocean basin. For this analysis, frequency and distribution of AR events in the model runs are analyzed by comparing them to changes in the jet stream as well as the Eulerian storm tracks and low-level baroclinicity. Latitudinal shifts in the ARs in the south Pacific Ocean basin using our integrations are not as tightly coupled to these two storm-related climatological metrics in the midlatitudes but fare better on the poleward side of the storm tracks.

Atmospheric rivers↗