bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Paradoxical Effects of COVID-19 on Cancer Care: Current Context and Potential Lasting Impacts
Authors: Broom Alex , Kenny Katherine , Page Alexander , Cort Nicole , Lipp Eric S. , Tan Aaron C. , Ashley David M. , Walsh Kyle M. , Khasraw Mustafa 
Published: August 2020

Abstract
Coronavirus disease 2019 (COVID-19) has fundamentally disrupted the practice of oncology, shifting care onto virtual platforms, rearranging the logistics and economics of running a successful clinical practice and research, and in some contexts, redefining what treatments patients with cancer should and can receive. Since the start of the pandemic in early 2020, there has been considerable emphasis placed on the implications for patients with cancer in terms of their vulnerability to the virus and potential exposure in healthcare settings. But little emphasis has been placed on the significant, and potentially enduring, consequences of COVID-19 for how cancer care is delivered. In this article, we outline the importance of a focus on the effects of COVID-19 for oncology practice during and potentially after the pandemic, focusing on key shifts that are already evident, including: the pivot to online consultations, shifts in access to clinical trial and definitions of “essential care,” the changing economics of practice, and the potential legacy effects of rapidly implemented changes in cancer care. COVID-19 is reshaping oncology practice, clinical trials, and delivery of cancer care broadly, and these changes might endure well beyond the short- to mid-term of the active pandemic. Therefore, shifts in practice brought about by the pandemic must be accompanied by improved training and awareness, enhanced infrastructure, and evidence-based support if they are to harness the positives and offset the potential negative consequences of the impacts of COVID-19 on cancer care.
Long Memory and Time Trends in Particulate Matter Pollution (PM2.5 and PM10) in the 50 U.S. States
Authors: Gil-Alana Luis A. , Yaya OlaOluwa S. , Awolaja Oladapo G. , Cristofaro Lorenzo 
Published: August 2020

AbstractThis paper focuses on the analysis of the time series behavior of the air quality in the 50 U.S. states by looking at the statistical properties of particulate matter (PM10and PM2.5) datasets. We use long daily time series of outdoor air quality indices to examine issues such as the degree of persistence as well as the existence of time trends in data. For this purpose, we use a long-memory fractionally integrated framework. The results show significant negative time trend coefficients in a number of states and evidence of long memory in the majority of the cases. In general, we observe heterogeneous results across counties though we notice higher degrees of persistence in the states on the west with respect to those on the east, where there is a general decreasing trend. It is hoped that the findings in the paper will continue to assist in quantitative evidence-based air quality regulation and policies.
Atmospheric Subseasonal Variability and Circulation Regimes: Spectra, Trends, and Uncertainties
Authors: Žagar Nedjeljka , Zaplotnik Žiga , Karami Khalil 
Published: August 2020

AbstractThe globally integrated subseasonal variability associated with the two main atmospheric circulation regimes, the balanced (or Rossby) and unbalanced (or inertia–gravity) regimes, is evaluated for the four reanalysis datasets: ERA-Interim, JRA-55, MERRA, and ERA5. The results quantify amplitudes and trends in midlatitude traveling and quasi-stationary Rossby wave patterns as well as in the equatorial wave activity across scales. A statistically significant reduction of subseasonal variability is found in Rossby waves with zonal wavenumber k = 6 along with an increase in variability in wavenumbers k = 3–5 in the summer seasons of both hemispheres. The four reanalyses also agree regarding increased variability in the large-scale Kelvin waves, mixed Rossby–gravity waves, and westward-propagating inertio-gravity waves with the lowest meridional mode. The amplitude and sign of trends in inertia–gravity modes with smaller zonal scales and greater meridional modes differ between the ERA-Interim and JRA-55 datasets on the one hand and the ERA5 and MERRA data on the other. An increased variability in the ERA-Interim and JRA-55 accounts for positive trends in their total subseasonal variability.
Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed
Authors: Parajuli Kshitij , Jones Scott B. , Tarboton David G. , Hipps Lawrence E. , Zhao Lin , Sadeghi Morteza , Rockhold Mark L. , Torres-Rua Alfonso , Flerchinger Gerald N. 
Published: August 2020

AbstractConsiderable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah land surface model with multiphysics option (Noah-MP) in simulating evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in situ soil moisture data during the growing season of year 2015, obtained from the Lower Sheep subcatchment within the Reynolds Creek Experimental Watershed in southwestern Idaho. We evaluated the performance of Noah-MP considering four different scenarios with 1) a one-layer soil profile with Noah-MP default soil hydraulic parameters and three more five-layer soil profiles using 2) Noah-MP default soil hydraulic parameters; 3) soil hydraulic parameters derived from a pedotransfer function using field observations; and 4) hydraulic parameters from scenario 3, which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input, and vegetation parameters. Our results indicate that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.
Projected Changes of Precipitation Characteristics Depend on Downscaling Method and Training Data: MACA versus LOCA Using the U.S. Northeast as an Example
Authors: Wang Guiling , Kirchhoff Christine J. , Seth Anji , Abatzoglou John T. , Livneh Ben , Pierce David W. , Fomenko Lori , Ding Tengyu 
Published: August 2020

AbstractThis study compares projected changes of precipitation characteristics in the U.S. Northeast in two analog-based climate downscaling products, Multivariate Adaptive Constructed Analogs (MACA) and Localized Constructed Analogs (LOCA). The level of similarity or differences between the two products varies with the type of precipitation metrics. For the total precipitation amount, the two products project significant annual increases that are similar in magnitude, spatial pattern, and seasonal distribution, with the largest increases in winter and spring. For the overall precipitation intensity or temporal aggregation of heavy precipitation (e.g., number of days with more than one inch of precipitation, the simple intensity index, and the fraction of annual precipitation accounted for by heavy events), both products project significant increases across the region with strong model consensus; the magnitude of absolute increases are similar between the two products, but the relative increases are larger in LOCA due to an underestimation of heavy precipitation in LOCA’s training data. For precipitation extremes such as the annual maximum 1-day precipitation, both products project significant increases in the long-term mean, but the magnitude of both the absolute and relative changes are much smaller in LOCA than in MACA, indicating that the extreme precipitation differences in the training data are amplified in future projections as a result of the analog-based downscaling algorithms. The two products differ the most in the intensity and frequency of rare extremes (e.g., 1-in-20-years events) for which MACA projects significant increases while the LOCA-projected changes are inconclusive over much of the study area.
Assessing the Impact of Soil Layer Depth Specification on the Observability of Modeled Soil Moisture and Brightness Temperature
Authors: Shellito Peter J. , Kumar Sujay V. , Santanello Joseph A. , Lawston-Parker Patricia , Bolten John D. , Cosh Michael H. , Bosch David D. , Holifield Collins Chandra D. , Livingston Stan , Prueger John , Seyfried Mark , Starks Patrick J. 
Published: August 2020

AbstractThe utility of hydrologic land surface models (LSMs) can be enhanced by using information from observational platforms, but mismatches between the two are common. This study assesses the degree to which model agreement with observations is affected by two mechanisms in particular: 1) physical incongruities between the support volumes being characterized and 2) inadequate or inconsistent parameterizations of physical processes. The Noah and Noah-MP LSMs by default characterize surface soil moisture (SSM) in the top 10 cm of the soil column. This depth is notably different from the 5-cm (or less) sensing depth of L-band radiometers such as NASA’s Soil Moisture Active Passive (SMAP) satellite mission. These depth inconsistencies are examined by using thinner model layers in the Noah and Noah-MP LSMs and comparing resultant simulations to in situ and SMAP soil moisture. In addition, a forward radiative transfer model (RTM) is used to facilitate direct comparisons of LSM-based and SMAP-based L-band Tb retrievals. Agreement between models and observations is quantified using Kolmogorov–Smirnov distance values, calculated from empirical cumulative distribution functions of SSM and Tb time series. Results show that agreement of SSM and Tb with observations depends primarily on systematic biases, and the sign of those biases depends on the particular subspace being analyzed (SSM or Tb). This study concludes that the role of increased soil layer discretization on simulated soil moisture and Tb is secondary to the influence of component parameterizations, the effects of which dominate systematic differences with observations.
High-Resolution (2.5 km) Ensemble Precipitation Analysis across Canada
Authors: Khedhaouiria Dikra , Bélair Stéphane , Fortin Vincent , Roy Guy , Lespinas Franck 
Published: August 2020

AbstractConsistent and continuous fields provided by precipitation analyses are valuable for hydrometeorological applications and land data assimilation modeling, among others. Providing uncertainty estimates is a logical step in the analysis development, and a consistent approach to reach this objective is the production of an ensemble analysis. In the present study, a 6-h High-Resolution Ensemble Precipitation Analysis (HREPA) was developed for the domain covering Canada and the northern part of the contiguous United States. The data assimilation system is the same as the Canadian Precipitation Analysis (CaPA) and is based on optimal interpolation (OI). Precipitation from the Canadian national 2.5-km atmospheric prediction system constitutes the background field of the analysis, while at-site records and radar quantitative precipitation estimates (QPE) compose the observation datasets. By using stochastic perturbations, multiple observations and background field random realizations were generated to subsequently feed the data assimilation system and provide 24 HREPA members plus one control run. Based on one summer and one winter experiment, HREPA capabilities in terms of bias and skill were verified against at-site observations for different climatic regions. The results indicated HREPA’s reliability and skill for almost all types of precipitation events in winter, and for precipitation of medium intensity in summer. For both seasons, HREPA displayed resolution and sharpness. The overall good performance of HREPA and the lack of ensemble precipitation analysis (PA) at such spatiotemporal resolution in the literature motivate further investigations on transitional seasons and more advanced perturbation approaches.
Changes in Future Flash Flood–Producing Storms in the United States
Authors: Dougherty Erin , Rasmussen Kristen L. 
Published: August 2020

AbstractFlash floods are high-impact events that can result in massive destruction, such as the May 2010 flash floods in the south-central United States that resulted in over $2 billion of damage. While floods in the current climate are already destructive, future flood risk is projected to increase based on work using global climate models. However, global climate models struggle to resolve precipitation structure, intensity, and duration, which motivated the use of convection-permitting climate models that more accurately depict these precipitation processes on a regional scale due to explicit representation of convection. These high-resolution convection-permitting simulations have been used to examine future changes to rainfall, but not explicitly floods. This study aims to fill this gap by examining future changes to rainfall characteristics and runoff in flash flood–producing storms over the United States using convection-permitting models under a pseudo–global warming framework. Flash flood accumulated rainfall increases on average by 21% over the United States in a future climate. Storm-generated runoff increases by 50% on average, suggesting increased runoff efficiency in future flash flood–producing storms. In addition to changes in nonmeteorological factors, which were not explored in this study, increased future runoff is possible due to the 7.5% K−1 increase in future hourly maximum rain rates. Though this median change in rain rates is consistent with Clausius–Clapeyron theory, some storms exhibit increased future rain rates well above this, likely associated with storm dynamics. Overall, results suggest that U.S. cities might need to prepare for more intense flash flood–producing storms in a future climate.
Impact of Land Initial States Uncertainty on Subseasonal Surface Air Temperature Prediction in CFSv2 Reforecasts
Authors: Shin Chul-Su , Dirmeyer Paul A. , Huang Bohua , Halder Subhadeep , Kumar Arun 
Published: August 2020

AbstractThe NCEP CFSv2 ensemble reforecasts initialized with different land surface analyses for the period of 1979–2010 have been conducted to assess the effect of uncertainty in land initial states on surface air temperature prediction. The two observation-based land initial states are adapted from the NCEP CFS Reanalysis (CFSR) and the NASA GLDAS-2 analysis; atmosphere, ocean, and ice initial states are identical for both reforecasts. This identical-twin experiment confirms that the prediction skill of surface air temperature is sensitive to the uncertainty of land initial states, especially in soil moisture and snow cover. There is no distinct characteristic that determines which set of the reforecasts performs better. Rather, the better performer varies with the lead week and location for each season. Estimates of soil moisture between the two land initial states are significantly different with an apparent north–south contrast for almost all seasons, causing predicted surface air temperature discrepancies between the two sets of reforecasts, particularly in regions where the magnitude of initial soil moisture difference lies in the top quintile. In boreal spring, inconsistency of snow cover between the two land initial states also plays a critical role in enhancing the discrepancy of predicted surface air temperature from week 5 to week 8. Our results suggest that a reduction of the uncertainty in land surface properties among the current land surface analyses will be beneficial to improving the prediction skill of surface air temperature on subseasonal time scales. Implications of a multiple land surface analysis ensemble are also discussed.
Ertel Potential Vorticity versus Bernoulli Potential on Approximately Neutral Surfaces in the Antarctic Circumpolar Current
Authors: Stanley Geoffrey J. , Dowling Timothy E. , Bradley Mary E. , Marshall David P. 
Published: August 2020

AbstractWe investigate the relationship between Ertel potential vorticity Q and Bernoulli potential B on orthobaric density surfaces in the Antarctic Circumpolar Current (ACC), using the Southern Ocean State Estimate. Similar to the extratropical atmospheres of Earth and Mars, Q and B correlate in the ACC in a function-like manner with modest scatter. Below the near-surface, the underlying function relating Q and B appears to be nearly linear. Nondimensionalizing its slope yields “Ma,” a “Mach” number for long Rossby waves, the ratio of the local flow speed to the intrinsic long Rossby wave speed. We empirically estimate the latter using established and novel techniques that yield qualitatively consistent results. Previous work related “Ma” to the degree of homogeneity of Q and to Arnol’d’s shear stability criteria. Estimates of “Ma” for the whole ACC are notably positive, implying inhomogeneous Q, on all circumpolar buoyancy surfaces studied. Upper layers generally exhibit “Ma” slightly less than unity, suggesting that shear instability may operate within these layers. Deep layers exhibit “Ma” greater than unity, implying stability. On surfaces shallower than 1000 m just north of the ACC, the Q versus B slope varies strongly on subannual and interannual time scales, but “Ma” hovers near unity. We also study spatial variability: the ACC is speckled with hundreds of small-scale features with “Ma” near unity, whereas away from the ACC “Ma” is more commonly negative or above unity, both corresponding to stability. Maps of the time-mean “Ma” show stable regions occupy most of the Southern Ocean, except for several topographically controlled hotspots where “Ma” is always near unity.
Hydraulics and Mixing of the Deep Overflow in the Lifamatola Passage of the Indonesian Seas
Authors: Tan Shuwen , Pratt Larry J. , Yuan Dongliang , Li Xiang , Wang Zheng , Li Yao , Corvianawatie Corry , Surinati Dewi , Budiman Asep S. , Bayhaqi Ahmad 
Published: August 2020

AbstractHydrographic measurements recently acquired along the thalweg of the Lifamatola Passage combined with historical moored velocity measurements immediately downstream of the sill are used to study the hydraulics, transport, mixing, and entrainment in the dense overflow. The observations suggest that the mean overflow is nearly critical at the mooring site, suggesting that a weir formula may be appropriate for estimating the overflow transport. Our assessment suggests that the weir formulas corresponding to a rectangular, triangular, or parabolic cross section all result in transports very close to the observation, suggesting their potential usage in long-term monitoring of the overflow transport or parameterizing the transport in numerical models. Analyses also suggest that deep signals within the overflow layer are blocked by the shear flow from propagating upstream, whereas the shallow wave modes of the full-depth continuously stratified flow are able to propagate upstream from the Banda Sea into the Maluku Sea. Strong mixing is found immediately downstream of the sill crest, with Thorpe-scale-based estimates of the mean dissipation rate within the overflow up to 1.1 × 10−7 W kg−1 and the region-averaged diapycnal diffusivity within the downstream overflow in the range of 2.3 × 10−3 to 10.1 × 10−3 m2 s−1. Mixing in the Lifamatola Passage results in 0.6–1.2-Sv (1 Sv ≡ 106 m3 s−1) entrainment transport added to the overflow, enhancing the deep-water renewal in the Banda Sea. A bulk diffusivity coefficient estimated in the deep Banda Sea yields 1.6 × 10−3 ± 5 × 10−4 m2 s−1, with an associated downward turbulent heat flux of 9 W m−2.
The Scale of Submesoscale Baroclinic Instability Globally
Authors: Dong Jihai , Fox-Kemper Baylor , Zhang Hong , Dong Changming 
Published: August 2020

AbstractThe spatial scale of submesoscales is an important parameter for studies of submesoscale dynamics and multiscale interactions. The horizontal spatial scales of baroclinic, geostrophic-branch mixed layer instabilities (MLI) are investigated globally (without the equatorial or Arctic oceans) based on observations and simulations in the surface and bottom mixed layers away from significant topography. Three high-vertical-resolution boundary layer schemes driven with profiles from a MITgcm global submesoscale-permitting model improve robustness. The fastest-growing MLI wavelength decreases toward the poles. The zonal median surface MLI wavelength is 51–2.9 km when estimated from the observations and from 32, 25, and 27 km to 2.5, 1.2, and 1.1 km under the K-profile parameterization (KPP), Mellor–Yamada (MY), and κ–ε schemes, respectively. The surface MLI wavelength has a strong seasonality with a median value 1.6 times smaller in summer (10 km) than winter (16 km) globally from the observations. The median bottom MLI wavelengths estimated from simulations are 2.1, 1.4, and 0.41 km globally under the KPP, MY, and κ–ε schemes, respectively, with little seasonality. The estimated required ocean model grid spacings to resolve wintertime surface mixed layer eddies are 1.9 km (50% of regions resolved) and 0.92 km (90%) globally. To resolve summertime eddies or MLI seasonality requires grids finer than 1.3 km (50%) and 0.55 km (90%). To resolve bottom mixed layer eddies, grids finer than 257, 178, and 51 m (50%) and 107, 87, and 17 m (90%) are estimated under the KPP, MY, and κ–ε schemes.
Heat Transport through Diurnal Warm Layers
Authors: Hughes Kenneth G. , Moum James N. , Shroyer Emily L. 
Published: August 2020

AbstractPenetration of solar radiation in the upper few meters of the ocean creates a near-surface, stratified diurnal warm layer. Wind stress accelerates a diurnal jet in this layer. Turbulence generated at the diurnal thermocline, where the shear of the diurnal jet is concentrated, redistributes heat downward via mixing. New measurements of temperature and turbulence from fast thermistors on a surface-following platform depict the details of this sequence in both time and depth. Temporally, the sequence at a fixed depth follows a counterclockwise path in logϵ–logN parameter space. This path also captures the evolution of buoyancy Reynolds number (a proxy for the anisotropy of the turbulence) and Ozmidov scale (a proxy for the outer vertical length scale of turbulence in the absence of the free surface). Vertically, the solar heat flux always leads to heating of fluid parcels in the upper few meters, whereas the turbulent heat flux divergence changes sign across the depth of maximum vertical temperature gradient, cooling fluid parcels above and heating fluid parcels below. In general, our measurements of fluid parcel heating or cooling rates of order 0.1°C h−1 are consistent with our estimates of heat flux divergence. In weak winds (<2 m s−1), sea surface temperature (SST) is controlled by the depth-dependent absorption of solar radiation. In stronger winds, turbulent mixing controls SST.