Relationships Between Supermicrometer Sea Salt Aerosol and Marine Boundary Layer Conditions: Insights From Repeated Identical Flight Patterns

The article of record as published may be found at http://dx.doi.org/10.1029/2019jd032346.The MONterey Aerosol Research Campaign (MONARC) in May–June 2019 featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. The objective of this study is to use MONARC data along with machine learning analysis to evaluate relationships between both supermicrometer sea salt aerosol number (N>1) and volume (V>1) concentrations and wind speed, wind direction, sea surface temperature (SST), ambient temperature (Tamb), turbulent kinetic energy (TKE), relative humidity (RH), marine boundary layer (MBL) depth, and drizzle rate. Selected findings from this study include the following: (i) Near surface (1 and V>1 concentration ranges were 0.1–4.6 cm?3 and 0.3–28.2 ?m3 cm ?3, respectively; (ii) four meteorological regimes were identified during MONARC with each resulting in different N>1 and V>1 concentrations and also varying horizontal and vertical profiles; (iii) the relative predictive strength of the MBL properties varies depending on predicting N>1 or V>1, with MBL depth being more highly ranked for predicting N>1 and with TKE being higher for predicting V>1; (iv) MBL depths >400 m (1 and V>1 concentrations; (v) enhanced drizzle rates coincide with reduced N>1 and V>1 concentrations; (vi) N>1 and V>1 concentrations exhibit an overall negative relationship with SST and RH and an overall positive relationship with Tamb; and (vii) wind speed and direction were relatively weak predictors of N>1 and V>1.This work was funded by Office of Naval Research grant N00014-16-1-2567 and National Aeronautics and Space Administration (NASA) grant 80NSSC19K0442, the latter of which is in support of the ACTIVATE Earth Venture Suborbital-3 (EVS-3) investigation, which is funded by NASA’s Earth Science Division and managed through the Earth System Science Pathfinder Program Office.This work was funded by Office of Naval Research grant N00014-16-1-2567 and National Aeronautics and Space Administration (NASA) grant 80NSSC19K0442, the latter of which is in support of the ACTIVATE Earth Venture Suborbital-3 (EVS-3) investigation, which is funded by NASA’s Earth Science Division and managed through the Earth System Science Pathfinder Program Office

Organic enrichment in droplet residual particles relative to out of cloud over the northwestern Atlantic: analysis of airborne ACTIVATE data

Cloud processing is known to generate aerosol species such as sulfate and secondary organic aerosol, yet there is a scarcity of airborne data to examine this issue. The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) was designed to build an unprecedented dataset relevant to aerosol cloud interactions with two coordinated aircraft over the northwestern Atlantic, with aerosol mass spectrometer data used from four deployments between 2020 2021 to contrast aerosol composition below, in (using a counterflow virtual impactor) and above boundary layer clouds

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem

Relationships between supermicrometer particle concentrations and cloud water sea salt and dust concentrations, analysis of MONARC and ACTIVATE data

This study uses airborne field data from the MONterey Aerosol Research Campaign (MONARC northeast Pacific summer 2019) and Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE: northwest Atlantic winter and summer 2020) to examine relationships between giant cloud condensation nuclei (GCCN) and cloud composition to advance knowledge of poorly characterized GCCNc loud interactions. The analysis compares cloud water composition data to particle concentration data with different minimum dry diameters between 1 and 10 mum (hereafter referred to as GCCN) collected below and above clouds adjacent to where cloud water samples were collected

Executive functioning in children with an autism spectrum disorder: Can we differentiate

The aim of this study was to investigate whether children with high-functioning autism (HFA), Asperger's syndrome (AS), and pervasive developmental disorder not otherwise specified (PDDNOS) can be differentiated from each other and from normal controls on their neurocognitive executive functioning (EF) profile. Children with HFA and AS showed the most EF deficits. The EF profile of the PDDNOS group was more disturbed that the normal control group, but was less disturbed than the profile of the HFA and AS groups. Little difference was found between the three PDD subtypes with respect to EF. This study supports the view that executive dysfunctioning plays an important role in autism. The usefulness of a distinction between different PDD subtypes was not demonstrated. © 2006 Springer Science+Business Media, Inc

Search for the bcb_c meson in hadronic Z decays

A search for the Bc meson decaying into the channels J/psi pi+ and J/psi l nu (l = e or mu) is performed in a sample of 3.9 million hadronic Z decays collected by the ALEPH detector. This search results in the observation of 0 and 2 candidates in each of these channels, respectively, while 0.44 and 0.81 background events are expected. The following 90\% confidence level upper limits are derived: Br(Z->Bc X)/Br(Z->q q )*Br(Bc->J/psi pi+) 3.6 10^-5 Br(Z->Bc X)/Br(Z->q q )*Br(Bc->J/psi l nu) 5.2 10^-5 An additional Bc->J/psi(e+e-) mu nu candidate with very low background probability, found in an independent analysis, is also described in detail

Measurement of the W-pair cross section in e+e−e^+ e^- collisions at 172 GeV

The e+e- --> W+W- cross section is measured in a data sample collected by ALEPH at a mean centre--of--mass energy of 172.09 GEV, corresponding to an integrated luminosity of 10.65 pb-1. Cross sections are given for the three topologies, fully leptonic, semi-leptonic and hadronic of a W-pair decay. Under the assumption that no other decay modes are present, the W-pair cross section is measured to be 11.7 +- 1.2 (stat.) +- 0.3 (syst.) pb. The existence of the triple gauge boson vertex of the Standard Model is clearly preferred by the data. The decay branching ratio of the W boson into hadrons is measured to be B(W --> hadrons) = 67.7 +- 3.1 (stat.) +- 0.7 (syst.)%, allowing a determination of the CKM matrix element |Vcs|= 0.98 +- 0.14 (stat.) +- 0.03 (syst.)

Measurement of the tau lepton lifetime with the three-dimensional impact parameter method.

A new method is presented for the measurement of the mean $\tau$ lepton lifetime using events in which $\tau$'s are pair-produced and both $\tau$'s decay to hadrons and $\nu_\tau$. Based on the correlation between the two $\tau$'s produced at a symmetric $e^+ e^-$ collider, the 3DIP method relies on the three-dimensional information from a double-sided vertex detector and on kinematic constraints for the precise measurement of the $\tau$ decay angles. Using the data collected from 1992 to 1994 with the ALEPH detector at LEP, a $\tau$ lifetime of $288.0 \pm 3.1 \pm 1.3$\fs is obtained from the sample in which both $\tau$'s decay to one charged track, and $292.8 \pm 5.6 \pm 3.0$\fs from the sample in which one $\tau$ decays to one prong and the other to three prongs. The results show small statistical correlations with those derived from other methods. When combined with the previously published ALEPH measurements, the resulting $\tau$ lifetime is $291.2 \pm 2.0 \pm 1.2$\fs