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Antiarrhythmic treatment of fetal supraventricular tachycardia (SVT) is used to prevent morbidity and mortality. The postnatal management of survivors is often arbitrary and varied.The purpose of this study was to examine the utility of a risk-based postnatal management strategy.Sixty-six prenatally treated newborns with fetal long or short ventriculoatrial tachycardia were reviewed. Postnatal diagnoses included atrioventricular reentrant tachycardia, atrial ectopic tachycardia, and permanent junctional reciprocating tachycardia. Unless SVT persisted to birth, early neonatal observation without treatment was recommended. For newborns without spontaneous arrhythmia after ≥2 days of observation, inducibility was tested by transesophageal pacing study (TEPS). Postnatal therapy was advised for spontaneous or inducible SVT. Characteristics associated with these outcomes were analyzed.Twenty-eight patients (42%) experienced SVT at or early after birth, which was associated with fetal long ventriculoatrial tachycardia (odds ratio [OR] 6.8; 95% confidence interval [CI] 1.88-24.57; P = .0029); delayed in utero cardioversion with treatment (median 11 days vs 5.5 days; P.0001); prenatal treatment with multiple antiarrhythmics (OR 4.42; 95% CI 1.56-12.55; P = .0059); and postnatal atrial ectopic tachycardia/permanent junctional reciprocating (OR 18.0; 95% CI 2.11-153.9; P = .0013). Of the 38 neonates undergoing TEPS, 19 (50%) had inducible tachyarrhythmias. Recurrence of SVT during infancy or childhood was documented in 4 of 6 patients with SVT at birth (66%), 8 of 22 patients with early neonatal SVT (36%), 4 of 19 patients with inducible SVT (21%), and 0 of 19 untreated patients without inducible SVT (0%) (P = .0032).The postnatal risk of SVT is related to the arrhythmia mechanism and prenatal treatment response. In newborns without spontaneous SVT, TEPS may be useful to guide the need for postnatal treatment on the basis of SVT inducibility.

Clouds play an important role in determining the Earth’s radiation budget. Despite their complex and three-dimensional (3D) structures, their interactions with radiation in models are often simplified to one-dimensional (1D), considering the time required to compute radiative transfer. Such a simplification ignores cloud Inhomogeneity and horizontal photon transport in radiative processes, which may be an acceptable approximation for low-resolution models, but can lead to significant errors and impact cloud evolution predictions in high-resolution simulations. Since model developments and operations are heading toward a higher resolution that is more susceptible to radiation errors, a fast and accurate 3D radiative transfer scheme becomes important and necessary. To address the need, we develop a machine-learning-based 3D radiative transfer emulator to provide surface radiation, shortwave fluxes at all layers, and heating rate profiles. The emulators are trained for highly heterogeneous shallow cumulus under different solar positions. We will discuss the performance of the emulators in accuracy and efficiency and discuss their potential applications.

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from 21 June to 20 July 2017 and from 15 January to 18 February 2018 in the Azores. The flights were designed to maximize the synergy between in situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Finally, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

Industry advances have greatly reduced the cost and size of ground-based shortwave (SW) sensors for the ultraviolet, visible, and near-infrared spectral ranges that make up the solar spectrum, while simultaneously increasing their ruggedness, reliability, and calibration accuracy needed for outdoor operation. These sensors and collocated meteorological equipment are an important part of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, which has supported parallel integrated measurements of atmospheric and surface properties for more than two decades at fixed and mobile sites around the world. The versatile capability of these ground-based measurements includes 1) rich spectral information required for retrieving cloud and aerosol microphysical properties, such as cloud phase, cloud particle size, and aerosol size distributions, and 2) high temporal resolution needed for capturing fast evolution of cloud microphysical properties in response to rapid changes in meteorological conditions. Here we describe examples of how ARM’s spectral radiation measurements are being used to improve understanding of the complex processes governing microphysical, optical, and radiative properties of clouds and aerosol.

Passive satellite observations play an important role in monitoring global aerosol properties and helping quantify aerosol radiative forcing in the climate system. The quality of aerosol retrievals from the satellite platform relies on well-calibrated radiance measurements from multiple spectral bands, and the availability of appropriate particle optical models. Inaccurate scattering phase function assumptions can introduce large retrieval errors. The high-spatial resolution, dual-view observations from the advanced baseline imagers onboard the two most recent geostationary operational environmental satellites (GOES), East and West, provide a unique opportunity to better constrain the aerosol phase function. Using dual GOES reflectance measurements for a dust event in the Gulf of Mexico in 2019, we demonstrate how a first-guess phase function can be reconstructed by considering the variations in observed scattering angles throughout the day. Using the reconstructed phase function, aerosol optical depth retrievals from the two satellites are self-consistent and agree well with surface-based optical depth estimates. We evaluate our methodology and reconstructed phase function against independent retrievals made from low-Earth-orbit multi-angle observations for a different dust event in 2020. Our new aerosol optical depth retrievals have a root-mean-square-difference of 0.019–0.047. Furthermore, the retrievals between the two geostationary satellites for this case agree within about 0.059 ± 0.072, as compared to larger discrepancies between the operational GOES products at times, which do not employ the dual-view technique.

Lofted mineral dust over data-sparse regions presents considerable challenges to satellite-based remote sensing methods and numerical weather prediction alike. The Southwest Asia domain is replete with such examples, with its diverse array of dust sources, dust mineralogy, and meteorologically-driven lofting mechanisms on multiple spatial and temporal scales. A microcosm of these challenges occurred over 3–4 August 2016 when two dust plumes, one lofted within an inland dry air mass and another embedded within a moist air mass, met over the Southern Arabian Peninsula. Whereas conventional infrared-based techniques readily detected the dry air mass dust plume, they experienced marked difficulties in detecting the moist air mass dust plume, which only became apparent when visible reflectance revealed it crossing over an adjacent dark water background. In combining information from numerical modelling, multi-satellite/multi-sensor observations of lofted dust and moisture profiles, and idealized radiative transfer simulations, we develop a better understanding of the environmental controls of this event, characterizing the sensitivity of infrared-based dust detection to column water vapor, dust vertical extent, and dust optical properties. Differences in assumptions of dust complex refractive index translate to variations in the sign and magnitude of the split-window brightness temperature difference commonly used for detecting mineral dust. A multi-sensor technique for mitigating the radiative masking effects of water vapor via modulation of the split-window dust-detection threshold, predicated on idealized simulations tied to these driving factors, is proposed and demonstrated. The new technique, indexed to independent-sensor description of the surface-to-500 mb atmospheric column moisture, reveals parts of the missing dust plume embedded in the moist air mass, with best performance over land surfaces.

Chip-on-Wafer-on-Substrate with Si interposer (CoWoS-S) is a TSV-based multi-chip integration technology that is widely used in high performance computing (HPC) and artificial intelligence (AI) accelerator area due to its flexibility to accommodate multiple chips of SoC, chiplet, and 3D stacks such as high bandwidth memory (HBM). The interposer size increases steadily over the past few years, from one full reticle size (∼830 mm2) to two reticle size (∼1700 mm2). The growth of interposer size offers more integration power to accommodate more active silicon in a package to satisfy the HPC/AI needs. In this paper, we report the new 5th generation CoWoS-S (CoWoS-S5) based on a Si interposer as large as three full reticle size (∼2500 mm2) by a novel 2-way lithography stitching approach. This will accommodate a multiple of logic chips at a total area of 1200 mm2 (with chiplets) together with eight HBM stacks. Besides the dimensional increase of the Si interposer, new features are incorporated to further enhance the electrical and thermal performances of CoWoS-S5 compared with the previous CoWoS-S portfolio. These include an integrated deep trench capacitor (iCap) for enhanced power integrity, 5 layers of sub-micron Cu interconnect with reduced sheet resistance to satisfy high speed die to die interconnect, new TSV structure interposer for both return and insertion loss reduction, and a higher thermal conductivity thermal interface material (TIM) to achieve a lower thermal resistance. Component level reliability with excellent electrical and physical results are also discussed.

We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine‐learning and optimization techniques and are constrained by in situ cloud probe measurements from the recent Atmospheric Radiation Measurement Program field campaign at Azores. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively, outperforming existing parameterizations. Our results confirm that cloud and drizzle water content are the most important factors for determining accretion rates. However, for autoconversion, in addition to cloud water content and droplet number concentration, we discovered a key role of drizzle number concentration that is missing in current parameterizations. The robust relation between autoconversion rate and drizzle number concentration is surprising but real, and furthermore supported by theory. Thus, drizzle number concentration should be considered in parameterizations for improved representation of the autoconversion process., Key Points Machine‐learning trained by in situ data constrains autoconversion and accretion rates with uncertainty of 15% and 5%, respectivelyThere is a surprising relation between autoconversion rate and drizzle number concentration that significantly improves parameterizationsThe exponent of autoconversion rate dependence on cloud number concentration is 0.75, lower than that in existing parameterizations

The ability to separate cloud and drizzle returns in active remote sensing observations is important for understanding the microphysics of clouds and precipitation. Yet, robust separations remain challenging in radar remote sensing. Prior methods for cloud and drizzle separation for radar observations use the properties of the Doppler spectra such as skewness. However, these methods have challenges when the drizzle becomes dominant in the observation volume. This paper presents a parametric time domain method (PTDM) that separates cloud and drizzle using the Doppler spectra measurements without assuming any prior properties of cloud and drizzle. The advantage of PTDM is that it can estimate the signal properties in the time domain and can obtain the cloud and drizzle estimates simultaneously. Based on our radar signal simulations, the uncertainty in estimated power and velocity from PTDM are within 2 dB and 0.02 m s−1, respectively. We have also evaluated the PTDM algorithm using observations from the Atmospheric Radiation Measurement (ARM) Program W-band cloud radar in the Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP-MBL) campaign at the Azores in 2009–10. Two cases corresponding to light and moderate drizzling conditions are considered for the study. The statistics of the estimates obtained show that the PTDM method performs well in separating the cloud and drizzle returns. Finally, the estimated cloud and drizzle reflectivity from PTDM were used to retrieve their corresponding microphysical properties, showing that the retrieved liquid water path agrees to 25 g m−2 with the benchmark microwave method.

Secondary ice production processes are widely proposed as the pathway by which observed cloud ice number concentration can markedly exceed what is expected from primary ice nucleation alone. These processes play a critical, yet poorly constrained, role in the lifecycle of mixed-phase clouds. Presently, main constraints on secondary ice production come from airborne observations, but the transiency of such observations makes it difficult to paint a complete picture of these processes. Here, we develop a novel method for retrieving ice number concentration in a Lagrangian reference frame, allowing us to unearth information not accessible from existing aircraft observations. Our retrieval method employs an iterative ensemble approach, advanced ice crystal models, and the traditional suite of polarimetric radar observables. We will present examples from the Atmospheric Radiation Measurement (ARM) program Mobile Facility deployment in Finland and evaluations against in-situ observations from the UK Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) field campaign. We will also present a climatology of cloud ice number concentration from the Finland campaign, shedding light on the spatiotemporal evolution, process rates, and trigger requirements of secondary ice production events.

This paper presents the spatiotemporal variability of warm rain events over southern West Africa (SWA) during the summer monsoon season for the first time, using Spinning Enhanced Visible Infrared Radiometer (SEVIRI) observations on the Meteosat geostationary satellites. The delineation of warm rain events is based on the principle that precipitating low-level clouds are associated with either sufficient water content or large cloud droplet size. Capitalising on the ability of spaceborne radar to resolve vertical cloud structures and detect the presence of precipitation, the delineation is trained by collocated SEVIRI and CloudSat observations. The resulting 12-years of observations from SEVIRI are used to examine the spatial, diurnal, seasonal and interannual variability of warm rain events over SWA. Warm rain events predominate during the monsoon in August, with little interannual variability, and persist over orography in the morning and the coasts after midday, likely enhanced by orographic lifting and land-sea breeze effects. Warm clouds have a much higher probability of precipitation along the coastlines of Liberia and Nigeria compared to the central SWA coastline and further inland. Finally, when evaluating an 8-day yet high-spatial resolution model simulation, we find that warm rain frequencies from the simulation agree well with SEVIRI near the coast but simulated warm cloud cover and thus warm rain frequencies are too low over the Gulf of Guinea. The probability of precipitation of warm clouds is also too low inland. The newly developed climatology creates opportunities to further investigate the diurnal cycle of warm rain, study aerosol-cloud-precipitation interactions, and assess the role of warm rain in the water cycle across Africa and beyond.

The contribution of cloud to the radiation budget of southern West Africa (SWA) is poorly understood and yet it is important for understanding regional monsoon evolution and for evaluating and improving climate models, which have large biases in this region. Radiative transfer calculations applied to atmospheric profiles obtained from the CERES– CloudSat–CALIPSO–MODIS (CCCM) dataset are used to investigate the effects of 12 different cloud types (defined by their vertical structure) on the regional energy budget of SWA (5°–10°N, 8°W–8°E) during June–September. We show that the large regional mean cloud radiative effect in SWA is due to nonnegligible contributions from many different cloud types; eight cloud types have a cloud fraction larger than 5% and contribute at least 5% of the regional mean shortwave cloud radiative effect at the top of the atmosphere. Low clouds, which are poorly observed by passive satellite measurements, were found to cause net radiative cooling of the atmosphere, which reduces the heating from other cloud types by approximately 10%. The sensitivity of the radiation budget to underestimating low-cloud cover is also investigated. The radiative effect of missing low cloud is found to be up to approximately −25 W m−2 for upwelling shortwave irradiance at the top of the atmosphere and 35 W m−2 for downwelling shortwave irradiance at the surface.

New, viable, and sustainable observation strategies from a constellation of satellites have attracted great attention across many scientific communities. Yet the potential for monitoring global Earth outgoing radiation using such a strategy has not been explored. To evaluate the potential of such a constellation concept and to investigate the configuration requirement for measuring radiation at a time resolution sufficient to resolve the diurnal cycle for weather and climate studies, we have developed a new recovery method and conducted a series of simulation experiments. Using idealized wide field-of-view broadband radiometers as an example, we find that a baseline constellation of 36 satellites can monitor global Earth outgoing radiation reliably to a spatial resolution of 1000 km at an hourly time scale. The error in recovered daily global mean irradiance is 0.16 W m-2 and -0.13 W m-2, and the estimated uncertainty in recovered hourly global mean irradiance from this day is 0.45 W m-2 and 0.15 W m-2, in the shortwave and longwave spectral regions, respectively. Sensitivity tests show that addressing instrument-related issues that lead to systematic measurement error remains of central importance to achieving similar accuracies in reality. The presented error statistics therefore likely represent the lower bounds of what could currently be achieved with the constellation approach, but this study demonstrates the promise of an unprecedented sampling capability for better observing the Earth’s radiation budget.

Paediatric pacemaker management is challenging because of the small patient size, complex cardiac anatomy, and unique programming considerations. Hardware placement options include epicardial and transvenous systems. When pacemaker malfunction is suspected, a systematic approach is required to determine whether there is malfunction in pacing, sensing, or no output due to hardware problem. In most cases, simple reprogramming may circumvent the problem and allow retention of the pacemaker system.

Fragile X syndrome (FXS) is the most common form of inherited intellectual disability. It is caused by the overexpansion of cytosine-guanine-guanine (CGG) trinucleotide in Fmr1 gene, resulting in complete loss of the fragile X mental retardation protein (FMRP). Previous studies using Fmr1 knockout (Fmr1 KO) mice have suggested that a N-methyl-D-aspartate receptors (NMDAR) hypofunction in the hippocampal dentate gyrus may partly contribute to cognitive impairments in FXS. Since activation of NMDAR plays an important role in dendritic arborization during neuronal development, we examined whether deficits in NMDAR function are associated with alterations in dendritic complexity in the hippocampal dentate region. The dentate granule cell layer (GCL) presents active postnatal neurogenesis, and consists of a heterogenous neuronal population with gradient ages from the superficial to its deep layer. Here, we show that neurons with multiple primary dendrites that reside in the outer GCL of Fmr1 KO mice display significantly smaller NMDAR excitatory post-synaptic currents (EPSCs) and a higher α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) to NMDA ratio in comparison to their wild-type counterparts. These deficits were associated with a significant decrease in dendritic complexity, with both dendritic length and number of intersections being significantly reduced. In contrast, although neurons with a single primary dendrite resided in the inner GCL of Fmr1 KO mice had a trend toward a reduction in NMDAR EPSCs and a higher AMPA/NMDA ratio, no alterations were found in dendritic complexity at this developmental stage. Our data indicate that the loss of FMRP causes NMDAR deficits and reduced dendritic complexity in granule neurons with multiple primary dendrites which are thought to be more mature in the GCL.

The spectrum of reflected solar radiation emerging at the top of the atmosphere is rich with Earth system information. To identify spectral signatures in the reflected solar radiation and directly relate them to the underlying physical properties controlling their structure, over 90 000 solar reflectance spectra are computed over West Africa in 2010 using a fast radiation code employing the spectral characteristics of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Cluster analysis applied to the computed spectra reveals spectral signatures related to distinct surface properties, and cloud regimes distinguished by their spectral shortwave cloud radiative effect (SWCRE). The cloud regimes exhibit a diverse variety of mean broadband SWCREs, and offer an alternative approach to define cloud type for SWCRE applications that does not require any prior assumptions. The direct link between spectral signatures and distinct physical properties extracted from clustering remains robust between spatial scales of 1, 20, and 240 km, and presents an excellent opportunity to understand the underlying properties controlling real spectral reflectance observations. Observed SCIAMACHY spectra are assigned to the calculated spectral clusters, showing that cloud regimes are most frequent during the active West African monsoon season of June–October in 2010, and all cloud regimes have a higher frequency of occurrence during the active monsoon season of 2003 compared with the inactive monsoon season of 2004. Overall, the distinct underlying physical properties controlling spectral signatures show great promise for monitoring evolution of the Earth system directly from solar spectral reflectance observations.

We use the spectrally invariant method to study the variability of cloud optical thickness τ and droplet effective radius reff in transition zones (between the cloudy and clear sky columns) observed from Solar Spectral Flux Radiometer (SSFR) and Shortwave Array Spectroradiometer-Zenith (SASZe) during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. The measurements from the SSFR and the SASZe are different, however inter-instrument differences of self-normalized measurements (divided by their own spectra at a fixed time) are small. The spectrally invariant method approximates the spectra in the cloud transition zone as a linear combination of definitely clear and cloudy spectra, where the coefficients, slope and intercept, characterize the spectrally invariant properties of the transition zone. Simulation results from the SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer) model demonstrate that (1) the slope of the visible band is positively correlated with the cloud optical thickness τ while the intercept of the near-infrared band has high negative correlation with the cloud drop effective radius reff even without the exact knowledge of τ; (2) the above relations hold for all Solar Zenith Angle (SZA) and for cloud-contaminated skies. In observations using redundant measurements from SSFR and SASZe, we find that during cloudy-to-clear transitions, (a) the slopes of the visible band decrease, and (b) the intercepts of the near-infrared band remain almost constant near cloud edges. The findings in simulations and observations suggest that, while the optical thickness decreases during the cloudy-to-clear transition, the cloud drop effective radius does not change when cloud edges are approached. These results support the hypothesis that inhomogeneous mixing dominates near cloud edges in the studied cases.

Fragile X syndrome (FXS) is caused by a mutation in the Fmr1 gene that leads to silencing of the gene and a loss of its gene product, Fragile X mental retardation protein (FMRP). Some of the key behavioral phenotypes for FXS include abnormal social anxiety and sociability. Here we show that Fmr1 knock-out (KO) mice exhibit impaired social recognition when presented with a novel mouse, and they display normal social interactions in other sociability tests. Administering minocycline to Fmr1 KO mice throughout critical stages of neural development improved social recognition memory in the novel mouse recognition task. To determine if synaptic changes in the prefrontal cortex (PFC) could have played a role in this improvement, we examined PSD-95, a member of the membrane-associated guanylate kinase family, and signaling molecules (ERK1/2, and Akt) linked to synaptic plasticity in the PFC. Our analyses indicated that while minocycline treatment can enhance behavioral performance, it does not enhance expression of PSD-95, ERK1/2 or Akt in the PFC.

Estimating the impact of radiation transport through cloud sides on the global energy budget is hampered by the lack of a fast radiation scheme suitable for use in global atmospheric models that can represent these effects in both the shortwave and longwave. This two-part paper describes the development of such a scheme, which we refer to as the Speedy Algorithm for Radiative Transfer through Cloud Sides (SPARTACUS). The principle of the method is to add extra terms to the two-stream equations to represent lateral transport between clear and cloudy regions, which vary in proportion to the length of cloud edge as a function of height. The present paper describes a robust and accurate method for solving the coupled system of equations in both the shortwave and longwave in terms of matrix exponentials. This solver has been coupled to a correlated-k model for gas absorption. We then confirm the accuracy of SPARTACUS by performing broadband comparisons with fully 3-D radiation calculations by the Monte Carlo model “MYSTIC” for a cumulus cloud field, examining particularly the percentage change in cloud radiative effect (CRE) when 3-D effects are introduced. In the shortwave, SPARTACUS correctly captures this change to CRE, which varies with solar zenith angle between −25% and +120%. In the longwave, SPARTACUS captures well the increase in radiative cooling of the cloud, although it is only able to correctly simulate the 30% increase in surface CRE (around 4 W m−2) if an approximate correction is made for cloud clustering.

Current weather and climate models neglect 3-D radiative transfer through cloud sides, which can change the cloud radiative effect (CRE) significantly. This two-part paper describes the development of the SPeedy Algorithm for Radiative TrAnsfer through CloUd Sides (SPARTACUS) to capture these effects efficiently in a two-stream radiation scheme for use in global models. The present paper concerns the longwave spectral region, where not much work has been done previously, although the limited previous work has suggested that radiative transfer through cloud sides increases the longwave surface CRE of shallow cumulus by around 30%. To assist the development of a longwave capability for SPARTACUS, we use a reference case of an isolated, isothermal, optically thick, cubic cloud in vacuum, for which 3-D effects increase CRE by exactly 200%. It is shown that for any cloud shape, the 3-D effect can be represented in SPARTACUS provided that correct account is made for (1) the effective zenith angle of diffuse radiation emitted from a cloud, (2) the spatial distribution of fluxes in the cloud, (3) cloud clustering that enhances the interception of emitted radiation by neighboring clouds, and (4) radiative smoothing leading to the effective cloud edge length being less than the measured value. We find empirically that the circumference of an ellipse fitted to a horizontal cross section through a cumulus cloud provides a good estimate of the radiatively effective cloud edge length, which provides some guidance to how cloud observations could be analyzed to extract their most important properties for radiation.

The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined., Key Points Satellite cloud droplet concentration uncertainties of 78% for pixel‐level retrievals and 54% for 1 by 1 degree retrievals are estimatedThe effective radius retrieval is the most important aspect for improvement, and more in situ evaluation is neededPotential improvements using passive and active satellite, and ground‐based instruments are discussed

International audience; Unprecedented ground-based and aircraft measurements in June-July 2016 in southern West Africa characterize atmospheric composition and dynamics, low-level cloud properties, the diurnal cycle, and air pollution impacts on health.The EU-funded project DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) investigates the relationship between weather, climate, and air pollution in southern West Africa, an area with rapid population growth, urbanisation, and increase in anthropogenic aerosol emissions. The air over this region contains a unique mixture of natural and anthropogenic gases, liquid droplets and particles, emitted in an environment, in which multi-layer clouds frequently form. These exert a large influence on the local weather and climate, mainly due to their impact on radiation, the surface energy balance, and thus the diurnal cycle of the atmospheric boundary layer.In June and July 2016, DACCIWA organized a major international field campaign in Ivory Coast, Ghana, Togo, Benin, and Nigeria. Three supersites in Kumasi, Savè, and Ile-Ife conducted permanent measurements and 15 Intensive observation periods. Three European aircraft together flew 50 research flights between 27 June and 16 July 2016 for a total of 155 hours. DACCIWA scientists launched weather balloons several times a day across the region (772 in total), measured urban emissions, and evaluated health data. The main objective was to build robust statistics of atmospheric composition, dynamics, and low-level cloud properties in various chemical landscapes to investigate their mutual interactions.This article presents an overview of the DACCIWA field campaign activities as well as some first research highlights. The rich data obtained during the campaign will be made available to the scientific community and help to advance scientific understanding, modeling, and monitoring the atmosphere over southern West Africa.

A globally complete, high temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the long-wave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 and 16.0 % of the variance at the global scale. The total variance explained by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The short-wave component of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found in regional satellite observations, but with slightly different timings due to known model biases. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content and height in convective regions but only cloud water content in marine stratocumulus regions, with substantially shorter lag times compared with the long-wave counterpart. This indicates that the short-wave radiation response to diurnal cloud development and dissipation is more rapid, which is found to be robust in the regional satellite observations. These global, diurnal radiation patterns and their coupling with other geophysical variables demonstrate the process-level understanding that can be gained using this approach and highlight a need for global, diurnal observing systems for Earth outgoing radiation in the future.

Capsule: A 21-month deployment to Graciosa Island in the northeastern Atlantic Ocean is providing an unprecedented record of the clouds, aerosols and meteorology in a poorly-sampled remote marine environment The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009- December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

Fragile X Syndrome (FXS) is the most common inherited cause of intellectual disability, and is the leading known single-gene cause of autism spectrum disorder. FXS patients display varied behavioural deficits that include mild to severe cognitive impairments in addition to mood disorders. Currently there is no cure for this condition, however minocycline is becoming commonly prescribed as a treatment for FXS patients. Minocycline has been reported to alleviate social behavioural deficits, and improve verbal functioning in patients with FXS; however, its mode of action is not well understood. Previously we have shown that FXS results in learning impairments that involve deficits in N-methyl-d-aspartate (NMDA) receptor-dependent synaptic plasticity in the hippocampal dentate gyrus (DG). Here we tested whether chronic treatment with minocycline can improve these deficits by enhancing NMDA receptor-dependent functional and structural plasticity in the DG. Minocycline treatment resulted in a significant enhancement in NMDA receptor function in the dentate granule cells. This was accompanied by an increase in PSD-95 and GluN2A and GluN2B subunits in hippocampal synaptoneurosome fractions. Minocycline treatment also enhanced dentate granule cell dendritic length and branching. In addition, our results show that chronic minocycline treatment can rescue performance in novel object recognition in FXS mice. These findings indicate that minocycline treatment has both structural and functional benefits for hippocampal cells, which may partly contribute to the pro-cognitive effects minocycline appears to have for treating FXS.

Satellite radar remote-sensing of rain is important for quantifying of the global hydrological cycle, atmospheric energy budget, and many microphysical cloud and precipitation processes; however, radar estimates of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94-GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced global retrievals of the rain drop size distribution. In this paper we demonstrate the capability to retrieve both rain rate and a parameter of the rain drop size distribution from an airborne 94-GHz Doppler radar using CAPTIVATE, the variational retrieval algorithm developed for EarthCARE radar–lidar synergy. For a range of rain regimes observed during the Tropical Composition, Cloud and Climate Coupling (TC4) field campaign in the eastern Pacific in 2007, we explore the contributions of Doppler velocity and path-integrated attenuation (PIA) to the retrievals, and evaluate the retrievals against independent measurements from a second, less attenuated, Doppler radar aboard the same aircraft. Retrieved drop number concentration varied over five orders of magnitude between light rain from melting ice, and warm rain from liquid clouds. Doppler velocity can be used to estimate rain rate over land, and retrievals of rain rate and drop number concentration are possible in profiles of light rain over land; in moderate warm rain, drop number concentration can be retrieved without Doppler velocity. These results suggest that EarthCARE rain retrievals facilitated by Doppler radar will make substantial improvements to the global understanding of the interaction of clouds and precipitation.

Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship-based retrievals of cloud optical depth (τ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration Nd and compute a cloud-aerosol interaction (ACI) metric defined as ACICCN = ∂ ln(Nd)/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN0.4) and 0.3% (CCN0.3) supersaturation. Analysis of CCN0.4, accumulation mode aerosol concentration (Na), and extinction coefficient (σext) indicates that Na and σext can be used as CCN0.4 proxies for estimating ACI. ACICCN derived from 10 min averaged Nd and CCN0.4 and CCN0.3, and CCN0.4 regressions using Na and σext, produce high ACICCN: near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in Nd. ACICCN computed in deep boundary layers was small (ACICCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate-resolution Imaging Spectroradiometer and GOES-15 data were compared against ship-based retrievals and further analyzed to compute a satellite-based ACICCN. Satellite data correlated well with their ship-based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite Nd and ship-based CCN0.4 and Na yielded a maximum ACICCN = 0.88–0.92, a value slightly less than the ship-based ACICCN, but still consistent with aircraft-based studies in the eastern Pacific.

Tropical Applications of Meteorology Using Satellite and Ground-Based Observations (TAMSAT) rainfall estimates are used extensively across Africa for operational rainfall monitoring and food security applications; thus, regional evaluations of TAMSAT are essential to ensure its reliability. This study assesses the performance of TAMSAT rainfall estimates, along with the African Rainfall Climatology (ARC), version 2; the Tropical Rainfall Measuring Mission (TRMM) 3B42 product; and the Climate Prediction Center morphing technique (CMORPH), against a dense rain gauge network over a mountainous region of Ethiopia. Overall, TAMSAT exhibits good skill in detecting rainy events but underestimates rainfall amount, while ARC underestimates both rainfall amount and rainy event frequency. Meanwhile, TRMM consistently performs best in detecting rainy events and capturing the mean rainfall and seasonal variability, while CMORPH tends to overdetect rainy events. Moreover, the mean difference in daily rainfall between the products and rain gauges shows increasing underestimation with increasing elevation. However, the distribution in satellite–gauge differences demonstrates that although 75% of retrievals underestimate rainfall, up to 25% overestimate rainfall over all elevations. Case studies using high-resolution simulations suggest underestimation in the satellite algorithms is likely due to shallow convection with warm cloud-top temperatures in addition to beam-filling effects in microwave-based retrievals from localized convective cells. The overestimation by IR-based algorithms is attributed to nonraining cirrus with cold cloud-top temperatures. These results stress the importance of understanding regional precipitation systems causing uncertainties in satellite rainfall estimates with a view toward using this knowledge to improve rainfall algorithms.

We have extensively evaluated the response of cloud base drizzle rate (Rcb; mm d−1) in warm clouds to liquid water path (LWP; g m−2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm−3), an aerosol proxy. This evaluation is based on a 19 month long data set of Doppler radar, lidar, microwave radiometers, and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law Rcb=0.0015±0.0009⋅LWP1.68±0.05NCCN−0.66±0.08, indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm−3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates but agrees well with simulations from a multiscale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multiscale models to accurately simulate the response of LWP to aerosol perturbations.

[1] The ability of six scanning cloud radar scan strategies to reconstruct cumulus cloud fields for radiation study is assessed. Utilizing snapshots of clean and polluted cloud fields from large eddy simulations, an analysis is undertaken of error in both the liquid water path and monochromatic downwelling surface irradiance at 870 nm of the reconstructed cloud fields. Error introduced by radar sensitivity, choice of radar scan strategy, retrieval of liquid water content (LWC), and reconstruction scheme is explored. Given an infinitely sensitive radar and perfect LWC retrieval, domain average surface irradiance biases are typically less than 3 W m−2 µm−1, corresponding to 5–10% of the cloud radiative effect (CRE). However, when using a realistic radar sensitivity of −37.5 dBZ at 1 km, optically thin areas and edges of clouds are difficult to detect due to their low radar reflectivity; in clean conditions, overestimates are of order 10 W m−2 µm−1 (~20% of the CRE), but in polluted conditions, where the droplets are smaller, this increases to 10–26 W m−2 µm−1 (~40–100% of the CRE). Drizzle drops are also problematic; if treated as cloud droplets, reconstructions are poor, leading to large underestimates of 20–46 W m−2 µm−1 in domain average surface irradiance (~40–80% of the CRE). Nevertheless, a synergistic retrieval approach combining the detailed cloud structure obtained from scanning radar with the droplet-size information and location of cloud base gained from other instruments would potentially make accurate solar radiative transfer calculations in broken cloud possible for the first time.

[1] Comprehensive surface-based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in the central Yangtze Delta region, during a research campaign from May 2008 to December 2009. Cloud optical depth (COD), effective radius (Re), and liquid water path (LWP) were retrieved from measurements made with a suite of ground-based and spaceborne instruments, including an Analytical Spectral Devices spectroradiometer, a multifilter rotating shadowband radiometer, a multichannel microwave radiometer profiler, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes. Annual mean LWP, COD, and Re are 115.8 ± 90.8 g/m2, 28.5 ± 19.2, and 6.9 ± 4.2 µm. Over 90% of LWP values are less than 250 g/m2. Most of the COD values (>90%) fall between 5 and 60, and ~80% of Re values are less than 10 µm. Maximum (minimum) values of LWP and Re occur in summer (winter); COD is highest in winter and spring. Raining and nonraining clouds have significant differences in LWP, COD, and Re. Rainfall frequency is best correlated with LWP, followed by COD and Re. Cloud properties retrieved from multiple ground-based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD, and Re were −33.6 g/m2 (−26.4%), −5.8 (−31.4%), and 2.9 µm (29.3%) for 11 MODIS-Terra overpasses and −43.3 g/m2 (−22.3%), −3.0 (−10.0%), and −1.3 µm (−12.0%) for 8 MODIS-Aqua overpasses, respectively. These discrepancies indicate that MODIS cloud products still suffer from large uncertainties in this region.

Fragile-X syndrome (FXS) is caused by the transcriptional repression of the Fmr1 gene resulting in loss of the Fragile-X mental retardation protein (FMRP). This leads to cognitive impairment in both male and female patients, however few studies have focused on the impact of FXS in females. Significant cognitive impairment has been reported in approximately 35% of women who exhibit a heterozygous Fmr1 gene mutation, however to date there is a paucity of information regarding the mechanistic underpinnings of these deficits. We, and others, have recently reported that there is significant impairment in N-methyl-d-aspartate receptor (NMDAR)-dependent long-term potentiation (LTP) and long-term depression (LTD) in the hippocampal dentate gyrus (DG) of male Fmr1 knock out mice. Here we examined if female mice displaying a heterozygous loss of the Fmr1 gene (Fmr1+/‐) would exhibit similar impairments in DG-dependent spatial memory processing and NMDAR hypofunction. We found that Female Fmr1+/‐ mice did not show impaired metabotropic glutamate receptor (mGluR)-LTD in the CA1 region, and could perform well on a temporal ordering task that is thought to involve this brain region. In contrast, female Fmr1+/‐ mice showed impairments in a pattern separation task thought to involve the DG, and also displayed a significant impairment in both NMDAR-dependent LTD and LTP in this region. The LTP impairment could be rescued by administering the NMDAR co-agonist, glycine. Our data suggests that NMDAR hypofunction in the DG may partly contribute to learning and memory impairment in female Fmr1+/‐ mice. Targeting NMDAR-dependent mechanisms may offer hope as a new therapeutic approach for treating female FXS patients with learning and memory impairments.

The single scattering albedo omega(sub O lambda) in atmospheric radiative transfer is the ratio of the scattering coefficient to the extinction coefficient. For cloud water droplets both the scattering and absorption coefficients, thus the single scattering albedo, are functions of wavelength lambda and droplet size r. This note shows that for water droplets at weakly absorbing wavelengths, the ratio omega(sub O lambda)(r)/omega(sub O lambda)(r (sub O)) of two single scattering albedo spectra is a linear function of omega(sub O lambda)(r). The slope and intercept of the linear function are wavelength independent and sum to unity. This relationship allows for a representation of any single scattering albedo spectrum omega(sub O lambda)(r) via one known spectrum omega(sub O lambda)(r (sub O)). We provide a simple physical explanation of the discovered relationship. Similar linear relationships were found for the single scattering albedo spectra of non-spherical ice crystals.

Small boundary-layer clouds are ubiquitous over many parts of the globe and strongly influence the Earths radiative energy balance. However, our understanding of these clouds is insufficient to solve pressing scientific problems. For example, cloud feedback represents the largest uncertainty amongst all climate feedbacks in general circulation models (GCM). Several issues complicate understanding boundary-layer clouds and simulating them in GCMs. The high spatial variability of boundary-layer clouds poses an enormous computational challenge, since their horizontal dimensions and internal variability occur at spatial scales much finer than the computational grids used in GCMs. Aerosol-cloud interactions further complicate boundary-layer cloud measurement and simulation. Additionally, aerosols influence processes such as precipitation and cloud lifetime. An added complication is that at small scales (order meters to 10s of meters) distinguishing cloud from aerosol is increasingly difficult, due to the effects of aerosol humidification, cloud fragments and photon scattering between clouds.

This study tested whether congruency between approach/avoidance dispositional motivation and message framing (gain, loss) affects receptivity to appeals for charitable donations. Participants read gain-framed and loss-framed messages regarding funding needs and completed the BIS vs. BAS scale assessing dispositional motivation. Approach-oriented people were more persuaded by gain-framed messages, and avoidance-oriented people were more persuaded by loss-framed messages. The results thus extend the congruency effect beyond self-relevant messages to include other-oriented messages as well. These findings suggest that real-world charitable appeals will be more effective to the degree that they are tailored to match the motivational dynamics of the target audience.

Background Light-chain (AL) amyloidosis is a multi-organ amyloid deposition disease caused by misfolded protein aggregation. Current treatments have improved overall (OS) and progression-free survival (PFS) but challenges remain in improving therapy with newer agents and targeting amyloid protein deposits with novel immunotherapy. We review the literature regarding efficacy of existing chemotherapy in AL amyloidosis and summarize non-FDA approved novel drugs and monoclonal antibodies (mAbs) in early phase clinical development. Methods We searched databases including Cochrane library, PubMed and ClinicalTrials.gov for all prospective and retrospective studies (As of 4/15/2018) with measured hematologic response rate (HR) in patients with AL amyloidosis since 2000. Inclusion criteria included all prospective and retrospective studies with melphalan-based treatments, bortezomib combinations including bortezomib, cyclophosphamide and dexamethasone (VCD), bortezomib and dexamethasone (VD) and immunotherapies. We included all studies with at least 5 or more patients and reported HR. Results From 918 studies, we selected 57 studies (2640 patients) evaluating HR with melphalan-based stem cell transplant (SCT) treatments and non-stem cell transplant treatments including melphalan and bortezomib combinations. Other agents included daratumumab (anti-CD38 mAb), and ixazomib (proteasome inhibitor). Mean aggregate HR reported from studies with melphalan-based SCT treatment (17 studies, n=587) was 67%. Mean aggregate HR from all non-transplant treatments (40 studies, n=2053) was 64%. Of the non-transplant treatments, HR for melphalan-based treatments (21 studies, n=1148) was 59% and varied as follows: melphalan + lenalidomide + dexamethasone (57%) and melphalan + dexamethasone (52%). Mean aggregated HR for non-transplant bortezomib-based treatment (17 studies, n=859) was 72% consisting of VD (69%) and VCD (76%). HR with Ixazomib (1 study) and Daratumumab (1 study) was 52% and 76% respectively. Other novel drugs currently being studied include 11-1F4 (chimeric fibril-reactive mAb), GSK2398852 and GSK2315698 (anti-serum amyloid protein mAbs), and NEOD001 (anti-circulating soluble and deposited aggregated amyloid mAb). Conclusion For AL amyloidosis, melphalan-based SCT has shown effectiveness while VD and VCD demonstrate effectiveness in non-transplant patients. Further studies are warranted to evaluate novel proteasome inhibitors (Ixazomib) and emerging immunotherapy with daratumumab. Current trials including amyloid protein and fibril targeting (circulating and tissue-fixed) with novel immunotherapy are innovative and may have higher clinical efficacy, but need further testing. Disclosures No relevant conflicts of interest to declare.

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS 532-nm channel, the primary channel for atmospheric products. Solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (i) calibration with coincident airborne and GLAS observations, (ii) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds, and (iii) calibration from first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.