Study of MPLNET-Derived Aerosol Climatology over Kanpur, India, and Validation of CALIPSO Level 2 Version 3 Backscatter and Extinction Products

The level 2 aerosol backscatter and extinction profiles from the NASA Micropulse Lidar Network (MPLNET) at Kanpur, India, have been studied from May 2009 to September 2010. Monthly averaged extinction profiles from MPLNET shows high extinction values near the surface during October March. Higher extinction values at altitudes of 24 km are observed from April to June, a period marked by frequent dust episodes. Version 3 level 2 Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol profile products have been compared with corresponding data from MPLNET over Kanpur for the above-mentioned period. Out of the available backscatter profiles, the16 profiles used in this study have time differences less than 3 h and distances less than 130 km. Among these profiles, four cases show good comparison above 400 m with R2 greater than 0.7. Comparison with AERONET data shows that the aerosol type is properly identified by the CALIOP algorithm. Cloud contamination is a possible source of error in the remaining cases of poor comparison. Another source of error is the improper backscatter-to-extinction ratio, which further affects the accuracy of extinction coefficient retrieval

Diminishing returns drive altruists to help extended family

This is the author accepted manuscript. The final version is available from nature Research via the DOI in this recordData availability: The transitions data for P. canadensis are available in the Supplementary Information.Code availability: The statistical code and individual-based simulation code are available in the Supplementary Information.Altruism between close relatives can be easily explained. However, paradoxes arise when organisms divert altruism towards more distantly related recipients. In some social insects, workers drift extensively between colonies and help raise less related foreign brood, seemingly reducing inclusive fitness. Since being highlighted by W. D. Hamilton, three hypotheses (bet hedging, indirect reciprocity and diminishing returns to cooperation) have been proposed for this surprising behaviour. Here, using inclusive fitness theory, we show that bet hedging and indirect reciprocity could only drive cooperative drifting under improbable conditions. However, diminishing returns to cooperation create a simple context in which sharing workers is adaptive. Using a longitudinal dataset comprising over a quarter of a million nest cell observations, we quantify cooperative payoffs in the Neotropical wasp Polistes canadensis, for which drifting occurs at high levels. As the worker-to-brood ratio rises in a worker’s home colony, the predicted marginal benefit of a worker for expected colony productivity diminishes. Helping related colonies can allow effort to be focused on related brood that are more in need of care. Finally, we use simulations to show that cooperative drifting evolves under diminishing returns when dispersal is local, allowing altruists to focus their efforts on related recipients. Our results indicate the power of nonlinear fitness effects to shape social organization, and suggest that models of eusocial evolution should be extended to include neglected social interactions within colony networks.Smithsonian Tropical Research Institute (STRI)National Geographic SocietyNatural Environment Research Council (NERC)European Research Council (ERC

Comparison of surface and column measurements of aerosol scattering properties over the western North Atlantic Ocean at Bermuda

Light scattering by size-resolved aerosols in near-surface air at Tudor Hill, Bermuda, was measured between January and June 2009. Vertical distributions of aerosol backscattering and column-averaged aerosol optical properties were characterized in parallel with a micro-pulse lidar (MPL) and an automated sun–sky radiometer. Comparisons were made between extensive aerosol parameters in the column, such as the lidar-retrieved extinction at 400 m and the aerosol optical depth (AOD), and scattering was measured with a surface nephelometer. Comparisons were also made for intensive parameters such as the Ångström exponent and calculations using AERONET(Aerosol Robotic Network)-derived aerosol physical parameters (size distribution, index of refraction) and Mie theory, and the ratio of submicron scattering to total scattering for size-segregated nephelometer measurements. In these comparisons the <i>r</i>² was generally around 0.50. Data were also evaluated based on back trajectories. The correlation between surface scattering and lidar extinction was highest for flows when the surface scattering was dominated by smaller particles and the flow had a longer footprint over land then over the ocean. The correlation of AOD with surface scatter was similar for all flow regimes. There was also no clear dependence of the atmospheric lapse rate, as determined from a nearby radiosonde station, on flow regime. The Ångström exponent for most flow regimes was 0.9–1.0, but for the case of air originating from North America, but with significant time over the ocean, the Ångström exponent was 0.57 ± 0.18. The submicron fraction of aerosol near the surface (<i>R</i>_sub-surf) was significantly greater for the flows from land (0.66 ± 0.11) than for the flows which spent more time over the ocean (0.40 ± 0.05). When comparing <i>R</i>_sub-surf and the column-integrated submicron scattering fraction, <i>R</i>_sub-col, the correlation was similar, <i>r</i>² = 0.50, but <i>R</i>_sub-surf was generally less than <i>R</i>_sub-col, indicating more large particles contributing to light scattering at the surface, contrary to conditions over continents and for polluted continental transport over the ocean. In general, though, the marginal correlations indicate that the column optical properties are weakly correlated with the surface optical measurements. Thus, if it is desired to associate aerosol chemical/physical properties with their optical properties, it is best to use optical and chemical/physical measurements with both collected at the surface or both collected in the column

Ground-Based Network and Supersite Observations to Complement and Enrich EOS Research

Since 1997 NASA has been successfully launching a series of satellites - the Earth Observing System (EOS) - to intensively study, and gain a better understanding of, the Earth as an integrated system. Space-borne remote sensing observations, however, are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. Through numerous participations, particularly but not limited to the EOS remote-sensing/retrieval and validation projects over the years, NASA/GSFC has developed and continuously refined ground-based networks and mobile observatories that proved to be vital in providing high temporal measurements, which complement and enrich the satellite observations. These are: the AERO NET (AErosol RObotic NETwork) a federation of ground-based globally distributed network of spectral sun-sky photometers; the MPLNET (Micro-Pulse Lidar NETwork, a similarly organized network of micro-pulse lidar systems measuring aerosol and cloud vertical structure continuously; and the SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere, mobile observatories, a suite of spectral radiometers and in-situ probes acquiring supersite measurements. Most MPLNET sites are collocated with those of AERONET, and both networks always support the deployment of SMART-COMMIT worldwide. These data products follow the data structure of EOS conventions: Level-0, instrument archived raw data; Level-1 (or 1.5), real-time data with no (or limited) quality assurance; Level-2, not real high temporal and spectral resolutions. In this talk, we will present NASA/GSFC groundbased facilities, serving as network or supersite observations, which have been playing key roles in major international research projects over diverse aerosol regimes to complement and enrich the EOS scientific research

Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study

Standard network meta‐analysis and indirect comparisons combine aggregate data from multiple studies on treatments of interest, assuming that any factors that interact with treatment effects (effect modifiers) are balanced across populations. Population adjustment methods such as multilevel network meta‐regression (ML‐NMR), matching‐adjusted indirect comparison (MAIC), and simulated treatment comparison (STC) relax this assumption using individual patient data from one or more studies, and are becoming increasingly prevalent in health technology appraisals and the applied literature. Motivated by an applied example and two recent reviews of applications, we undertook an extensive simulation study to assess the performance of these methods in a range of scenarios under various failures of assumptions. We investigated the impact of varying sample size, missing effect modifiers, strength of effect modification and validity of the shared effect modifier assumption, validity of extrapolation and varying between‐study overlap, and different covariate distributions and correlations. ML‐NMR and STC performed similarly, eliminating bias when the requisite assumptions were met. Serious concerns are raised for MAIC, which performed poorly in nearly all simulation scenarios and may even increase bias compared with standard indirect comparisons. All methods incur bias when an effect modifier is missing, highlighting the necessity of careful selection of potential effect modifiers prior to analysis. When all effect modifiers are included, ML‐NMR and STC are robust techniques for population adjustment. ML‐NMR offers additional advantages over MAIC and STC, including extending to larger treatment networks and producing estimates in any target population, making this an attractive choice in a variety of scenarios

Effects of a 6-week Low-Carbohydrate High-Fat Diet on Lipid Profiles in Competitive Recreational Distance Runners

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Effects of a Low Carbohydrate Diet Versus a High Carbohydrate Diet on 5-km Running Performance

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Science lives: School choices and ‘natural tendencies’

An analysis of 12 semi-structured interviews with university-based scientists and non-scientists illustrates their life journeys towards, or away from, science and the strengths and impact of life occurrences leading them to choose science or non-science professions. We have adopted narrative approaches and used Mezirow's transformative learning theory framework. The areas of discussion from the result have stressed on three main categories that include ‘smooth transition’, ‘incremental wavering transition' and ‘transformative transition’. The article concludes by discussing the key influences that shaped initial attitudes and direction in these people through natural inclination, environmental inspirations and perceptions of science