Observed Tightening of Tropical Ascent in Recent Decades and Linkage to Regional Precipitation Changes

Climate models predict that the tropical ascending region should tighten under global warming, but observational quantification of the tightening rate is limited. Here we show that the observed spatial extent of the relatively moist, rainy and cloudy regions in the tropics associated with large‐scale ascent has been decreasing at a rate of −1%/decade (−5%/K) from 1979 to 2016, resulting from combined effects of interdecadal variability and anthropogenic forcings, with the former contributing more than the latter. The tightening of tropical ascent is associated with an increase in the occurrence frequency of extremely strong ascent, leading to an increase in the average precipitation rate in the top 1% of monthly rainfall in the tropics. At the margins of the convective zones such as the Southeast Amazonia region, the contraction of large‐scale ascent is related to a long‐term drying trend about −3.2%/decade in the past 38 years

The vertical distribution of ozone in the mesosphere and lower thermosphere

An assessment is made of the ability of current theory to explain the phenomenology of upper atmospheric ozone as revealed by the sizeable body of measurements presently available. The chemistry of ozone in the mesosphere and lower thermosphere is closely coupled to the chemistries of other oxygen/hydrogen-containing species, which must be considered concurrently. To provide insight into the sensitivity of model calculations to the choice of values used for key chemical rate constants and climatological parameters, simple analytical expressions for ozone are derived for those situations when it is in photochemical steady state, the mesosphere during daylight hours and the lower thermosphere throughout the full diurnal period. The model is found to reproduce the detailed Aladdin 74 rocket measurements of ozone from 50 to 95 km, numerous other measurements of mid-latitude ozone in the lower mesosphere, the secondary maximum in the ozone vertical distribution at the mesopause, and the diurnal variability of ozone seen in the radio measurements of Wilson and Schwartz (1981) and other observations. The agreement with the Aladdin 74 data results from adjusting some key parameters within the uncertainties of laboratory measurements or known natural climatological variability. The variety of mid-latitude observations can be understood in terms of the estimated variability of environmental factors: diurnal, seasonal, and solar cycles in the solar illumination; the abundance of water vapor; and the details of the thermal profile of the atmosphere. The ozone secondary maximum results from the onset of the coupling between active-hydrogen and active-oxygen chemistry and its observed variability may be a consequence of secular changes in mesopause dynamics. Above ∼95 km, ozone observations are consistently higher than model results and cannot be accounted for by the set of reactions currently included in the model

GPU/CPU Performance of Image Processing Tasks for use in the CAM 2 System

Over the past several years, graphics processing units (GPU) have increasingly been viewed as the future of image processing engines. Currently, the Continuous Analysis of Many CAMeras (CAM2) project performs its processing on CPUs, which will potentially be more costly as the system scales to service more users. This study seeks to analyze the performance gains of GPU processing and evaluate the advantage of supporting GPU-accelerated analysis for CAM2 users. The platform for comparing the CPU and GPU performance has been the NVIDIA Jetson TK1. The target hardware implementation is an Amazon cloud instance, where final cost analysis will be performed. It is expected that the GPU will out perform its CPU counterpart in some image processing applications. The degree to which it outperforms the CPU is subject to a number of factors. So far, tests have shown the expected speedup (and lackthereof) in basic mathematical operations performed on the GPU, indicative of the expected success of the integration into the CAM2 system

A Statistical Estimation of the Occurrence of Extraterrestrial Intelligence in the Milky Way Galaxy

In the field of astrobiology, the precise location, prevalence, and age of potential extraterrestrial intelligence (ETI) have not been explicitly explored. Here, we address these inquiries using an empirical galactic simulation model to analyze the spatial–temporal variations and the prevalence of potential ETI within the Galaxy. This model estimates the occurrence of ETI, providing guidance on where to look for intelligent life in the Search for ETI (SETI) with a set of criteria, including well-established astrophysical properties of the Milky Way. Further, typically overlooked factors such as the process of abiogenesis, different evolutionary timescales, and potential self-annihilation are incorporated to explore the growth propensity of ETI. We examine three major parameters: (1) the likelihood rate of abiogenesis (λ_A); (2) evolutionary timescales (T_(evo)); and (3) probability of self-annihilation of complex life (P_(ann)). We found P_(ann) to be the most influential parameter determining the quantity and age of galactic intelligent life. Our model simulation also identified a peak location for ETI at an annular region approximately 4 kpc from the galactic center around 8 billion years (Gyrs), with complex life decreasing temporally and spatially from the peak point, asserting a high likelihood of intelligent life in the galactic inner disk. The simulated age distributions also suggest that most of the intelligent life in our galaxy are young, thus making observation or detection difficult

Digital Quantum Simulation of the Statistical Mechanics of a Frustrated Magnet

Many problems of interest in physics, chemistry and computer science are equivalent to problems defined on systems of interacting spins. However, most such problems require computational resources that are out of reach with classical computers. A promising solution to overcome this challenge is quantum simulation. Several 'analogue' quantum simulations of interacting spin systems have been realized experimentally, where ground states were prepared using adiabatic techniques. Here we report a 'digital' quantum simulation of thermal states; a three-spin frustrated magnet was simulated using a nuclear magnetic resonance quantum information processor, and we were able to explore the phase diagram of the system at any simulated temperature and external field. These results help to identify the challenges for performing quantum simulations of physical systems at finite temperatures, and suggest methods that may be useful in simulating thermal open quantum systems.Chemistry and Chemical Biolog

Radiative absorption enhancement of dust mixed with anthropogenic pollution over East Asia

The particle mixing state plays a significant yet poorly quantified role in aerosol radiative forcing, especially for the mixing of dust (mineral absorbing) and anthropogenic pollution (black carbon absorbing) over East Asia. We have investigated the absorption enhancement of mixed-type aerosols over East Asia by using the Aerosol Robotic Network observations and radiative transfer model calculations. The mixed-type aerosols exhibit significantly enhanced absorbing ability than the corresponding unmixed dust and anthropogenic aerosols, as revealed in the spectral behavior of absorbing aerosol optical depth, single scattering albedo, and imaginary refractive index. The aerosol radiative efficiencies for the dust, mixed-type, and anthropogenic aerosols are −101.0, −112.9, and −98.3 Wm⁻²τ⁻¹ at the bottom of the atmosphere (BOA); −42.3, −22.5, and −39.8 Wm⁻²τ⁻¹ at the top of the atmosphere (TOA); and 58.7, 90.3, and 58.5 Wm⁻²τ⁻¹ in the atmosphere (ATM), respectively. The BOA cooling and ATM heating efficiencies of the mixed-type aerosols are significantly higher than those of the unmixed aerosol types over the East Asia region, resulting in atmospheric stabilization. In addition, the mixed-type aerosols correspond to a lower TOA cooling efficiency, indicating that the cooling effect by the corresponding individual aerosol components is partially counteracted. We conclude that the interaction between dust and anthropogenic pollution not only represents a viable aerosol formation pathway but also results in unfavorable dispersion conditions, both exacerbating the regional air pollution in East Asia. Our results highlight the necessity to accurately account for the mixing state of aerosols in atmospheric models over East Asia in order to better understand the formation mechanism for regional air pollution and to assess its impacts on human health, weather, and climate

Impact of Cloud Ice Particle Size Uncertainty in a Climate Model and Implications for Future Satellite Missions

Ice particle size is pivotal to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R_(ei)) observation on the global scale to constrain its representation in climate models. In support of future mission design, here we present a modeling assessment of the sensitivity of climate simulations to R_(ei) and quantify the impact of the proposed mission concept on reducing the uncertainty in climate sensitivity. We perturb the parameters pertaining to ice fall speed parameter and R_(ei) in radiation scheme, respectively, in National Center for Atmospheric Research CESM1 model with a slab ocean configuration. The model sensitivity experiments show that a settling velocity increase due to a larger R_(ei) results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. A similar competition between longwave and shortwave cloud forcing changes also exists when perturbing R_(ei) in the radiation scheme. Linearity generally holds for the climate response for R_(ei) related parameters. When perturbing falling snow particle size (R_(es)) in a similar way, we find much less sensitivity of climate responses. Our quadrupling CO₂ experiments with different parameter settings reveal that R_(ei) and R_(es) can account for changes in climate sensitivity significantly from +12.3% to −6.2%. By reducing the uncertainty ranges of R_(ei) and R_(es) from a factor of 2 to ±25%, a future satellite mission under design is expected to improve the climate state simulations and reduce the climate sensitivity uncertainty pertaining to ice particle size by approximately 60%. Our results highlight the importance of better observational constraints on R_(ei) by satellite missions

Mass transport phenomena between bubbles and dissolved gases in liquids under reduced gravity conditions

The experimental and analytical work that was done to establish justification and feasibility for a shuttle middeck experiment involving mass transfer between a gas bubble and a liquid is described. The experiment involves the observation and measurement of the dissolution of an isolated immobile gas bubble of specified size and composition in a thermostatted solvent liquid of known concentration in the reduced gravity environment of earth orbit. Methods to generate and deploy the bubble were successful both in normal gravity using mutually buoyant fluids and under reduced gravity conditions in the NASA Lear Jet. Initialization of the experiment with a bubble of a prescribed size and composition in a liquid of known concentration was accomplished using the concept of unstable equilibrium. Subsequent bubble dissolution or growth is obtained by a step increase or decrease in the liquid pressure. A numerical model was developed which simulates the bubble dynamics and can be used to determine molecular parameters by comparison with the experimental data. The primary objective of the experiment is the elimination of convective effects that occur in normal gravity

Impact of Cloud Ice Particle Size Uncertainty in a Climate Model and Implications for Future Satellite Missions

Ice particle size is pivotal to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R_(ei)) observation on the global scale to constrain its representation in climate models. In support of future mission design, here we present a modeling assessment of the sensitivity of climate simulations to R_(ei) and quantify the impact of the proposed mission concept on reducing the uncertainty in climate sensitivity. We perturb the parameters pertaining to ice fall speed parameter and R_(ei) in radiation scheme, respectively, in National Center for Atmospheric Research CESM1 model with a slab ocean configuration. The model sensitivity experiments show that a settling velocity increase due to a larger R_(ei) results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. A similar competition between longwave and shortwave cloud forcing changes also exists when perturbing R_(ei) in the radiation scheme. Linearity generally holds for the climate response for R_(ei) related parameters. When perturbing falling snow particle size (R_(es)) in a similar way, we find much less sensitivity of climate responses. Our quadrupling CO₂ experiments with different parameter settings reveal that R_(ei) and R_(es) can account for changes in climate sensitivity significantly from +12.3% to −6.2%. By reducing the uncertainty ranges of R_(ei) and R_(es) from a factor of 2 to ±25%, a future satellite mission under design is expected to improve the climate state simulations and reduce the climate sensitivity uncertainty pertaining to ice particle size by approximately 60%. Our results highlight the importance of better observational constraints on R_(ei) by satellite missions