351 research outputs found
Multiple Equilibria in a Single-Column Model of the Tropical Atmosphere
A single-column model run under the weak temperature gradient approximation,
a parameterization of large-scale dynamics appropriate for the tropical
atmosphere, is shown to have multiple stable equilibria. Under conditions
permitting persistent deep convection, the model has a statistically steady
state in which such convection occurs, as well as an extremely dry state in
which convection does not occur. Which state is reached depends on the initial
moisture profile.Comment: Submitted to Geophysical Research Letter
Trimodal cloudiness and tropical stable layers in simulations of radiative convective equilibrium
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95176/1/grl24304.pd
Pregnancy rate in dairy cows treated with human chorionic gonadotropin five days after insemination
This study tested whether the administration of hCG five days after insemination increased progesterone concentration and pregnancy rate (PR) in dairy cows. A total of 989 lactating Holstein cows with different parity and number of prior services wereused. Cows were inseminated after overt estrus or at a fixed-time. Five days post-insemination, cows were randomly assigned to two treatment groups: hCG (n=482), which received 3500 IU of hCG by intramuscular injection; and the control group (n=507), which did not receive any treatment. Pregnancy was diagnosed by ultrasound on day 30 post-insemination, and gestation was confirmed on day 60 post-insemination by rectal palpation. In 15 cows from each treatment group, plasma progesterone concentration was determined on days 5, 11, and 15 post-insemination. Pregnancy rate was analysed using logistic regression. Variations in progesterone concentration between treatments were tested by ANOVA for repeated measurements. Progesterone concentration was higher on days 11 and 15 in cows treated with hCG, compared to the control group (P<0.05). Treatment with hCG increased pregnancy rate (47.5 vs. 37.4%. Odds ratio 1.3; P<0.05). No interaction was observed between treatment and body condition, prior services, milk production, parity, or insemination type (overt estrus or fixed time). Treatment with hCG did not reduce pregnancy losses between day 30 and 60 post-insemination (P>0.1). We conclude that injection of hCG five days after insemination increased progesterone concentration and pregnancy rate in dairy cows
Observing convective aggregation
Convective self-aggregation, the spontaneous organization of initially scattered convection into isolated convective clusters despite spatially homogeneous boundary conditions and forcing, was first recognized and studied in idealized numerical simulations. While there is a rich history of observational work on convective clustering and organization, there have been only a few studies that have analyzed observations to look specifically for processes related to self-aggregation in models. Here we review observational work in both of these categories and motivate the need for more of this work. We acknowledge that self-aggregation may appear to be far-removed from observed convective organization in terms of time scales, initial conditions, initiation processes, and mean state extremes, but we argue that these differences vary greatly across the diverse range of model simulations in the literature and that these comparisons are already offering important insights into real tropical phenomena. Some preliminary new findings are presented, including results showing that a self-aggregation simulation with square geometry has too broad a distribution of humidity and is too dry in the driest regions when compared with radiosonde records from Nauru, while an elongated channel simulation has realistic representations of atmospheric humidity and its variability. We discuss recent work increasing our understanding of how organized convection and climate change may interact, and how model discrepancies related to this question are prompting interest in observational comparisons. We also propose possible future directions for observational work related to convective aggregation, including novel satellite approaches and a ground-based observational network
Strategies for incorporating patient-reported outcomes in the care of people with chronic kidney disease (PRO kidney): a protocol for a realist synthesis
Background: Patient-reported outcomes and experience measures (jointly referred to here as PROs) are internationally recognized as a means for patients to provide information about their quality of life, symptoms, and experiences with care. Although increasingly recognized as key to improving the quality of healthcare at individual (e.g., patients, caregivers, and providers) and aggregate (e.g., government, policy/system-wide decision-making) levels, there are important knowledge gaps in our understanding of how PROs are, and can be, used across different settings, particularly in nephrology to enhance person-centered care. This knowledge is needed for developing strategies to guide optimal use of PROs in nephrology care. Currently, no strategies exist. The purpose of this review is to address this knowledge gap by answering the following realist question: How can PROs be used to enhance person centered nephrology care, both at individual and aggregate levels?
Methodology: Realist synthesis is an explanatory approach to data synthesis that aims to explain how context and mechanisms influence the outcome of an intervention. An initial program theory will be developed through the systematic search of the published literature in bibliographic databases (Ovid MEDLINE, Ovid Embase, EBSCOhost CINAHL, Web of Science, and Scopus) on existing theories explaining how PROs are used in healthcare settings. This initial program theory will then be tested and refined through the process of realist synthesis, using context-mechanism-outcome configurations. A kidney-specific program theory will then be created to address the utilization of PROs in nephrology across individual and aggregate levels to augment person-centered care. Searching will be iterative and refined as data is extracted and analyzed using a pilot testedcontext + mechanism = outcome heuristic. Throughout, we will consult methodological experts, research team practitioners, and the Patient Advisory Committee to help refine the theories. Last, we will develop and disseminate knowledge translation products widely to knowledge user groups.
Discussion: The utilization of PROs remains a challenge in nephrology. The findings from this synthesis will provide a framework to guide both policy makers and practitioners on how to enhance person-centered care through successful utilization of PROs across individual and aggregate levels in nephrology
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Evaluation of the model representation of the evolution of convective systems using satellite observations of outgoing longwave radiation
We introduce a technique for assessing the diurnal development of convective storm systems based on outgoing longwave radiation fields. Using the size distribution of the storms measured from a series of images, we generate an array in the lengthscale-time domain based on the standard
score statistic. It demonstrates succinctly the size evolution of storms as well as the dissipation kinematics. It also provides evidence related to the temperature evolution of the cloud tops. We apply this approach to a test case comparing observations made by the Geostationary Earth Radiation Budget instrument to output from the Met Office Unified Model run at two resolutions. The 12km resolution model produces peak convective activity on all lengthscales significantly earlier in the day than shown by the observations and no evidence for storms growing in size. The 4km resolution model shows realistic timing and growth evolution although the dissipation mechanism still differs from the observed data
Designing Ecosystems of Intelligence from First Principles
This white paper lays out a vision of research and development in the field
of artificial intelligence for the next decade (and beyond). Its denouement is
a cyber-physical ecosystem of natural and synthetic sense-making, in which
humans are integral participants -- what we call ''shared intelligence''. This
vision is premised on active inference, a formulation of adaptive behavior that
can be read as a physics of intelligence, and which inherits from the physics
of self-organization. In this context, we understand intelligence as the
capacity to accumulate evidence for a generative model of one's sensed world --
also known as self-evidencing. Formally, this corresponds to maximizing
(Bayesian) model evidence, via belief updating over several scales: i.e.,
inference, learning, and model selection. Operationally, this self-evidencing
can be realized via (variational) message passing or belief propagation on a
factor graph. Crucially, active inference foregrounds an existential imperative
of intelligent systems; namely, curiosity or the resolution of uncertainty.
This same imperative underwrites belief sharing in ensembles of agents, in
which certain aspects (i.e., factors) of each agent's generative world model
provide a common ground or frame of reference. Active inference plays a
foundational role in this ecology of belief sharing -- leading to a formal
account of collective intelligence that rests on shared narratives and goals.
We also consider the kinds of communication protocols that must be developed to
enable such an ecosystem of intelligences and motivate the development of a
shared hyper-spatial modeling language and transaction protocol, as a first --
and key -- step towards such an ecology.Comment: 23+18 pages, one figure, one six page appendi
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Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions
As part of an international intercomparison project, a set of single column models (SCMs) and cloud-resolving models (CRMs) are run under the weak temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics.
CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation.
When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations
Simulations of the 2004 North American Monsoon: NAMAP2
The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.open131
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