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ABSTRACTFilmmakers use various cinematic techniques in an effort to guide attention to certain aspects of these events. The present study was conducted to investigate how framing and editing can guide viewers’ attention toward character actions during event segmentation. Participants watched and segmented a movie that simultaneously showed two actors engaged in two related activities. Participants watched one of three versions of the movie: Static center version that did not foreground any character; Static off-center version that foregrounding one of the characters, and an edited version with a mix of shots that foregrounding both characters. Participants engaged in an event partonomy task in which they were asked to identify the boundaries between the events that were depicted in the movie. After watching the movie, they were asked to recall the events. The results showed converging evidence between the event segmentation and recall data, which both indicated that cinematic devices affect the perception and memory of the event structure depicted in the film.

Starting in late 2013, the Northeast (NE) Pacific Ocean experienced anomalously warm sea surface temperatures (SSTs) that persisted for over 2 years. This marine heatwave, known as “the Blob,” produced many devastating ecological impacts with socioeconomic implications for coastal communities. The warm waters observed during the NE Pacific 2013/2016 marine heatwave altered the surface energy balance and disrupted ocean–atmosphere interactions in the region. In principle, ocean–atmosphere interactions following the formation of the marine heatwave could have perpetuated warm SSTs through a positive SST‐cloud feedback. The actual situation was more complicated. While reanalysis data show a decrease in boundary layer cloud fraction and an increase in downward shortwave radiative flux at the surface coincident with warm SSTs, this was accompanied by an increase in longwave radiative fluxes at the surface, as well as an increase in sensible and latent heat fluxes out of the ocean mixed layer. The result is a small negative net heat flux anomaly (compared to the anomalies of the individual terms contributing to the net heat flux). This provides new information about the midlatitude ocean–atmosphere system while it was in a perturbed state. More specifically, a mixed layer heat budget reveals that anomalies in both the atmospheric and oceanic processes offset each other such that the anomalously warm SSTs persisted for multiple years. The results show how the atmosphere–ocean system in the NE Pacific is able to maintain itself in an anomalous state for an extended period of time. During the 2013–2016 NE Pacific marine heatwave, a decrease in low cloud fraction and increase in surface radiative fluxes were observedConcurrently, anomalous turbulent fluxes and ocean processes offset a positive SST‐cloud feedback to maintain high SST anomaliesA balance of anomalous processes allows the atmosphere–ocean system in the NE Pacific to maintain an anomalous state for multiple years

Atmospheric reanalyses are valuable tools for studying the atmosphere, as they provide temporally and spatially complete coverage of atmospheric variables. However, some regions are susceptible to large biases in reanalysis products due to the scarce data available to assimilate into the reanalyses. Consequently, evaluation of reanalyses using available measurements is essential for quantifying regional errors. Here we use NASA's CERES satellite estimates to evaluate surface radiative fluxes and total cloud fraction in the Northeast Pacific from five reanalysis products—ERA‐Interim, MERRA2, JRA‐55, NCEP2, and CFSR—from years 2001 to 2015. Results show that biases of surface incident shortwave radiative flux in reanalyses compared to satellite estimates range from 3.8 (CFSR) to 21.2 Wm‐2 (NCEP2), with significant biases in JRA‐55 and NCEP2. Mean surface downward longwave radiative flux in the reanalysis products is biased by −8.9 (MERRA2) to 3.9 Wm−2(JRA‐55), with significant biases in MERRA2 and NCEP2. Errors in the surface radiative fluxes are partially linked to differences in total cloud fraction in the satellite estimates and reanalyses, which show significant negative biases ranging from −8% (CFSR) to −21.7% (NCEP2). There is not one reanalysis that outperforms the rest in the NE Pacific. The most appropriate data set depends on the variables of interest, subregion of the NE Pacific being studied, time period of interest, and whether the reanalysis data will be used to study long‐term or short‐term climate processes. Using the errors presented for each reanalysis data set can help guide appropriate use and bound uncertainty for the five reanalysis products analyzed. An evaluation of radiative fluxes and total cloud fraction from five reanalysis products is performed using CERES EBAF satellite estimatesShortwave radiative flux is mostly overestimated in reanalysis data sets, while longwave radiative flux has both negative and positive biases, depending on the reanalysisThere is no gold standard reanalysis—the most appropriate data set depends on variables, time period, and subregion of interest

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR‐E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle‐ and high‐altitude topped clouds agrees well between MISR retrievals and the MISR‐simulated output, with distributions of middle‐ and high‐topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low‐topped clouds between MISR retrievals and MISR‐simulated output that are due to differences in the detection of low‐level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low‐altitude cloud cover. The MISR‐simulated and MISR‐retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure. MISR‐simulated cloud top heights are derived from CloudSat/CALIPSO‐retrieved visible extinction profiles and compared with MISR retrievalsMISR‐simulated cloud top heights are in good agreement with MISR retrievals, and middle‐ and high‐topped clouds agree to within 5% cloud areaLarge uncertainties remain in low‐topped and total cloud area due to differences in detection of subpixel‐scale clouds

Hepatic steatosis is one complication patients may experience following clinical islet transplantation (CIT), yet the cause and consequences of this are poorly understood. The purpose of this case-control study was to examine the relationship between hepatic steatosis, metabolic parameters and graft function in an Albertan cohort of CIT recipients. Hepatic steatosis was detected by magnetic resonance imaging (MRI) in n = 10 cases age-matched with n=10 MRI-negative controls. Progression/regression of steatosis was determined by ultrasound (US) in cases. Hepatic steatosis first appeared 2.8 ± 2.2 (mean ± SD) years post-CIT, and lasted approximately 4.6 ± 2.0 years. In five cases steatosis resolved, with recurrence in two cases during the follow-up period (8.5 ± 3.2 years). No evidence of CIT causing deleterious effects on long-term liver function or graft outcome was observed.

The article discusses climate change in its scientific context and from the perspective of evangelical Christians. The distinction between predicting weather and climate, which involves mathematical models of initial conditions and boundary conditions respectively, is mentioned. Indicators of a warming climate are noted. The greenhouse effect, natural variations in carbon dioxide or greenhouse gas concentrations, and the effect of human activities on climate are discussed. The Christian response to global warming and climate change is discussed in the general categories of Cock-eyed optimists, End-time militants, Denialists, Creation care proponents, and Social justice advocates.

Immunosuppression with sirolimus and low-dose tacrolimus has facilitated successful clinical islet transplantation (CIT). Because the long-term effects on the kidney are unknown and immunosuppressant drugs can be nephrotoxic, CIT is currently restricted to patients with preserved renal function or a functioning renal transplant. The impact of CIT on the native kidney of islet-alone recipients was assessed with magnetic resonance imaging (MRI). After successful CIT, MRI revealed perinephric edema (PNE) in 10 of 30 recipients. PNE was associated with a mild degree of renal impairment but was not associated with preexisting diabetic nephropathy, albuminuria, microscopic hematuria, graft function, or other clinical and metabolic parameters. The presence of PNE on MRI after CIT seems to be a common but benign finding, most likely an adverse effect of sirolimus. Although this novel observation does not seem to be of concern, further studies are required to examine the long-term impact of CIT and immunosuppression on renal function.

The interaction of the Aretic winter aerosol (Arctic haze) with solar radiation produces changes in the radiation field that result in the enhancement of scattering and absorption processes which alter the energy balance and solar energy distribution in the Arctic atmosphere-surface system. During the second Arctic Gas and Aerosols Sampling Project (AGASP II) field experiment, we measured radiation parameters using the NOAA WP-3D research aircraft as a platform. State-of-the-art instrumentation was used to measure in situ the absorption of solar radiation by the Arctic atmosphere during severe haze events. Simultaneously with the absorption measurements, we determined optical depths, and total, direct, and scattered radiation fields. All optical measurements were made at spectral bands centered at 412, 500, 675, and 778 nm and with a bandpass of 10 nm. With this selection of spectral regions we concentrated on the measurement of the radiative effects of the aerosol excluding most of the contributions by the gaseous components of the atmosphere. An additional measurement performed during these experiments was the determination of total solar spectrum fluxes. The experimentally determined parameters were used to define an aerosol model that was employed to deduce the absorption by the aerosols over the full solar spectrum and to calculate atmospheric heating rate profiles. The analyses summarized above allowed us to deduce the magnitude of the change in some important parameters. For example, we found changes in instantaneous heating rate of up to about 0.6 K/day. Besides the increased absorption (30 to 40%) and scattering of radiation by the atmosphere, the haze reduces the surface absorption of solar energy by 6 to 10% and the effective planetary albedo over ice surfaces by 3 to 6%. The vertical distribution of the absorbing aerosol is inferred from the flux measurements. Values for the specific absorption of carbon are found to be around 6 m2/g for externally mixed aerosol and about 11.7 m2/g for internally mixed aerosol. A complete study of the radiative effects of the Arctic haze should include infrared measurements and calculations as well as physics of the ice, snow, and water surfaces.

Recent measurements of the single-scattering albedo ω˜_0 of tropospheric aerosols indicate the presence of a strongly absorbing material which has tentatively been identified as graphitic carbon (soot). Theoretical calculations, based on several different models of the way in which soot might be mixed with other aerosol materials, show that a minimum of 20% soot by volume is necessary to achieve the observed urban value of ω˜_0 = 0.6. Rural values of the order of 0.8 can be accounted for with 1–5% soot by volume. These same values of ω˜_0 can be produced by similar amounts of the iron oxide magnetite, which is shown to be virtually indistinguishable from soot by optical measurements performed on bulk samples. Calculations of phase functions for various mixtures of soot also indicate the difficulty of determining aerosol composition by optical scattering techniques. The climatic effects of these absorbing aeorosols are computed using a simple one-layer model, and the results suggest that heating rates in urban pollution layers may be of the order of 4 K/day.

AbstractPyranometers have been used for many years to measure broadband surface incoming solar irradiance, data that is necessary for surface energy budget, cloud forcing, and satellite validation research. Because such measurements are made at a specific location, it is unclear how representative they may be of a larger area. This study attempts to determine a reasonable spacing between measurement sites for such research by computing the correlation, and standard deviation from perfect correlation, between simultaneous measurements of incoming solar irradiance for a network of surface measurement sites covering a 75 km × 75 km area. Using 1-min data collected from this network of 11 sites during the NASA First ISSCP Radiation Experiment/Surface Radiation Budget Project temporal averages were calculated. The correlation between any two of these sites was determined by comparing simultaneous measurement averages for the 55 possible combinations of site pairs, along with the distances between them. In an attempt to remove the effect of the diurnal cycle, thus leaving clouds as the primary influence on correlation of the radiation field, model results for a clear day were used to normalize measured irradiances and correlations were again calculated.For individual days, the correlation between sites varied widely, depending primarily on the type of cloud cover the region experienced that day. Removal of the diurnal cycle, as expected, significantly decreased these correlation values. Comparisons using the continuous experiment records from 13 October through 2 November 1986, however, show that a relatively high degree of correlation existed with or without the diurnal cycle removed. Plotting these correlation coefficients versus the distance between sites, the expected trend for a decrease in correlation with increasing distance is observed. Results also confirm that, whether using the complete record for the duration of the experiment or by individual day, the correlation between site station pairs increases with increasing averaging times. Finally, the standard deviation from perfect correlation suggests a predictive relationship within about 6 of clear-sky irradiance for daily averages at a distance of 75 km. Thus, a spacing of 150 km between measurement sites seems reasonable for studies of midlatitude frontal weather regimes using daily averages over periods of weeks or more.

We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high‐pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model‐simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state‐dependent. Frontal conditions in the model do not produce enough thick cloud, while fair‐weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias. Models generally struggle to simulate clouds. Identifying the processes that cause errors is an important step toward improving them. We define a set of weather patterns for a region in the Great Plains that represent different physical processes and evaluate a climate model's cloud occurrence for each of those patterns. The model underpredicts cirrus clouds for all patterns. For thick clouds, however, the model overpredicts during fair‐weather conditions and underpredicts during stormy conditions. These errors tend to balance each other out. When the model resolution is improved, it does a better job of predicting thick clouds for most weather patterns, but now, the errors no longer balance each other. The result is that the model with better resolution has a worse overall prediction of thick clouds, despite better predictions for most individual patterns. Evaluating models by pattern, rather than just the overall total, helps to identify when there are underlying improvements that might be missed otherwise. Doing so may be valuable for future efforts toward improving the simulation of clouds in models. Clustering defines a set of atmospheric states for the great plains that are valuable tools for evaluation of model cloud occurrenceThe NOAA/GFDL AM3 model does not produce enough cirrus but has counterbalancing errors in thick cloud occurrenceIncreasing model horizontal resolution improves state cloud properties but removes counterbalancing errors and increases the overall bias