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Sea ice leads, or fractures account for a small proportion of the Arctic Ocean surface area, but play a critical role in the energy and moisture exchanges between the ocean and atmosphere. As the sea ice area and volume in the Arctic has declined over the past few decades, changes in sea ice leads have not been studied as extensively. A recently developed approach uses artificial intelligence (AI) and satellite thermal infrared window data to build a twenty-year archive of sea ice lead detects with Moderate Resolution Imaging Spectroradiometer (MODIS) and later, an archive from Visible Infrared Imaging Radiometer Suite (VIIRS). The results are now available and show significant improvement over previously published methods. The AI method results have higher detection rates and a high level detection agreement between MODIS and VIIRS. Analysis over the winter season from 2002–2003 through to the 2021–2022 archive reveals lead detections have a small decreasing trend in lead area that can be attributed to increasing cloud cover in the Arctic. This work reveals that leads are becoming increasingly difficult to detect rather than less likely to occur. Although the trend is small and on the same order of magnitude as the uncertainty, leads are likely increasing at a rate of 3700 km2 per year with a range of uncertainty of 3500 km2 after the impact of cloud cover changes are removed. [ABSTRACT FROM AUTHOR]

Background: Esophageal histology is critical for diagnosis and surveillance of disease activity in eosinophilic esophagitis (EoE). A validated noninvasive biomarker has not been identified. We aimed to determine the utility of blood and urine eosinophil‐associated proteins to diagnose EoE and predict esophageal eosinophilia. Methods: Blood and urine were collected from children undergoing endoscopy with biopsy. Absolute eosinophil count (AEC), plasma eosinophil‐derived neurotoxin (EDN), eosinophil cationic protein (ECP), major basic protein‐1 (MBP‐1), galectin‐10 (CLC/GAL‐10), Eotaxin‐2 and Eotaxin‐3, and urine osteopontin (OPN) and matrix metalloproteinase‐9 (MMP‐9) were determined. Differences were assessed between EoE and control, and with treatment response. The capacity to predict EoE diagnosis and esophageal eosinophil counts was assessed. Results: Of 183 specimens were collected from 56 EoE patients and 15 non‐EoE controls with symptoms of esophageal dysfunction; 33 EoE patients had paired pre‐ and post‐treatment specimens. Plasma (CLC/GAL‐10, ECP, EDN, Eotaxin‐3, MBP‐1) and urine (OPN) biomarkers were increased in EoE compared to control. A panel comprising CLC/GAL‐10, Eotaxin‐3, ECP, EDN, MBP‐1, and AEC was superior to AEC alone in distinguishing EoE from control. AEC, CLC/GAL‐10, ECP, and MBP‐1 were significantly decreased in patients with esophageal eosinophil counts <15/hpf in response to treatment. AEC, CLC/GAL‐10, ECP, EDN, OPN, and MBP‐1 each predicted esophageal eosinophil counts utilizing mixed models controlled for age, gender, treatment, and atopy; AEC combined with MBP‐1 best predicted the counts. Conclusions: We identified novel panels of eosinophil‐associated proteins that along with AEC are superior to AEC alone in distinguishing EoE from controls and predicting esophageal eosinophil counts. [ABSTRACT FROM AUTHOR]

Experimental and clinical data strongly support a role for the eosinophil in the pathogenesis of asthma, allergic and parasitic diseases, and hypereosinophilic syndromes, in addition to more recently identified immunomodulatory roles in shaping innate host defense, adaptive immunity, tissue repair/remodeling, and maintenance of normal tissue homeostasis. A seminal finding was the dependence of allergic airway inflammation on eosinophil-induced recruitment of Th2-polarized effector T-cells to the lung, providing a missing link between these innate immune effectors (eosinophils) and adaptive T-cell responses. Eosinophils come equipped with preformed enzymatic and nonenzymatic cationic proteins, stored in and selectively secreted from their large secondary (specific) granules. These proteins contribute to the functions of the eosinophil in airway inflammation, tissue damage, and remodeling in the asthmatic diathesis. Studies using eosinophil-deficient mouse models, including eosinophil-derived granule protein double knock-out mice (major basic protein-1/eosinophil peroxidase dual gene deletion) show that eosinophils are required for all major hallmarks of asthma pathophysiology: airway epithelial damage and hyperreactivity, and airway remodeling including smooth muscle hyperplasia and subepithelial fibrosis. Here we review key molecular aspects of these eosinophil-derived granule proteins in terms of structure-function relationships to advance understanding of their roles in eosinophil cell biology, molecular biology, and immunobiology in health and disease. [ABSTRACT FROM AUTHOR]

Thirty-one years of imager data from polar orbiting satellites are composited to produce a satellite climate data set of cloud amount for the Great Lakes region. A trend analysis indicates a slight decreasing trend in cloud cover over the region during this time period. The trend is significant and largest (~2% per decade) over the water bodies. A strong seasonal cycle of cloud cover is observed over both land and water surfaces. Winter cloud amounts are greater over the water bodies than land due to heat and moisture flux into the atmosphere. Late spring through early autumn cloud amounts are lower over the water bodies than land due to stabilization of the boundary layer by relatively cooler lake waters. The influence of the lakes on cloud cover also extends beyond their shores, affecting cloud cover and properties far down wind. Cloud amount composited by wind direction demonstrate that the increasing cloud amounts downwind of the lakes is greatest during autumn and winter. Cold air flows over relatively warm lakes in autumn and winter generate wind parallel convective cloud bands. The cloud properties of these wind parallel cloud bands over the lakes during winter are presented. [ABSTRACT FROM AUTHOR]

Ellis AK, Ackerman SJ, Crawford L, Du J, Bedi R, Denburg JA. Cord blood molecular biomarkers of eosinophilopoiesis: Kinetic analysis of GATA-1, MBP1 and IL-5Rα mRNA expression. Pediatr Allergy Immunol 2010: 21: 640–648. © 2010 John Wiley & Sons A/S Eosinophil/basophil (Eo/B) progenitor phenotype and function in cord blood (CB) are associated with atopic risk at birth and infant clinical outcomes. Molecular analyses of eosinophil–basophil differentiation events could identify clinically predictive biomarkers. To determine CB kinetic patterns of Eo/B lineage-associated gene expression (GATA-1, MBP1 and IL-5Rα) after IL-5 stimulation, CB non-adherent mononuclear cells were isolated from random fresh and frozen samples and incubated in the presence of recombinant human interleukin-5. Some underwent CD34+ positive selection using magnetic cell separation. At various time-points, mRNA expression of GATA-1, MBP1 and IL-5Rα (total transcripts) was determined utilizing multiplex quantitative polymerase chain reaction (Q-PCR). Relative expression levels of the IL-5Rα soluble vs. transmembrane isoforms were also analyzed. Stimulation of the non-adherent mononuclear cells with IL-5 resulted in early up-regulation of GATA-1, peaking at 48 h, followed by decreasing expression and down-regulation by 96 h. The CD34+ enriched population demonstrated an equivalent expression pattern ( r = 0.963, p = 0.0349). MBP1 mRNA expression [non-adherent mononuclear cells (NAMNCs) and CD34+ alike; r = 0.988, p = 0.012] was slowly up-regulated in response to IL-5, maximal at 96 h. Total IL-5Rα expression appeared stable over the time-course, mediated by differential expression of the soluble and transmembrane isoforms (i.e., initial increase in the transmembrane contribution followed by a predominance of the soluble isoform by 48–72 h). Multiplex Q-PCR analysis of mRNA from CB demonstrates expression of critical eosinophil-basophil lineage-specific events that are consistent with current understanding of eosinophil differentiation and maturation. The non-adherent mononuclear cell population provides a surrogate signal for the CD34+ progenitor population. [ABSTRACT FROM AUTHOR]

Arctic sea ice extent has decreased dramatically over the last 30 years, and this trend is expected to continue through the twenty-first century. Changes in sea ice extent impact cloud cover, which in turn influences the surface energy budget. Understanding cloud feedback mechanisms requires an accurate determination of cloud cover over the polar regions, which must be obtained from satellite-based measurements. The accuracy of cloud detection using observations from space varies with surface type, complicating any assessment of climate trends as well as the understanding of ice–albedo and cloud–radiative feedback mechanisms. To explore the implications of this dependence on measurement capability, cloud amounts from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared with those from the CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites in both daytime and nighttime during the time period from July 2006 to December 2008. MODIS is an imager that makes observations in the solar and infrared spectrum. The active sensors of CloudSat and CALIPSO, a radar and lidar, respectively, provide vertical cloud structures along a narrow curtain. Results clearly indicate that MODIS cloud mask products perform better over open water than over ice. Regional changes in cloud amount from CloudSat/CALIPSO and MODIS are categorized as a function of independent measurements of sea ice concentration (SIC) from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). As SIC increases from 10% to 90%, the mean cloud amounts from MODIS and CloudSat–CALIPSO both decrease; water that is more open is associated with increased cloud amount. However, this dependency on SIC is much stronger for MODIS than for CloudSat–CALIPSO, and is likely due to a low bias in MODIS cloud amount. The implications of this on the surface radiative energy budget using historical satellite measurements are discussed. The quantified ice–water difference in MODIS cloud detection can be used to adjust estimated trends in cloud amount in the presence of changing sea ice cover from an independent dataset. It was found that cloud amount trends in the Arctic might be in error by up to 2.7% per decade. The impact of these errors on the surface net cloud radiative effect (“forcing”) of the Arctic can be significant, as high as 8.5%. [ABSTRACT FROM AUTHOR]

The article presents an analysis of the methodology of the Cooperative Institute for Meteorological Satellite Studies (CIMSS), a federally funded research center in the U.S. It is stated that bibliometric methods were used to examine the success of the center's mission. The center helps in the examination of several publications, patterns in research, classification of topics and publishing venues. It focuses on satellite-related research in atmospheric and Earth system science.

Significant improvements have been made to the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask (MOD35 and MYD35) for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2-μm water vapor absorption band have been added as well as updates to the 3.9–12- and 11–12-μm cloud tests. More non-MODIS ancillary input data have been added. Land and sea surface temperature maps provide crucial information for mid- and low-level cloud detection and lessen dependence on ocean brightness temperature variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud versus clear-sky signals, where visible and near-infrared (NIR) reflectances are high, but infrared brightness temperatures are relatively warm. Day and night Arctic cloud frequency results are compared to those created by the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder-Extended (APP-X) algorithm. Day versus night sea surface temperatures derived from MODIS radiances and using only the MODIS cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions are shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions. Continuing validation activities are described in Part II of this paper. [ABSTRACT FROM AUTHOR]

A technique using the Geostationary Operational Environmental Satellite (GOES) sounder radiance data has been developed to improve detection of low clouds and fog just after sunrise. The technique is based on a simple difference method using the shortwave (3.7 μm) and longwave (11.0 μm) window bands in the infrared range of the spectrum. The time period just after sunrise is noted for the difficulty in being able to correctly identify low clouds and fog over land. For the GOES sounder cloud product this difficulty is a result of the visible reflectance of the low clouds falling below the “cloud” threshold over land. By requiring the difference between the 3.7- and the 11.0-μm bands to be greater than 5.0 K, successful discrimination of low clouds and fog is found 85% of the time for 21 cases from 14 September 2005 to 6 March 2006 over the GOES-12 sounder domain. For these 21 clear and cloudy cases the solar zenith angle ranged from 87° to 77°; however, the range of solar zenith angles for cloudy cases was from 85° to 77°. The success rate further improved to 95% (20 out of 21 cases) by including a difference threshold of 5.0 K between the 3.7- and 4.0-μm bands, requiring that the 11.0-μm band be greater than 260 K, and limiting the test to fields of view where the surface elevation is below 999 m. These final three limitations were needed to more successfully deal with cases involving snow cover and dead vegetation. To ensure that only the time period immediately after sunrise is included the solar zenith angle threshold for application of these tests is between 89° and 70°. [ABSTRACT FROM AUTHOR]

Early enhanced-V studies used 8-km ground-sampled distance and 30-min temporal-sampling Geostationary Operational Environmental Satellite (GOES) infrared (IR) imagery. In contrast, the ground-sampled distance of current satellite imagery is 1 km for low earth orbit (LEO) satellite IR imagery. This improved spatial resolution is used to detect and investigate quantitative parameters of the enhanced-V feature. One of the goals of this study is to use the 1-km-resolution LEO data to help understand the impact of higher-resolution GOES data (GOES-R) when it becomes available. A second goal is to use the LEO data available now to provide better severe storm information than GOES when it is available. This study investigates the enhanced-V feature observed with 1-km-resolution satellite imagery as an aid for severe weather warning forecasters by comparing with McCann’s enhanced-V study. Therefore, verification statistics such as the probability of detection, false alarm ratio, and critical success index were calculated. Additionally, the importance of upper-level winds to severe weather occurrence will be compared with that of the quantitative parameters of the enhanced-V feature. The main goal is to provide a basis for the development of an automated detection algorithm for enhanced-V features from the results in this study. Another goal is to examine daytime versus nighttime satellite overpass distributions with the enhanced-V feature. [ABSTRACT FROM AUTHOR]

During 2002 and 2003, surveys of introductory meteorology students were conducted at the University of Georgia and the University of Wisconsin—Madison. These surveys asked which one question about weather and climate each student would most like to have answered in the class, as well as other demographic and educational information. The more than 750 responses that were obtained ran the gamut of meteorology and were not overwhelmingly focused on any one topic, including severe weather. Results from the two universities are nearly identical, with the exception of a greater awareness of climate issues at Wisconsin. Several topics that are most commonly noted by students, such as weather forecasting and atmospheric optics, are given inadequate treatment in many introductory meteorology textbooks and classes. The results of the surveys suggest that an instructor could use students' first-day responses to this kind of question to shape a syllabus that would incorporate student interests, while retaining educational integrity. [ABSTRACT FROM AUTHOR]

In this study, we examined global treatment outcomes during 16 months of intensive, psychodynamic treatment for 77 inpatients suffering from treatment-refractory disorders. Hypotheses based on the phase model of treatment change (Howard, Lueger, Maling,&Martinovich, 1993; Howard, Moras, Brill, Martinovich,&Lutz, 1996) were supported in the study results. Diagnostic and Statistical Manual of Mental Disorders (4th ed.; American Psychiatric Association, 1994) Axis V scales assessing behavioral functioning demonstrated large and medium effect size change, whereas stable, enduring personality functioning assessed by psychoanalytic Rorschach scales and the Social Cognition and Object Relations Scale (Westen, 1995) for the Thematic Apperception Test (Murray, 1943) demonstrated small and medium effect size change. We also report assessment of reliable change index and clinical significance. The ecological validity of Rorschach measures is supported by significant validity coefficients (in the hypothesized directions) between implicit measures of personality functioning and behavioral ratings. [ABSTRACT FROM AUTHOR]

The present review is a comprehensive examination of the therapist''s personal attributes and in-session activities that positively influence the therapeutic alliance from a broad range of psychotherapy perspectives. Therapist''s personal attributes such as being flexible, honest, respectful, trustworthy, confident, warm, interested, and open were found to contribute positively to the alliance. Therapist techniques such as exploration, reflection, noting past therapy success, accurate interpretation, facilitating the expression of affect, and attending to the patient''s experience were also found to contribute positively to the alliance. This review reveals how these therapist personal qualities and techniques have a positive influence on the identification or repair of ruptures in the alliance. [Copyright &y& Elsevier]

Develops an interactive web-based program using Java for students taking an introductory course in weather and climate at the University of Wisconsin in Madison, Wisconsin. Use of visual-identification quizzes and exercises for students; List of applets used in teaching meteorology.

The Rorschach Mutuality of Autonomy Scale (MOA; Urist, 1977) and the Social Cognition and Object Relations Scale (SCORS; Westen,1995) have been shown to be reliable and valid measures of interpersonal functioning. Utilizing a sample of 57 outpatients with a Diagnostic and Statistical Manual of Mental Disorders (4th ed.; American Psychiatric Association, 1994) Axis II diagnosis, this study extends the findings of previous research demonstrating the reliability and convergent validity of each measure. Analyses focused on the convergent validity between the Rorschach MOA Scale and 8 SCORS variables (complexity, affect, emotional investment in relationships, emotional investment in values and morals, understanding of social causality, management of impulses/aggression, self-esteem, identity/coherence of self) ratings of Thematic Apperception Test (Murray, 1943) narratives. The conceptual nature and clinical utility of these findings are discussed in relation to psychological assessment. [ABSTRACT FROM AUTHOR]

Investigates the reliability and convergent and discriminant validity of the DSM-IV Global Assessment of Functioning Scale and two experimental DSM-IV axis V global rating scales, the Global Assessment of Relational Scale and the Social and Occupational Functioning Assessment Scale. Intraclass correlation coefficients; Factor structure of ratings.

Utilizing a collaborative therapeutic assessment (TA) model proposed by Finn and Tonsager (1997), we examined the interaction between therapeutic alliance and in-session process during the assessment phase of treatment. This study compares the utility of the TA model (n = 38) versus a traditional information gathering model (n = 90) of assessment. The results of this study indicate that the use of a TA model may decrease the number of patients who terminate treatment against medical advice. The Session Evaluation Questionnaire (Stiles & Snow, 1984), Combined Alliance Short Form (Hatcher & Barends, 1996), and Penn Helping Alliance Questionnaire-Revised (Barber & Crits-Christoph, 1996) can reliably measure the patient's experience of the assessment. The psychological assessment process may impact the patient's experience of assessment feedback and aid in the development of a therapeutic alliance. The therapeutic alliance developed during the assessment was found to be related to alliance early in psychotherapy. We discuss the theoretical, clinical, and research implications of these findings. [ABSTRACT FROM AUTHOR]

This study investigates the extent to which the number of psychotherapy sessions attended is predicted by the Rorschach Mutuality of Autonomy Scale (MOA; Urist, 1977), Holt primary (A1) and secondary (A2) process aggression variables (Holt, 1977), and ratings of Thematic Apperception Test (TAT) narratives using Westen's (1995) eight Social Cognition and Object Relations Scale (SCORS) variables (complexity of representation of people, affective quality of representations, emotional investment in relationships, emotional investment in values and moral standards, understanding of social causality, experience and management of aggressive impulses, self-esteem, identity and coherence of self). Seventy-six patients with a DSM-IV Axis H diagnosis participated in this study. Two separate stepwise regression analyses (one for Rorschach variables, N = 76, and one for the SCORS ([TAT]) variables, n = 63) indicated that the Rorschach MOA PATH score (sum of scale points 5, 6, and 7; positive), as well as two individual SCORS variables (in order of relative magnitude, affective quality of representations, negative, and emotional investment in relationships, positive), were predictive of the number of psychotherapy sessions attended by patients. The conceptual nature and clinical utility of these variables are discussed in relation to the termination and continuation of psychodynamic psychotherapy. (Bulletin of the Menninger Clinic, 64[3], 3 86-408) [ABSTRACT FROM AUTHOR]

Investigates the relationship between high-spectral resolution infrared radiances (IR) and the microphysical properties of cirrus clouds. Calculations of IR radiances using radiosonde measurements of the atmospheric state; Sensitivity of cloud forcing to ice-particle size, ice-water path, and cloud altitude; Use of discrete ordinate radiative transfer algorithm.

Despite accounting for a small fraction of the surface area in the Arctic, long and narrow sea ice fractures, known as "leads", play a critical role in the energy flux between the ocean and atmosphere. As the volume of sea ice in the Arctic has declined over the past few decades, it is increasingly important to monitor the corresponding changes in sea ice leads. A novel approach has been developed using artificial intelligence (AI) to detect sea ice leads using satellite thermal infrared window data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS). In this new approach, a particular type of convolutional neural network, a U-Net, replaces a series of conventional image processing tests from our legacy algorithm. Results show the new approach has a high detection accuracy with F1 Scores on the order of 0.7. Compared to the legacy algorithm, the new algorithm shows improvement, with more true positives, fewer false positives, fewer false negatives, and better agreement between satellite instruments. [ABSTRACT FROM AUTHOR]

Human sialic acid-binding immunoglobulin-like lectins (Siglecs) are expressed on subsets of immune cells. Siglec-8 is an immune inhibitory Siglec on eosinophils and mast cells, which are effectors in allergic disorders including eosinophilic esophagitis. Inhibition occurs when Siglec-8 is crosslinked by multivalent Siglec ligands in target tissues. Previously we discovered a high-affinity Siglec-8 sialoglycan ligand on human airways composed of terminally sialylated keratan sulfate chains carried on a single protein, DMBT1. Here we extend that approach to another allergic inflammatory target tissue, human esophagus. Lectin overlay histochemistry revealed that Siglec-8 ligands are expressed predominantly by esophageal submucosal glands, and are densely packed in submucosal ducts leading to the lumen. Expression is tissue-specific; esophageal glands express Siglec-8 ligand whereas nearby gastric glands do not. Extraction and resolution by gel electrophoresis revealed a single predominant human esophageal Siglec-8 ligand migrating at >2 MDa. Purification by size exclusion and affinity chromatography, followed by proteomic mass spectrometry, revealed the protein carrier to be MUC5B. Whereas all human esophageal submucosal cells express MUC5B, only a portion convert it to Siglec-8 ligand by adding terminally sialylated keratan sulfate chains. We refer to this as MUC5B S8L. Material from the esophageal lumen of live subjects revealed MUC5B S8L species ranging from ~1–4 MDa. We conclude that MUC5B in the human esophagus is a protein canvas on which Siglec-8 binding sialylated keratan sulfate chains are post-translationally added. These data expand understanding of Siglec-8 ligands and may help us understand their roles in allergic immune regulation. [ABSTRACT FROM AUTHOR]

Abstract. Wheat (cv Chinese Spring) tissues were transformed using Agrobacterium tumefasciens and a new plasmid modular vector, pMVTBP. We constructed pMVTBP with unique restriction sites connecting (1) the CaMV 35S promoter, (2) a Kozak sequence, (3) the FLAG epitope, (4) the (His)6 epitope, (5) a coding region (for wheat TATA Binding Protein, wTBP) and (6) the CaMV 35S 3'UTR. This vector thus allows easy exchange of different regulatory or coding sequences. Explants of either germinating mature seeds, or immature embryos, were induced to callus for up to two weeks, treated with virulence-induced bacteria for one hour, then regenerated into plantlets. Transient expression of a GUS reporter gene, assayed at about one week, occurred in 10--12% of calluses. Expression of the FLAG-tagged wTBP was also detected, by immunostaining. Stable expression, by selective growth on geneticin, and by GUS expression at about six weeks, occurred in 1-2% of calluses, quite comparable to that achieved by other methods. [ABSTRACT FROM AUTHOR]

Investigates the utility of the Social Cognition and Object Relations Scale (SCORS). Use of SCORS to assess an array of psychological functioning by using clinical narratives such as the Thematic Apperception Test (TAT); Differentiation between antisocial personality disorder, borderline personality disorder, narcissistic personality disorder and Cluster C personality disorder.

Investigates three factors that may contribute to the negative brightness temperature differences between 11 and 6.7 micrometers observed by global satellites. Calibration errors; Nonuniform scenes within the field of view; Physical properties of the observed phenomena.

In this issue of Blood, Doyle et al provide evidence that knockout of the genes encoding the two most abundant eosinophil secondary granule proteins disrupts the normal differentiation of eosinophils from progenitors in the bone marrow, providing a novel strain of mice with a highly specific deficiency in eosinophilopoiesis and, therefore, eosinophils. This strain is likely to be used by investigators to elaborate the normal vs pathogenic roles of eosinophils in health and disease. [ABSTRACT FROM AUTHOR]

The article presents a comment on the paper "Deficiencies in the Present Funding Process in Meteorology," by Toby Carlson published in a 2007 issue of the "Bulletin of the American Meteorological Society". There are four characteristics that define a successful research team, and they include shared learning and discovery, connections to other applications and life experiences, and an inclusive environment.

This paper introduces the Continuity Moderate Resolution Imaging Spectroradiometer (MODIS)-Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (MVCM), a cloud detection algorithm designed to facilitate continuity in cloud detection between the MODIS (Moderate Resolution Imaging Spectroradiometer) on the Aqua and Terra platforms and the series of VIIRS (Visible Infrared Imaging Radiometer Suite) instruments, beginning with the Soumi National Polar-orbiting Partnership (SNPP) spacecraft. It is based on the MODIS cloud mask that has been operating since 2000 with the launch of the Terra spacecraft (MOD35) and continuing in 2002 with Aqua (MYD35). The MVCM makes use of fourteen spectral bands that are common to both MODIS and VIIRS so as to create consistent cloud detection between the two instruments and across the years 2000–2020 and beyond. Through comparison data sets, including collocated Aqua MODIS and Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) from the A-Train, this study was designed to assign statistical consistency benchmarks between the MYD35 and MVCM cloud masks. It is shown that the MVCM produces consistent cloud detection results between Aqua MODIS, SNPP VIIRS, and NOAA-20 VIIRS and that the quality is comparable to the standard Aqua MODIS cloud mask. Globally, comparisons with collocated CALIOP lidar show combined clear and cloudy sky hit rates of 88.2%, 87.5%, 86.8%, and 86.8% for MYD35, MVCM Aqua MODIS, MVCM SNPP VIIRS, and MVCM NOAA-20 VIIRS, respectively, for June through until August, 2018. For the same months and in the same order for 60S–60N, hit rates are 90.7%, 90.5%, 90.1%, and 90.3%. From the time series constructed from gridded daily means of 60S–60N cloud fractions, we found that the mean day-to-day cloud fraction differences/standard deviations in percent to be 0.68/0.55, 0.94/0.64, −0.20/0.50, and 0.44/0.82 for MVCM Aqua MODIS-MVCM SNPP VIIRS day and night, and MVCM NOAA-20 VIIRS-MVCM SNPP VIIRS day and night, respectively. It is seen that the MODIS and VIIRS 1.38 µm cirrus detection bands perform similarly but with MODIS detecting slightly more clouds in the middle to high levels of the troposphere and the VIIRS detecting more in the upper troposphere above 16 km. In the Arctic, MVCM Aqua MODIS and SNPP VIIRS reported cloud fraction differences of 0–3% during the mid-summer season and −3–4% during the mid-winter. [ABSTRACT FROM AUTHOR]

Sea ice leads (fractures) play a critical role in the exchange of mass and energy between the ocean and atmosphere in the polar regions. The thinning of Arctic sea ice over the last few decades will likely result in changes in lead distributions, so monitoring their characteristics is increasingly important. Here we present a methodology to detect and characterize sea ice leads using satellite imager thermal infrared window channels. A thermal contrast method is first used to identify possible sea ice lead pixels, then a number of geometric and image analysis tests are applied to build a subset of positively identified leads. Finally, characteristics such as width, length and orientation are derived. This methodology is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) observations for the months of January through April over the period of 2003 to 2018. The algorithm results are compared to other satellite estimates of lead distribution. Lead coverage maps and statistics over the Arctic illustrate spatial and temporal lead patterns. [ABSTRACT FROM AUTHOR]

Cloud properties are critical to our understanding of weather and climate variability, but their estimation from satellite imagers is a nontrivial task. In this work, we aim to improve cloud detection, which is the most fundamental cloud property. We use a neural network applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements to determine whether an imager pixel is cloudy or cloud-free. The neural network is trained and evaluated using 4 years (2016–2019) of coincident measurements between VIIRS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). We successfully address the lack of sun glint in the collocation dataset with a simple semi-supervised learning approach. The results of the neural network are then compared with two operational cloud masks: the Continuity MODIS-VIIRS Cloud Mask (MVCM) and the NOAA Enterprise Cloud Mask (ECM). We find that the neural network outperforms both operational cloud masks in most conditions examined with a few exceptions. The largest improvements we observe occur during the night over snow- or ice-covered surfaces in the high latitudes. In our analysis, we show that this improvement is not solely due to differences in optical-depth-based definitions of a cloud between each mask. We also analyze the differences in true-positive rate between day–night and land–water scenes as a function of optical depth. Such differences are a contributor to spatial artifacts in cloud masking, and we find that the neural network is the most consistent in cloud detection with respect to optical depth across these conditions. A regional analysis over Greenland illustrates the impact of such differences and shows that they can result in mean cloud fractions with very different spatial and temporal characteristics. [ABSTRACT FROM AUTHOR]

Cloud properties are critical to our understanding of weather and climate variability, but their estimation from satellite imagers is a nontrivial task. In this work, we aim to improve cloud detection which is the most fundamental cloud property. We use a neural network applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements to determine whether an imager pixel is cloudy or cloud-free. The neural network is trained and evaluated using four years (2016-2019) of coincident measurements between VIIRS and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). We successfully address the lack of sun glint in the collocation dataset with a simple semi-supervised learning approach. The results of the neural network are then compared with two operational cloud masks: the MODIS-VIIRS Continuity Cloud Mask (MVCM) and the NOAA Enterprise Cloud Mask (ECM). We find that the neural network outperforms both operational cloud masks in most conditions examined with a few exceptions. The largest improvements we observe occur during the night over snow or ice covered surfaces in the high latitudes. In our analysis, we show that this improvement is not solely due to differences in optical depth-based definitions of a cloud between each mask. We also analyze the differences in true positive rate between day/night and land/water scenes as a function of optical depth. Such differences are a contributor to spatial artifacts in cloud masking and we find that the neural network is the most consistent in cloud detection with respect to optical depth across these conditions. A regional analysis over Greenland illustrates the impact of such differences and shows that they can result in mean cloud fractions with very different spatial and temporal characteristics. [ABSTRACT FROM AUTHOR]

Examines the expression of lysophospholipases (LPLases) by eosinophils in the asthmatic lung. Hydrolysis of surfactant phospholipids catalyzed by phospholipase A[sub 2] (PLA[sub 2]); Influence of PLA[sub 2] and eosinophil LPLases on the ability of the surfactant to maintain airway patency; LPLases activity.

Biomarkers of disease activity have come into wide use in the study of mechanisms of human disease and in clinical medicine to both diagnose and predict disease course; as well as to monitor response to therapeutic intervention. Here we review biomarkers of the involvement of mast cells, basophils, and eosinophils in human allergic inflammation. Included are surface markers of cell activation as well as specific products of these inflammatory cells that implicate specific cell types in the inflammatory process and are of possible value in clinical research as well as within decisions made in the practice of allergy-immunology. [ABSTRACT FROM AUTHOR]

Profiles of atmospheric temperature and water vapor from remotely sensed platforms provide critical observations within the temporal and spatial gaps of the radiosonde network. The 2017 National Academies of Science Decadal Survey highlighted that observations of the planetary boundary layer (PBL) from the current space-based observing system are not of the necessary accuracy or resolution for monitoring and predicting high-impact weather phenomena. One possible solution to improving observations of the PBL is supplementing the existing space-based observing system with a network of ground-based profilers. A synthetic information content study is developed utilizing profiles from the Atmospheric Radiation Measurement (ARM) program sites at the Southern Great Plains (SGP), east North Atlantic (ENA), and North Slope of Alaska (NSA) to assess the benefits, in terms of degrees of freedom (DOF), vertical resolution, and uncertainties, of a synergy between the ground-based Atmospheric Emitted Radiance Interferometer (AERI) with space-based hyperspectral infrared (IR) sounders. A combination of AERI with any of the three polar-orbiting IR sounders: the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), or the Infrared Atmospheric Sounding Interferometer (IASI), results in a DOF increase of 30%–40% in the surface-to-700-hPa layer compared to the space-based instrument alone. Introducing AERI measurements to the observing system also results in significant improvements to vertical resolution and uncertainties in the bottom 1000 m of the atmosphere compared to CrIS measurements alone. A synergy of CrIS and AERI exceeds the 1-km-vertical-resolution goal set by the Decadal Survey in the lowest 1000 m. [ABSTRACT FROM AUTHOR]

Abstract: The lidar and radar profiling capabilities of the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites provide opportunities to improve the characterization of cloud properties. An Arctic cloud climatology based on their observations may be fundamentally different from earlier Arctic cloud climatologies based on passive satellite observations, which have limited contrast between the cloud and underlying surface. Specifically, the Radar–Lidar Geometrical Profile product (RL-GEOPROF) provides cloud vertical profiles from the combination of active lidar and radar. Based on this data product for the period July 2006 to March 2011, this paper presents a new cloud macrophysical property characteristic analysis for the Arctic, including cloud occurrence fraction (COF), vertical distributions, and probability density functions (PDF) of cloud base and top heights. Seasonal mean COF shows maximum values in autumn, minimum values in winter, and moderate values in spring and summer; this seasonality is more prominent over the Arctic Ocean on the Pacific side. The mean ratios of multi-layer cloud to total cloud over the ocean and land are between 24% and 28%. Low-level COFs are higher over ocean than over land. The ratio of low-level cloud to total cloud is also higher over ocean. Middle-level and high-level COFs are smaller over ocean than over land except in summer, and the ratios of middle-level and high-level clouds to total cloud are also smaller over ocean. Over the central Arctic Ocean, PDFs of cloud top height and cloud bottom height show (1) two cloud top height PDF peaks, one for cloud top heights lower than 1200m and another between 7 and 9km; and (2) high frequency for cloud base below 1000m with the majority of cloud base heights lower than 2000m. [Copyright &y& Elsevier]

Precipitable water vapor (PWV) observations from the National Center of Atmospheric Research (NCAR) SuomiNet networks of ground-based global positioning system (GPS) receivers and the National Oceanic and Atmospheric Administration (NOAA) Profiler Network (NPN) are used in the regional assessment of global climate models. Study regions in the U.S. Great Plains and Midwest highlight the differences among global climate model output from the Fourth Assessment Report (AR4) Special Report on Emissions Scenarios (SRES) A2 scenario in their seasonal representation of column water vapor and the vertical distribution of moisture. In particular, the Community Climate System model, version 3 (CCSM3) is shown to exhibit a dry bias of over 30% in the summertime water vapor column, while the Goddard Institute for Space Studies Model E20 (GISS E20) agrees well with PWV observations. A detailed assessment of vertical profiles of temperature, relative humidity, and specific humidity confirm that only GISS E20 was able to represent the summertime specific humidity profile in the atmospheric boundary layer (<3%) and thus the correct total column water vapor. All models show good agreement in the winter season for the region. Regional trends using station-elevation-corrected GPS PWV data from two complimentary networks are found to be consistent with null trends predicted in the AR4 A2 scenario model output for the period 2000-09. The time to detect (TTD) a 0.05 mm yr−1 PWV trend, as predicted in the A2 scenario for the period 2000-2100, is shown to be 25-30 yr with 95% confidence in the Oklahoma-Kansas region. [ABSTRACT FROM AUTHOR]

The properties of clouds that may be observed by satellite instruments, such as optical thickness and cloud-top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through 'instrument simulators,' diagnostic tools that map the model representation to synthetic observations so that differences can be interpreted as model error. But simulators may themselves be restricted by limited information or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP), two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail datasets developed for comparison with global models using ISCCP and MODIS simulators. In nature MODIS observes less midlevel cloudiness than ISCCP, consistent with the different methods used to determine cloud-top pressure; aspects of this difference are reproduced by the simulators. Differences in observed distributions of optical thickness, however, are not captured. The largest differences can be traced to different approaches to partly cloudy pixels, which MODIS excludes and ISCCP treats as homogeneous. These cover roughly 15% of the planet and account for most of the optically thinnest clouds. Instrument simulators cannot reproduce these differences because there is no way to synthesize partly cloudy pixels. Nonetheless, MODIS and ISCCP observations are consistent for all but the optically thinnest clouds, and models can be robustly evaluated using instrument simulators by integrating over the robust subset of observations. [ABSTRACT FROM AUTHOR]

No Abstract available. [ABSTRACT FROM AUTHOR]

The first of the next-generation series of the Geostationary Operational Environmental Satellite (GOES-R) is scheduled for launch in 2015. The new series of GOES will not have an infrared (IR) sounder dedicated to acquiring high-vertical-resolution atmospheric temperature and humidity profiles. High-spectral-resolution sensors have a much greater vertical-resolving power of temperature, moisture, and trace gases than low-spectral-resolution sensors. Because of coarse vertical resolution and limited accuracy in the legacy sounding products from the current GOES sounders, placing a high-spectral-resolution IR sounder with high temporal resolution in the geostationary orbit can provide nearly time-continuous three-dimensional moisture and wind profiles. This would allow substantial improvements in monitoring the mesoscale environment for severe weather forecasting and other applications. Application areas include nowcasting (and short-term forecasts) and numerical weather prediction, which require products such as atmospheric moisture and temperature profiles as well as derived parameters, clear-sky radiances, vertical profiles of atmospheric motion vectors, sea surface temperature, cloud-top properties, and surface properties. Other application areas include trace gases/air quality, dust detection and characterization, climate, and calibration. This paper provides new analysis that further documents the available information regarding the anticipated improvements and their benefits. [ABSTRACT FROM AUTHOR]

Temporal changes in stability and shear associated with the development of thunderstorms are quantified using the enhanced temporal resolution of combined Atmospheric Emitted Radiance Interferometer (AERI) thermodynamic profile retrievals and National Oceanic and Atmospheric Administration (NOAA) 404-MHz wind profiler observations. From 1999 to 2003, AERI systems were collocated with NOAA wind profilers at five sites in the southern Great Plains of the United States, creating a near-continuous dataset of atmospheric soundings in both the prestorm and poststorm environments with a temporal resolution of up to 10 min between observations. Median values for several standard severe weather indices were calculated for tornadic storms and nontornadic supercells. It was found that instability generally increases throughout the preconvective period, reaching a peak roughly 1 h before a tornado forms or a nontornadic supercell forms large hail. Wind shear for both tornadic and nontornadic storms starts to increase roughly 3 h before storm time. However, indices are highly variable between time and space and may not be representative of the environment at large. [ABSTRACT FROM AUTHOR]

Various perspectives on leadership within the psychoanalytic, organizational and socio-biological literature are reviewed, with particular attention to research studies in these areas. Hypotheses are offered about what makes an effective leader: her ability to structure tasks well in order to avoid destructive regressions, to make constructive use of the omnipresent regressive energies in group life, and to redirect regressions when they occur. Systematic qualitative observations of three videotaped sessions each from N = 18 medical staff work groups at an urban medical center are discussed, as is the utility of a scale, the Leadership and Group Regressions Scale (LGRS), that attempts to operationalize the hypotheses. Analyzing the tapes qualitatively, it was noteworthy that at times (in N = 6 groups), the nominal leader of the group did not prove to be the actual, working leader. Quantitatively, a significant correlation was seen between leaders’ LGRS scores and the group’s satisfactory completion of their quantitative goals (p = 0.007) and ability to sustain the goals (p = 0.04), when the score of the person who met criteria for group leadership was used. [ABSTRACT FROM AUTHOR]

This study investigates the facets of the alliance and their relationship with estimated effectiveness of psychotherapy using a measure called the Combined Alliance Short Form (CASF; Hatcher, 1999; Hatcher & Barends, 1996; Hatcher, Barends, Hansell, & Gutfreund, 1995). Because the CASF has both patient and therapist versions, it was possible to compare ratings of various facets of the alliance from each perspective. Data were collected from 125 patient–therapist dyads, and all participants completed the CASF as well as measures of perceived progress during therapy. Convergence was examined for each alliance subscale for the patient–therapist dyads. Both the patient and therapist Confident Collaboration factors were found to be primary predictors of perceived improvement in psychotherapy. Number of psychotherapy sessions was related to patient estimates of improvement and therapist ratings of the amount of help received by their patients as well. Confident Collaboration, a factor that reflects the level of confidence and commitment a patient experiences regarding the therapy as well as the degree to which the therapy is experienced as worthwhile, is discussed in relation to previous research. Implications regarding the presence of this factor during psychotherapy are considered in detail. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An assessment of the performance of the Geostationary Operational Environmental Satellite (GOES) sounder cloud-top pressure product is presented. GOES sounder cloud-top-height data were compared with values derived from a consensus cloud boundary dataset that utilizes data from a cloud lidar and a cloud radar located at the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program’s Cloud and Radiation Test Bed (CART) site in Lamont, Oklahoma. Comparisons were performed from April 2000 to March 2002. A temporal filtering process was applied to the cloud lidar and cloud radar output so that a representative picture of the cloud field on the same spatial scale of the GOES sounder could be derived. Comparisons between the GOES sounder and ground-based cloud boundary measurements yielded a mean difference of 1772 m and a standard deviation of 1733 m. The difference between GOES cloud-top-height and ground-based retrievals is within ±500 m for 22% of the retrievals and within ±1500 m for 56% of the retrievals. These results are comparable to findings in similar studies that utilized the MODIS Airborne Simulator. [ABSTRACT FROM AUTHOR]

We examined the impact of patient- and therapist-rated alliance developed during psychological assessment on the subsequent alliance measured early and late in formal psychotherapy. We hypothesized that a working alliance developed during psychological assessment conducted from a collaborative therapeutic model of assessment (TMA; Finn&Tonsager, 1992, 1997; Fischer, 1994) between the patient and therapist would carry into formal psychotherapy. We also hypothesized that alliance for those patients receiving a TMA would be significantly greater than patients receiving psychological testing as usual. To test this hypothesis, we administered the Combined Alliance Short Form-Patient Version (Hatcher&Barends, 1996) and the Combined Alliance Short Form-Therapist Version (Hatcher, 1999) to a sample of outpatients and their therapists at the end of the assessment feedback session, early, and late in psychotherapy. The hypotheses were supported as alliance scales rated at the assessment feedback session demonstrated positive and significant relationships with alliance throughout formal psychotherapy and in relation to a control group. The clinical utility and research implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

Two-category support vector machines (SVMs) have become very popular in the machine learning community for classification problems and have recently been shown to have good optimality properties for classification purposes. Treating multicategory problems as a series of binary problems is common in the SVM paradigm. However, this approach may fail under a variety of circumstances. The multicategory support vector machine (MSVM), which extends the binary SVM to the multicategory case in a symmetric way, and has good theoretical properties, has recently been proposed. The proposed MSVM in addition provides a unifying framework when there are either equal or unequal misclassification costs, and when there is a possibly nonrepresentative training set. Illustrated herein is the potential of the MSVM as an efficient cloud detection and classification algorithm for use in Earth Observing System models, which require knowledge of whether or not a radiance profile is cloud free. If the profile is not cloud free, it is valuable to have information concerning the type of cloud, for example, ice or water. The MSVM has been applied to simulated MODIS channel data to classify the radiance profiles as coming from clear sky, water clouds, or ice clouds, and the results are promising. It can be seen in simple examples, and application to Moderate Resolution Imaging Spectroradiometer (MODIS) observations, that the method is an improvement over channel-by-channel partitioning. It is believed that the MSVM will be a very useful tool for classification problems in atmospheric sciences. [ABSTRACT FROM AUTHOR]

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System (EOS) platform launched in December 1999. After achieving final orbit, MODIS began earth observations in late February 2000 and has been acquiring data since that time. The instrument is also being flown on the Aqua spacecraft, launched in May 2002. A comprehensive set of remote sensing algorithms for cloud detection and the retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various algorithms being used for the remote sensing of cloud properties from MODIS data with an emphasis on the pixel-level retrievals (referred to as Level-2 products), with 1-km or 5-km spatial resolution at nadir. An example of each Level-2 cloud product from a common data granule (5 min of data) off the coast of South America will be discussed. Future efforts will also be mentioned. Relevant points related to the global gridded statistics products (Level-3) are highlighted though additional details are given in an accompanying paper in this issue. [ABSTRACT FROM AUTHOR]

Presents a study which examined the consistency in shortwave top-of-atmosphere reflectances and albedos obtained from satellite measurements and radiation modeling. Details of the Earth Radiation Budget Experiment and Advanced Very High Resolution Radiometer satellite data used in the study; Identification of uniform low-level overcast scenes; Retrieval of cloud optical properties.