Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state

Diffraction-limited polarimetric imaging of protoplanetary disks and mass-loss shells with VAMPIRES

Both the birth and death of a stellar system are areas of key scientific importance. Whether it's understanding the process of planetary formation in a star's early years, or uncovering the cause of the enormous mass-loss that takes place during a star's dying moments, a key to scientific understanding lies in the inner few AU of the circumstellar environment. Corresponding to scales of 10s of milli-arcseconds, these observations pose a huge technical challenge due to the high angular-resolutions and contrasts required. A major stumbling block is the problem of the Earth's own atmospheric turbulence. The other difficulty is that precise calibration is required to combat the extremely high contrast ratios and high resolutions faced. By taking advantage of the fact that starlight scattered by dust in the circumstellar region is polarized, differential polarimetry can help achieve this calibration. Spectral features can also be utilized

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement

Applying the Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) Framework to evaluate automated evidence synthesis in health behaviour change

YesAutomated tools to speed up the process of evidence synthesis are increasingly apparent within health behaviour research, however, frameworks to evaluate the development and implementation of such tools are not routinely used. This commentary explores the potential of the Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework (NASSS; Greenhalgh et al., 2017) for supporting automated evidence synthesis in health behaviour change by applying it to the ongoing Human Behaviour-Change Project, which aims to revolutionise evidence synthesis within behaviour change intervention research. To increase the relevance of NASSS for health behaviour change, we recommend i) terminology changes (‘condition’ to ‘behaviour’ and ‘patient’ to ‘end user’) and ii) a that it is used prospectively so that complexities can be addressed iteratively. We draw three conclusions about i) the need to specify the organisations that will use the technology, ii) identifying what to do if interdependencies fail and iii) even though we have focused on automated evidence synthesis, NASSS would arguably be beneficial for technology developments in health behaviour change more generally, particularly for invention development (e.g. for a behaviour change app)

Prospectus, February 1, 2017

Staerkel Planetarium provides learning opportunities; New Safely features to be implemented at Parkland; Parkland resources available to help those with depressionhttps://spark.parkland.edu/prospectus_2017/1002/thumbnail.jp

Prospectus, March 8, 2017

Parkland hosts hundreds for regional math competition; College\u27s band, orchestra play themed concerts each semester; Student Government Candidates; Counseling and Advising Center offers resources for anxiety; Scholarships available for Parkland students, but deadlines approach; Parkland hosts Science Olympiad regionals;https://spark.parkland.edu/prospectus_2017/1007/thumbnail.jp

Prospectus, February 8, 2017

Black History Month kicks off at Parkland; Local march coincided with national women\u27s rallies; Behind the badge: meet officers Kopmann, Boltinghouse; Agriculture program director wins innovation award; German club provides extra-curricular option for Parkland students;https://spark.parkland.edu/prospectus_2017/1003/thumbnail.jp

Prospectus, April 5, 2017

Playing chess may provide boon to learning; Understanding the etiquette regarding service animals; Parkland hosted private university transfer fair; Spurlock celebrates diversity with samba performance; Animal Encounters at local museum continues to entertain children;https://spark.parkland.edu/prospectus_2017/1010/thumbnail.jp

Telomere length predicts for outcome to FCR chemotherapy in CLL

We have previously shown that dividing patients with CLL into those with telomeres inside the fusogenic range (TL-IFR) and outside the fusogenic range (TL-OFR) is powerful prognostic tool. Here, we used a high-throughput version of the assay (HT-STELA) to establish whether telomere length could predict for outcome to fludarabine, cyclophosphamide, rituximab (FCR)-based treatment using samples collected from two concurrent phase II studies, ARCTIC and ADMIRE (n = 260). In univariate analysis, patients with TL-IFR had reduced progression-free survival (PFS) (P < 0.0001; HR = 2.17) and shorter overall survival (OS) (P = 0.0002; HR = 2.44). Bifurcation of the IGHV-mutated and unmutated subsets according to telomere length revealed that patients with TL-IFR in each subset had shorter PFS (HR = 4.35 and HR = 1.48, respectively) and shorter OS (HR = 3.81 and HR = 2.18, respectively). In addition, the OS of the TL-OFR and TL-IFR subsets were not significantly altered by IGHV mutation status (P = 0.61; HR = 1.24 and P = 0.41; HR = 1.47, respectively). In multivariate modeling, telomere length was the dominant co-variable for PFS (P = 0.0002; HR = 1.85) and OS (P = 0.05; HR = 1.61). Taken together, our data suggest that HT-STELA is a powerful predictor of outcome to FCR-based treatment and could be used to inform the design of future risk-adapted clinical trials

Prospectus, February 22, 2017

New opportunities for Parkland aviation students; Black History Month continues at Parkland; Navajo storytelling event held at Spurlock; Six inducted into Athletic Hall of Fame; Foreign language enrollment at Parkland remains low;https://spark.parkland.edu/prospectus_2017/1005/thumbnail.jp