A method for merging flow-dependent forecast error statistics from an ensemble with static statistics for use in high resolution variational data assimilation

The background error covariance matrix, B, is often used in variational data assimilation for numerical weather prediction as a static and hence poor approximation to the fully dynamic forecast error covariance matrix, Pf. In this paper the concept of an Ensemble Reduced Rank Kalman Filter (EnRRKF) is outlined. In the EnRRKF the forecast error statistics in a subspace defined by an ensemble of states forecast by the dynamic model are found. These statistics are merged in a formal way with the static statistics, which apply in the remainder of the space. The combined statistics may then be used in a variational data assimilation setting. It is hoped that the nonlinear error growth of small-scale weather systems will be accurately captured by the EnRRKF, to produce accurate analyses and ultimately improved forecasts of extreme events.

On merging gradient estimation with mean-tracking techniques for cluster identification

This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.

HMEF: framework to evaluate merging of Higher Education Institutions – application of Enterprise Architecture

Mergers of Higher Education Institutions (HEIs) are organisational processes requiring tremendous amount of resources, in terms of time, work, and money. A number of mergers have been seen on previous years and more are to come. Several studies on mergers have been conducted, revealing some crucial factors that affect the success of mergers. Based on literature review on these studies, factors are: the initiator of merger, a reason for merger, geographical distance of merging institutions, organisational culture, the extend of overlapping course portfolio, and Quality Assurance Systems (QASs). Usually these kind of factors are not considered on mergers, but focus is on financial matters. In this paper, a framework (HMEF) for evaluating merging of HEIs is introduced. HMEF is based on Enterprise Architecture (EA), focusing on factors found to be affecting the success of mergers. By using HMEF, HEIs can focus on matters that crucial for merging.

Evidence of component merging equatorward of the cusp

The Polar spacecraft passed through a region near the dayside magnetopause on May 29, 1996, at a geocentric distance of similar to 8 R-E and high, northern magnetic latitudes. The interplanetary magnetic field (IMF) was northward during the pass. Data from the Thermal Ion Dynamics Experiment revealed the existence of low-speed (similar to 50 km s(-1)) ion D-shaped distributions mixed with cold ions (similar to 2 eV) over a period of 2.5 hours. These ions were traveling parallel to the magnetic field toward the Northern Hemisphere ionosphere and were convecting primarily eastward. The D-shaped distributions are distinct from a convecting Maxwellian and, along with the magnetic field direction, are taken as evidence that the spacecraft was inside the magnetosphere and not in the magnetosheath. Furthermore, the absence of ions in the antiparallel direction is taken as evidence that low-shear merging was occurring at a location southward of the spacecraft and equatorward of the Southern Hemisphere cusp. The cold ions were of ionospheric origin, with initially slow field-aligned speeds, which were accelerated upon reflection from the magnetopause. These observations provide significant new evidence consistent with component magnetic merging sites equatorward of the cusp for northward IMF.

AmalgamScope: merging annotations data across the human genome

The past years have shown an enormous advancement in sequencing and array-based technologies, producing supplementary or alternative views of the genome stored in various formats and databases. Their sheer volume and different data scope pose a challenge to jointly visualize and integrate diverse data types. We present AmalgamScope a new interactive software tool focusing on assisting scientists with the annotation of the human genome and particularly the integration of the annotation files from multiple data types, using gene identifiers and genomic coordinates. Supported platforms include next-generation sequencing and microarray technologies. The available features of AmalgamScope range from the annotation of diverse data types across the human genome to integration of the data based on the annotational information and visualization of the merged files within chromosomal regions or the whole genome. Additionally, users can define custom transcriptome library files for any species and use the file exchanging distant server options of the tool.

A method for merging nadir-sounding climate records, with an application to the global-mean stratospheric temperature data sets from SSU and AMSU

A method is proposed for merging different nadir-sounding climate data records using measurements from high-resolution limb sounders to provide a transfer function between the different nadir measurements. The two nadir-sounding records need not be overlapping so long as the limb-sounding record bridges between them. The method is applied to global-mean stratospheric temperatures from the NOAA Climate Data Records based on the Stratospheric Sounding Unit (SSU) and the Advanced Microwave Sounding Unit-A (AMSU), extending the SSU record forward in time to yield a continuous data set from 1979 to present, and providing a simple framework for extending the SSU record into the future using AMSU. SSU and AMSU are bridged using temperature measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), which is of high enough vertical resolution to accurately represent the weighting functions of both SSU and AMSU. For this application, a purely statistical approach is not viable since the different nadir channels are not sufficiently linearly independent, statistically speaking. The near-global-mean linear temperature trends for extended SSU for 1980–2012 are −0.63 ± 0.13, −0.71 ± 0.15 and −0.80 ± 0.17 K decade−1 (95 % confidence) for channels 1, 2 and 3, respectively. The extended SSU temperature changes are in good agreement with those from the Microwave Limb Sounder (MLS) on the Aura satellite, with both exhibiting a cooling trend of ~ 0.6 ± 0.3 K decade−1 in the upper stratosphere from 2004 to 2012. The extended SSU record is found to be in agreement with high-top coupled atmosphere–ocean models over the 1980–2012 period, including the continued cooling over the first decade of the 21st century.