Effect of eastward moving cloud clusters over northwest India and neighbourhood on the Indian summer monsoon

A number of studies have been made relating to the prediction of date of onset and also the activity of southwest monsoon over India. In this study an attempt has been made to link the behaviour of rainfall in northern and peninsular India to the satellite cloud clusters over the region of Afghanistan, Iran and northwest India. The monsoon rainfall over India commences in June. Hence variation of monsoon rainfall pattern with the movement of cloud clusters from northwest in pre-monsoon and monsoon months have been studied to elucidate the pattern of changes. The variability of monsoon performance largely depends on the number and movement of cloud clusters over northwestern region during pre-monsoon and monsoon months.

Formation mechanism of super cluster over the tropics

A large-scale cloud phenomenon was analyzed to understand its internal structure, organization and movement. A westward moving uncommon super cluster was shown to have developed in the study region while each cloud cluster moved FJESE. The super cluster has horizontal length 2000 km, life time more than 2 days, very low TBB (<210 K) cloud area ~40× 104 km2 and moved westward with a speed of ~6 m/s. These features are some what different from the usual properties of super cluster as reported in several works. It was found that new clouds successively formed and interacted between themselves, and organized to form cloud clusters. The cloud clusters merged with the old large cluster to take part in the maintenance of super cluster. The propagation speed and the direction of the super cluster was followed by the formation of new cluster.

A Contrast of Recent Changing Tendencies in Genesis Productivity of Tropical Cloud Clusters over the Western North Pacific in May and October

Tropical cloud clusters (TCCs) are embryos of tropical cyclones (TCs) and may have the potential to develop into TCs. The genesis productivity (GP) of TCCs is used to quantify the proportion of TCCs that can evolve into TCs. Recent studies have revealed a decrease in GP of western North Pacific (WNP) TCCs during the extended boreal summer (July–October) since 1998. Here, we show that the changing tendencies in GP of WNP TCCs have obvious seasonality. Although most months could see recent decreases in GP of WNP TCCs, with October experiencing the strongest decreasing trend, May is the only month with a significant recent increasing trend. The opposite changing tendencies in May and October could be attributed to different changes in low-level atmospheric circulation anomalies triggered by different sea surface temperature (SST) configurations across the tropical oceans. In May, stronger SST warming in the tropical western Pacific could prompt increased anomalous westerlies associated with anomalous cyclonic circulation, accompanied by the weakening of the WNP subtropical high and the strengthening of the WNP monsoon. Such changes in background atmospheric circulations could favor the enhancement of atmospheric eddy kinetic energy and barotropic energy conversions, resulting in a recent intensified GP of WNP TCCs in May. In October, stronger SST warming in the tropical Atlantic and Indian Oceans contributed to anomalous easterlies over the tropical WNP associated with anomalous anticyclonic circulation, giving rise to the suppressed atmospheric eddy kinetic energy and recent weakened GP of WNP TCCs. These results highlight the seasonality in recent changing tendencies in the GP of WNP TCCs and associated large-scale atmospheric-oceanic conditions.

Convective Cloud Clusters and Squall Lines along coastal Amazon

Mesoscale convective cloud clusters develop and organize in the form of squall lines along the coastal Amazon in the afternoon hours and propagate inland during the evening hours. The frequency, location, organization into lines and movement of the convective systems are determined by analyzing the “precipitation features” obtained from the TRMM satellite for the period 1998-2014. The convective clusters and their alignments into Amazon coastal squall lines are more frequent from December through July and they mostly stay within 170 km from the coast line. Their development and movement in the afternoon and evening hours of about 14 m s-1 are helped by the sea breeze. Negative phase of Atlantic Dipole and La Niña combined increase the frequency of convective clusters over coastal Amazon. Composite environmental conditions of 13 large Amazon coastal squall line cases in April show that conditional instability increases from 09 LT to 12 LT and the wind profiles show a jet like structure in low levels. The differences in the vertical profiles of temperature and humidity between the large squall line composites and no-squall line composites are weak. However, appreciable increase in the mean value of CAPE from 09 LT to 15 LT is found in large squall line composite. The mean mixing ratio of mixed layer at 09 LT in La Niña situations is significantly larger in the large squall line composite. Thus, CAPE and mixed layer mixing ratio are considered promising indicators of the convective activity over the coastal belt of the Amazon Basin.

Emergency Landing Spot Detection Algorithm for Unmanned Aerial Vehicles

The use and research of Unmanned Aerial Vehicle (UAV) have been increasing over the years due to the applicability in several operations such as search and rescue, delivery, surveillance, and others. Considering the increased presence of these vehicles in the airspace, it becomes necessary to reflect on the safety issues or failures that the UAVs may have and the appropriate action. Moreover, in many missions, the vehicle will not return to its original location. If it fails to arrive at the landing spot, it needs to have the onboard capability to estimate the best area to safely land. This paper addresses the scenario of detecting a safe landing spot during operation. The algorithm classifies the incoming Light Detection and Ranging (LiDAR) data and store the location of suitable areas. The developed method analyses geometric features on point cloud data and detects potential right spots. The algorithm uses the Principal Component Analysis (PCA) to find planes in point cloud clusters. The areas that have a slope less than a threshold are considered potential landing spots. These spots are evaluated regarding ground and vehicle conditions such as the distance to the UAV, the presence of obstacles, the area’s roughness, and the spot’s slope. Finally, the output of the algorithm is the optimum spot to land and can vary during operation. The proposed approach evaluates the algorithm in simulated scenarios and an experimental dataset presenting suitability to be applied in real-time operations.

Container orchestration on HPC systems through Kubernetes

Containerisation demonstrates its efficiency in application deployment in Cloud Computing. Containers can encapsulate complex programs with their dependencies in isolated environments making applications more portable, hence are being adopted in High Performance Computing (HPC) clusters. Singularity, initially designed for HPC systems, has become their de facto standard container runtime. Nevertheless, conventional HPC workload managers lack micro-service support and deeply-integrated container management, as opposed to container orchestrators. We introduce a Torque-Operator which serves as a bridge between HPC workload manager (TORQUE) and container orchestrator (Kubernetes). We propose a hybrid architecture that integrates HPC and Cloud clusters seamlessly with little interference to HPC systems where container orchestration is performed on two levels.