The Australian monsoon, Part 2 : Depressions and cyclones

A study of the NCEP/NCAR Reanalysis for the Australian region during the southern summer reveals that most of the depressions and cyclones over the region form and develop in a stationary wave that develops along the continent's northern coastline during this period due to land-sea thermal contrast. The structure and properties of the stationary wave are brought out in detail and internal and external forcings that lead to its development into depressions and cyclones are discussed. Environmental factors that appear to influence the movement and recurvature of cyclones over the region are discussed with two case studies.

On the onset of summer monsoon over India in relation to interactions of the monsoon stationary wave with transient baroclinic waves leading to monsoon cyclogenesis

The important problem of the early or late onset of summer monsoon over India is addressed in the present study and found to be related to the structure and behaviour of a monsoon stationary wave that forms over the region due to land-sea thermal contrast and interacts with travelling wave disturbances in the westerlies and the easterlies associated with the subtropical belt over Asia. Depending upon the type of coupling and decoupling that occurs between the interacting waves, monsoon advances towards India either slowly or speedily. Since northward-propagating monsoon depressions are found to accelerate the onset processes. the study carries out a detailed analysis of the interaction processes which give rise to such disturbances and determine their development and movement.

Thermographic Stall Detection by Model-Inspired Evaluation of the Dynamic Temperature Behaviour

Model-inspired signal processing approaches with an enhanced detectability of flow separation on thermographic images are presented. Flow separation causes performance loss, structural loads and increasing acoustic emissions on wind turbine rotor blades. However, due to the low thermal contrast between turbulent and separated flow regions, the non-invasive thermographic visualisation of flow separation is currently only possible for wind tunnel measurements, which are characterised by a high thermal contrast and a small measuring distance. The state-of-the-art signal processing approaches evaluate the surface temperature fluctuation of thermographic image series. However, understanding of the signal measurement chain with a distinct consideration of the influences on the dynamic surface temperature is incomplete. Therefore, designing model-inspired signal processing approaches which provide a high interpretability and a maximum contrast is an open task. The proposed signal processing approaches evaluate the surface response selectively, by using the amplitude information of the surface temperature response to an oscillating input signal or gradient-based for a transient input signal. The approaches are applied to wind tunnel measurements on a rotor blade profile at a near thermodynamic steady state and a transient thermodynamic behaviour at Reynolds numbers that are representative for operational wind turbines. The gradient-based evaluation shows an improved contrast for the detection of flow separation, but is only applicable to profiles with transient thermodynamic behaviour. The amplitude evaluation provides a high degree of interpretability of the processed images based on flow-dependent features and enables for an unambiguous identification of flow separation by a global amplitude minimum close to the separation point. Additionally, an increased spatial resolution for surface modifications is shown, while the contrast between flow regions is significantly decreased. Hence, the proposed approaches allow for an improved identifiability of flow separation with regard to future applications on wind turbines in operation.

Discrepancies of Upper Troposphere Summer Thermal Contrast Between Tibetan Plateau and Tropical Indian Ocean in Multiple Data

Under the background of global warming, the summer land-sea thermal contrasts at the upper troposphere exists great discrepancies in radiosonde data (IUK, RICH, and RAOBCORE), reanalysis data (JRA-55, NCEP/DOE, and ERA5) and CMIP6 models results (MPI, FGOALS, and CESM2) for the period of 1979-2014. It can be found that the descriptive statistical indicators (i.e., maximum, minimum, and skewness) of the summer land-sea thermal contrasts index (TTI) between the Tibetan Plateau (TP) and the Tropical Indian Ocean (TIO) vary greatly. The ERA5 and JRA-55 data have the best correlation with radiosonde data. The linear trend and running linear trend (RTL) of the radiosonde data are significantly correlated with the reanalysis data, and both show that the land-sea thermal contrast rapidly increasing are in 1990s and the late 2000s, and the period of rapid weakening was early 2000s. This interannual variation may modulated by the decadal signals such as Pacific Decadal Oscillation (PDO). Except for the NCEP/DOE and IUK, other data show that the most significant warming in the TP-TIO region is at the upper troposphere, and the vertical profiles of the summer temperature trend are quite different in different data, and CMIP6 shows an obvious warm bias in the upper troposphere.

Improved Influenza Diagnostics through Thermal Contrast Amplification

Influenza poses a serious health threat and creates an economic burden for people around the world. The accurate diagnosis of influenza is critical to the timely clinical treatment of patients and the control of outbreaks to protect public health. Commercially available rapid influenza diagnostic tests (RIDTs) that are operated by visual readout are widely used in clinics to screen influenza infections, but RIDTs suffer from imperfect analytical sensitivity, especially when the virus concentration in the sample is low. Fortunately, the sensitivity can be simply improved through an add-on signal amplification step, i.e., thermal contrast amplification (TCA). To demonstrate the advantage of TCA for influenza diagnosis, we conducted a prospective cohort study on 345 clinical specimens collected for influenza A and B testing during the 2017–2018 influenza season. All samples were tested using the Quidel QuickVue Influenza A + B test, followed by a TCA readout, and then confirmatory polymerase chain reaction testing. Through the TCA detecting sub-visual weak positives, TCA reading improved the overall influenza sensitivity by 53% for influenza A and 33% for influenza B over the visual RIDTs readings. Even though the specificity was compromised slightly by the TCA protocol (relative decrease of 0.09% for influenza A and 0.01% for influenza B), the overall performance was still better than that achieved by visual readout based on comparison of their plots in receiver operating characteristic space and F1 scores (relative increase of 14.5% for influenza A and 12.5% for influenza B). Performing a TCA readout on wet RIDTs also improved the overall TCA performance (relative increase in F1 score of 48%). Overall, the TCA method is a simple and promising way to improve the diagnostic performance of commercial RIDTs for infectious diseases, especially in the case of specimens with low target analytes.