Comparative analysis of the rapid intensification of two super cyclonic storms in the Arabian Sea

A comparative analysis of the rapid intensification(RI)of super cyclonic storms Chapala(2015)and Kyarr(2019)in the Arabian Sea is conducted using the North Indian Ocean tropical cyclone data,microwave sounding images,the NOAA OISST data and the ERA5 reanalysis data.Results show that the subtropical westerly jet stream and the Southern Hemisphere anticyclonic circulation led to the formation of an obvious double-channel outflow from the northern and southern sides of the two storm centers,and the substantial inflow appeared at the eastern boundary layer of both storms.These promoted the vertical ascent motion and release of the latent heat of condensation.A warm sea surface is a necessary but not dominant factor for the RI of cyclonic storms in the Arabian Sea.During the RI of Chapala and Kyarr,the deep vertical wind shear was less than 10 m s-1;moreover,the mid-level humidity conditions favored the RI of the two cyclonic storms.Chapala had a single warm core,whereas Kyarr had double warm cores in the vertical direction.The impacts of the latent heat of fusion is more obvious for Chapala,and the potential vorticity in its inner core increases from 4.4 PVU to 8.8 PVU,whereas the potential vorticity and vorticity in the inner core of Kyarr do not change significantly.Microwave detection images show that both Chapala and Kyarr were accompanied by the formation of eyewalls during the RI phase,and the radius of maximum wind decreased and the maximum wind speed increased during the eyewall-thinning process.Both Chapala and Kyarr passed through a positive anomaly region of maximum potential intensity during the RI phase,which increases the possibility to develop to higher intensity after genesis.

Seasonal Prediction of Tropical Cyclones and Storms over the Southwestern Indian Ocean Region Using the Generalized Linear Models

Tropical cyclones (TCs) and storms (TSs) are among the devastating events in the world and southwestern Indian Ocean (SWIO) in particular. The seasonal forecasting TCs and TSs for December to March (DJFM) and November to May (NM) over SWIO were conducted. Dynamic parameters including vertical wind shear, mean zonal steering wind and vorticity at 850 mb were derived from NOAA (NCEP-NCAR) reanalysis 1 wind fields. Thermodynamic parameters including monthly and daily mean Sea Surface Temperature (SST), Outgoing Longwave Radiation (OLR) and equatorial Standard Oscillation Index (SOI) were used. Three types of Poison regression models (i.e. dynamic, thermodynamic and combined models) were developed and validated using the Leave One Out Cross Validation (LOOCV). Moreover, 2 × 2 square matrix contingency tables for model verification were used. The results revealed that, the observed and cross validated DJFM and NM TCs and TSs strongly correlated with each other (p ≤ 0.02) for all model types, with correlations (r) ranging from 0.62 - 0.86 for TCs and 0.52 - 0.87 for TSs, indicating great association between these variables. Assessment of the model skill for all model types of DJFM and NM TCs and TSs frequency revealed high skill scores ranging from 38% - 70% for TCs and 26% - 72% for TSs frequency, respectively. Moreover, results indicated that the dynamic and combined models had higher skill scores than the thermodynamic models. The DJFM and NM selected predictors explained the TCs and TSs variability by the range of 0.45 - 0.65 and 0.37 - 0.66, respectively. However, verification analysis revealed that all models were adequate for predicting the seasonal TCs and TSs, with high bias values ranging from 0.85 - 0.94. Conclusively, the study calls for more studies in TCs and TSs frequency and strengths for enhancing the performance of the March to May (MAM) and December to October (OND) seasonal rainfalls in the East African (EA) and Tanzania in particular.

Historic and Future Perspectives of Storm and Cyclone

In weather sciences,the two specific terms“storm”and“cyclone”frequently appear in literature and usually refer to the violent nature of a number of weather systems characterized by central low pressure,strong winds,large precipitation amounts in the form of rain,freezing rain,or snow,as well as thunder and lightning.But what is the connection between these two specific terms?In this paper,the historic evolutions of the terms“storm”and“cyclone”are reviewed from the perspective of weather science.The earliest recorded storms in world history are also briefly introduced.Then,the origin of the term“meteorological bomb”,which is the nickname of the“explosive cyclone”is introduced.Later,the various definitions of explosive cyclones given by several researchers are discussed.Also,the climatological features of explosive cyclones,as well as the future trends of explosive cyclones under global climate change,are discussed.

Epidemiology of Biopsy Proven Glomerular Disorders and Effect of Severe Cyclone on Its Incidence in Central Queensland Region of Australia

Aim: The objectives of this study are to determine the epidemiology of biopsy-proven glomerular disease (GD) in Central Queensland and the effect of a severe cyclone on its incidence and clinical phenotype. Background: Central Queensland (CQ) has a relatively high incidence of kidney disease. Since its biopsy service commenced in 2005, there have been no data on biopsy-proven GD. It has been suggested that GD incidence changes around times of natural disasters. In February 2015, the CQ region was affected by a category 5 Cyclone Marcia. This provides an opportunity to explore possible environmental triggers of GD. Methods: This was a single-centre retrospective observational study on biopsy-proven kidney disease in CQ. All kidney biopsies performed between January 2005 and December 2019 were included. Patients with biopsy-proven GD during 3 years before and after Cyclone Marcia (from 2012 to 2018) were analysed. Results: 170 native kidney biopsies occurred during the 15 years. The number of annual biopsies steadily increased from 7 to 16. The most common biopsy-proven kidney disease was IgA Nephropathy (27%) followed by diabetic nephropathy (20%). GD comprised 64% of biopsies. Unlike other GD, the incidence of ANCA-associated vasculitis (AAV) significantly increased after cyclone (one pre- and eight post-cyclone, P value = 0.039). The majority of AAV cases occurred in the first year after the cyclone. Conclusion: Kidney biopsies in CQ provide important epidemiological data on biopsy-proven kidney disease. Cyclones have a possible effect on the incidence and clinical phenotype of ANCA associated vasculitis.

A Modified Algorithm for Identifying and Tracking Extratropical Cyclones

In this study, a modified identification and tracking algorithm for extratropical cyclones is developed. This identification scheme is based on triangular-mesh contouring techniques combined with a connected-component labeling method in order to detect the outer boundaries and spatial domain characteristics of individual cyclones. A new tracking method allowing for the identification of cyclone merging and splitting events, as well as short-lived windstorms, is developed to reduce the uncertainty in the tracking of extratropical cyclones. I also show that this method excludes the tracks of open systems that would have been unnecessarily detected using conventional NCP methods. The climatological features of the distribution of cyclone frequencies are substantially larger over the traditional storm track regions compared to those seen in previous studies. Interestingly, a significant increase in the cyclone density in the Arctic occurs during all four seasons（up to 19%in summer） compared to that seen with a latitude-longitude gridded mesh analysis. I develop two new regional intensity indices（depth and vorticity） based on the cyclonic domain to better quantify the cyclonic activity in the Arctic region, and find that the interannual variabilities in these two indices are highly consistent. The results of this analysis may shed light on high-latitude cyclonic behavior studies via the newly detected 2D cyclone atlas derived from this cyclonic-domain-based algorithm.