Chennai to get flood warning system
Relationship Science Salaries trends. 28 salaries for 4 jobs at Relationship Science in Chennai. Salaries posted anonymously by Relationship. The relation between insect abundance and rainfall was analyzed using . T.N. Ananthakrishnan, Emeritus Scientist, Chennai, for literature and Vinod K.V., Devagiri Proceedings of the National Academy of Sciences USA. El-Nino that freaked the weather conditions in Tamil Nadu especially Chennai, is in a very complicated relationship with India. Besides affecting.
For instance, higher scaling rates for sub-daily rainfall extremes than daily extremes are reported in previous studies 1021 The precipitation-temperature relationship can also be affected by the other factors such as duration and type of a storm event 23 — 25temperature 26season and the geographical location where the storm occurs 27 For instance, Wasko et al.
Furthermore, convective events are more sensitive to temperature 29 and show higher scaling than stratiform rainfall 30which is supported by the findings of Moseley et al. In India, major rainfall occurs through convective storms which have high-temperature dependency Therefore, scaling of rainfall extremes with surface air temperature SAT may not be a good indicator of climatic change Moreover, high SAT during the pre-monsoon March—May season most often get cooled down due to rain events, which results in a negative relationship between SAT and rainfall during the monsoon season.
For example, Vittal et al. Since diurnal variations in SAT in response to rainfall may provide improper scaling rates, a relationship of rainfall extremes with T or in the upper troposphere, temperature at hPawhich is at a height sufficient enough to avoid these variations may be robust Furthermore, the relationship between rainfall and humidity may be a good predictor to analyse rainfall extremes under the warmer climate Relative humidity and dewpoint temperature DPT are related as DPT corresponds to the air temperature at which the air is completely saturated with water i.
Urban areas in India face frequent flooding caused by extreme rainfall events. Urban stormwater infrastructures designs are based on intensity duration frequency IDF curves, which are usually developed using an annual maximum rainfall series assuming stationary conditions in India 36 However, in the present scenario, annual maximum rainfall cannot be assumed to have a time-invariant probability density function 3638 For instance, Cheng and AghaKouchak 40 reported significant differences in stationary and nonstationary intensity duration frequency IDF curves estimated for a shorter duration at a few stations in the USA.
Despite the need of an improved understanding of rainfall extremes in urban areas, efforts to evaluate the scaling relationship between rainfall extremes and SAT, T, and DPT in India have been limited. Moreover, the relationship of daily and sub-daily rainfall extremes with T and DPT may help to improve our understanding of precipitation extremes, which might have strong implications for urban stormwater designs, especially under non-stationary climate conditions.
Here, we aim to address the following questions: Therefore, the selected stations can provide information of rainfall extremes in urban locations especially in the absence of observation stations within urban areas. We acknowledge that these stations may not truly represent urban micro-climate or the factors that affect urban meteorology, for which, a larger number of stations within urban areas will be needed, and are currently unavailable in India. Notwithstanding this limitation, the station based GSOD data can provide valuable information about the relationship between rainfall extremes and temperature at urban locations.
Latest Chennai rains News, Photos, Latest News Headlines about Chennai rains - The Hindu
Since rainfall datasets are available at different spatial resolutions, we applied areal reduction factors 10 to bring all the datasets to point scale consistent with GSOD data. This often inundates the areas through which they pass. But, when one compares Tamil Nadu low pressure system with other monsoon low pressure systems, some puzzling questions arise. How a weaker system brought so much rain? To bring out the aforementioned question, I have compared it with one monsoon depression which was observed in central India during September The low pressure system which brought rains in Tamil Nadu was very feeble in terms of air pressure as compared to the September system.
The thumb rule is that the stronger a system is, the lower will be its air pressure and such a system will produce lot of rain under favourable conditions. In the above image, compactness of clouds of monsoon depression photographed on September 17 is another indicator of its strength over Tamil Nadu system photographed on December 1.
Thus, its definitely intriguing to see such a feeble system producing more rainfall than a powerful system. Internet is already flooded with several articles where without providing substantial evidences, people have linked this heavy rain event with factors like climate change or global warming.
Below, we have a look at what could have made this low pressure system so powerful. Variations in North-East Monsoon M Rajeevandirector of Indian Institute of Tropical Meteorology, Pune, and a senior monsoon researcher says that there is an increasing trend in the amount of northeast monsoon rainfall NEMR in the recent years and this rainfall posseses a lot of variability on inter-annual scale.
He says that the total precipitable water for this system was about 1. In andNEMR was below normal but in andit was slightly above normal.
What caused heavy rains in Tamil Nadu
Role of vortex suspected Weather forecaster Rajesh Kapadia who writes a blog called "Vagaries of Weather" believes that Tamil Nadu heavy rains were caused by development of a vortex within the low pressure near surface levels.
Vortex basically refers to rotating motion observed in a fluid say air in this case.
According to him, such vortex or called vortices when in high number developing within a low pressure can bring sudden heavy rain. A cocktail of weather conditions The atmospheric setup on December 1,appears to be more complex than was anticipated. As can be seen from above image, a high pressure "H" region of clockwise winds anchored over eastern Bay of Bengal caused an inflow of moisture rich warm air from Bay of Bengal in Tamil Nadu.
To represent this, I have used red dotted arrows. As monsoon has withdrawn from most parts of India, the air over central and northern parts of India is drier and colder than the warm moist air coming from southeast.