Water lifting and outflow gain of kinetic energy in tropical cyclones

While water lifting plays a recognized role in the global atmospheric power budget, estimates for this role in tropical cyclones vary from no effect to a major reduction in storm intensity. To better assess this impact, here we consider the work output of an infinitely narrow thermodynamic cycle with two streamlines connecting the top of the boundary layer in the vicinity of maximum wind (without assuming gradient-wind balance) to an arbitrary level in the inviscid free troposphere. The reduction of a storm’s maximum wind speed due to water lifting is found to decline with increasing efficiency of the cycle and is about 5% for maximum observed Carnot efficiencies. In the steady-state cycle, there is an extra heat input associated with the warming of precipitating water. The corresponding positive extra work is of an opposite sign and several times smaller than that due to water lifting. We also estimate the gain of kinetic energy in the outflow region. Contrary to previous assessments, this term is found to be large when the outflow radius is small (comparable to the radius of maximum wind). Using our framework, we show that Emanuel’s maximum potential intensity (E-PI) corresponds to a cycle where total work equals work performed at the top of the boundary layer (net work in the free troposphere is zero). This constrains a dependence between the outflow temperature and heat input at the point of maximum wind, but does not constrain the radial pressure gradient. We outline the implications of the established patterns for assessing real storms.

Integrating storm surge modeling with traffic data analysis to evaluate the effectiveness of hurricane evacuation

An integrated storm surge modeling and traffic analysis were conducted in this study to assess the effectiveness of hurricane evacuations through a case study of Hurricane Irma. The Category 5 hurricane in 2017 caused a record evacuation with an estimated 6.8 million people relocating statewide in Florida. The Advanced Circulation (ADCIRC) model was applied to simulate storm tides during the hurricane event. Model validations indicated that simulated pressures, winds, and storm surge compared well with observations. Model simulated storm tides and winds were used to estimate the area affected by Hurricane Irma. Results showed that the storm surge and strong wind mainly affected coastal counties in south-west Florida. Only moderate storm tides (maximum about 2.5 m) and maximum wind speed about 115 mph were shown in both model simulations and Federal Emergency Management Agency (FEMA) post-hurricane assessment near the area of hurricane landfall. Storm surges did not rise to the 100-year flood elevation level. The maximum wind was much below the design wind speed of 150–170 mph (Category 5) as defined in Florida Building Code (FBC) for south Florida coastal areas. Compared with the total population of about 2.25 million in the six coastal counties affected by storm surge and Category 1–3 wind, the statewide evacuation of approximately 6.8 million people was found to be an over-evacuation due mainly to the uncertainty of hurricane path, which shifted from south-east to south-west Florida. The uncertainty of hurricane tracks made it difficult to predict the appropriate storm surge inundation zone for evacuation. Traffic data were used to analyze the evacuation traffic patterns. In south-east Florida, evacuation traffic started 4 days before the hurricane’s arrival. However, the hurricane path shifted and eventually landed in south-west Florida, which caused a high level of evacuation traffic in south-west Florida. Over-evacuation caused Evacuation Traffic Index (ETI) to increase to 200% above normal conditions in some sections of highways, which reduced the effectiveness of evacuation. Results from this study show that evacuation efficiency can be improved in the future by more accurate hurricane forecasting, better public awareness of real-time storm surge and wind as well as integrated storm surge and evacuation modeling for quick response to the uncertainty of hurricane forecasting.

Seasonal Disparity in the Effect of Meteorological Conditions on Air Quality in China Based on Artificial Intelligence

Air contamination is identified with individuals’ wellbeing and furthermore affects the sustainable development of economy and society. This paper gathered the time series data of seven meteorological conditions variables of Beijing city from 1 November 2013 to 31 October 2017 and utilized the generalized regression neural network optimized by the particle swarm optimization algorithm (PSO-GRNN) to explore seasonal disparity in the impacts of mean atmospheric humidity, maximum wind velocity, insolation duration, mean wind velocity and rain precipitation on air quality index (AQI). The results showed that in general, the most significant impacting factor on air quality in Beijing is insolation duration, mean atmospheric humidity, and maximum wind velocity. In spring and autumn, the meteorological diffusion conditions represented by insolation duration and mean atmospheric humidity had a significant effect on air quality. In summer, temperature and wind are the most significant variables influencing air quality in Beijing; the most important reason for air contamination in Beijing in winter is the increase in air humidity and the deterioration of air diffusion condition. This study investigates the seasonal effects of meteorological conditions on air contamination and suggests a new research method for air quality research. In future studies, the impacts of different variables other than meteorological conditions on air quality should be assessed.

Characteristics of thunderstorms and squalls over Indira Gandhi International (IGI) airport, New Delhi - Impact on environment especially on summer’s day temperatures and use in forecasting

In the present study, commencement timings and duration of thunderstorms (TS) and squalls at IGI airport, Palam, New Delhi have been analysed critically based on most recent eleven years data of 1995-2005 to find their favourable time of occurrences. Then utility of such data base in the aviation warning has been demonstrated. Environmental changes associated with these squalls have also been further analysed to understand their impact. Being recent May 2007 a very cool month over Delhi, the role of TS on controlling the day’s soaring temperature has also been studied from their data. Results show TS are maximum in June followed by July whereas squalls are maximum in May followed by June. It shows more than 80% of TS in each season are of duration less than 3 hours with remaining are mostly 3 to 6 hours. The peak time period of commencement of both TS and squalls in the day differ with the progress of the months. For pre monsoon months, the most favourable timing of TS and squalls are 1200-1500 UTC while for monsoon, it starts earlier. Around 37% of the total TS during the period were associated with squalls. The average maximum wind speed in squall at IGI airport is about 68 kmph with highest maximum wind speed 139 kmph. On an average the environmental temperature falls by 5.6° C, humidity levels rises by 17.8% and mean sea level pressure rises by 1.6 hPa due to the occurrences of squalls. Study also shows daily maximum temperature rise is highly controlled by TS occurrences and May 2007, being a month of highest TS occurrences at the airport since 1995, became one of the coolest month in May over Delhi. The comparison of TS frequencies shows 12% increase in their annual activities since 1950-1980 with very high unusual increase of 51% in June and 26% in May. Since analysis of data from 1995 shows occurrences of TS are reversely but strongly correlated with summer temperatures and longer period temperature data since 1975 also confirms absence of significant trend in maximum temperature and higher temperature days in peak summer months of May and June till recent as expected due to high pollution, global warming and fast urbanization in the city, so it is the higher number of TS occurrences over the region from time to time which might have been main factor for controlling its significant rise.

Value addition in district level dynamical forecast during intense rainfall spells over the west coast of India

lkj & ekulwu _rq ds nkSjku Hkkjr ds if’peh rV ij Hkkjh o"kkZ dh ?kVukvksa dk vjc lkxj ds Åij iouksa dh vf/kdre xfr ds ØksM ¼dksj½ ds lkFk ?kfu"B laca/k gSA bl 'kks/k&i= esa bZ- lh- ,e- MCY;w- ,Q- ¼;wjksih; e/;e vof/k iwokZuqeku dsUnz½ }kjk 850 gSDVkikLdy ij iwokZuqekfur 72 ?kaVs ds izokg izfr:i dk mi;ksx fd;k x;k gS ftlls if’peh rV ij Hkkjh o"kkZ dk iwokZuqeku djus ds fy, ftyk Lrjh; xfrdh; iwokZuqeku iz.kkyh dh {kerk c<+kus gsrq ek=kRed i)fr dk fodkl fd;k tk ldsA ;g ns[kk x;k gS fd if’peh rV ij o"kkZ dh ek=k dk if’peh rV ij vjc lkxj esa iou dh vf/kdre xfr ds 72 ?kaVs ds bZ- lh- ,e- MCY;w- ,Q- }kjk fd, x, iwokZuqeku ds lkFk egRoiq.kZ lglaca/k gSA if’peh rV ij Hkkjh o"kkZ ds {ks= ds v{kka’kh; foLrkj dk if’peh rV ij iou dh vf/kdre xfr ds ØksM ¼dksj½ ds lkFk egRoiw.kZ lglaca/k gSA bl 'kks/k&i= esa ;g crk;k x;k gS fd xzh"edkyhu ekulwu _rq ds nkSjku Hkkjr ds if’peh rV ij Hkkjh o"kkZ ds 72 ?kaVs dk iwokZuqeku djus ds fy, iouksa dh vf/kdre xfr ds 72 ?kaVs ds iwokZuqekfur ØksM ¼dksj½ vkSj foLrkj dh rhozrk vkSj fLFkfr dh {kerk c<+kus ds fy, laHkkfor iwoZlwpdksa ds :i esa mi;ksx fd;k tk ldrk gSA Occurrences of intense rainfall events over west coast of India during monsoon are intimately linked to the core of maximum winds over the Arabian Sea. ECMWF (Europian Centre for Medium Range Weather Forecasting ) predicted 72 hr flow pattern at 850 hPa has been used to develop a quantitative method for value addition in the district level dynamical forecast system for intense rainfall over the west coast. It has been found that the amount of rainfall over the west coast is significantly correlated to 72 hr ECMWF forecast of maximum wind speed over the Arabian Sea along the west coast. The latitudinal width of the heavy rainfall belt over the west coast has got significant correlation with the location of maximum wind core along the west coast. It has been shown that the strength and location of the 72 hr predicted core and fetch of maximum winds could be used as potential predictors in the value addition for 72 hr heavy rainfall forecast along the west coast of India during summer monsoon.

Some climatological aspects of thunderstorms and squalls over Guwahati Airport

Lkkj & xqokgkVh gokbZ vM~Ms ij vk, paMokr ls tqM+s okf"kZd vkSj ekfld ckjEckjrk dk forj.k] xtZ ds lkFk vk, rwQkuksa vkSj paMokrksa ds vkjEHk gksus dk le; vkSj mudh vof/k rFkk i;kZoj.kh; ifjorZuksa dk fo’ys"k.k fd;k x;k gSA rwQku vkSj paMokr lcls T;knk ebZ ds eghusa esa vkrs gSa vkSj mlds ckn viSzy ds eghus esa vkrs gSaA rwQkuksa vkSj paMokrksa dh vko`fr;k¡ lcls T;knk ebZ ds eghusa esa gksrh gSa vkSj mlds ckn vizSy ds eghus esa gksrh gSaA vf/kdk¡’k rwQku ekulwu _rq ls iwoZ vkSj ekulwu _rq ds nkSjku vkrs gSa rFkk paMokr Qjojh ls ebZ ds eghuksa ds nkSjku vkrs gSaA ekulwu _rq ls iwoZ vkus okys vf/kdk¡’k rwQku e/; jkf= ls ysdj rM+ds lqcg ds le; esa vkrs gSa tcfd ekulwu _rq ds nkSjku vkus okys rwQku 0600&1200 ;w- Vh- lh- ds chp vk;k djrs gSa vf/kdk¡’k rwQkuksa dh vof/k rhu ?kaVksa ls Hkh de dh gksrh gSA vf/kdk¡’k paMokrksa dh vof/k pkj feuVksa ls Hkh de dh gksrh gS] fn’kk mÙkj if’pe vkSj ;s 0900&2100 ;w- Vh- lh- ds le; vkrs gSaA xqokgkVh gokbZ vM~Ms ij paMokr ds vkus ls i;kZoj.kh; rkieku vkSlru 2-2° lsa- rd fxj tkrk gS] lkisf{kd vknzZrk 8-5 izfr’kr rd c<+ tkrh gS vkSj nkc 1-6 gSDVkikLdy rd c<+ tkrk gSA xqokgkVh gokbZ vM~Ms ij paMokr ds vkus ls vf/kdre iou xfr vkSlru yxHkx 39 ukWV~l gksrh gSA fiNys v/;;uksa ls rqyuk djus ij ;g irk pyrk gS fd fiNys dqN o"kksZa esa rQkuksa vkSj paMokrksa ds y{k.kksa esa fo’ks"k ifjorZu ugha vk;k gSA The annual and monthly frequency distribution, time of commencement and duration of thunderstorms & squalls and environmental changes associated with occurrence of squall at Guwahati Airport have been analyzed. The frequencies of thunderstorms and squalls are maximum in the month of May followed by April. Most of the thunderstorms occur during premonsoon and monsoon season and squalls occur during Feb-May. Most of the premonsoon thunderstorms commence during midnight to early morning while the thunderstorms during monsoon season have preference to commence between 0600-1200 UTC. Majority of thunderstorms is of the duration of less than three hours. Majority of squalls have the duration of less than four minutes, direction as northwesterly and occur during 0900-2100 UTC. On the average, environmental temperature falls by 2.2° C, the relative humidity rises by 8.5%, and the pressure increases by 1.6 hPa due to squall over Guwahati Airport. The average maximum wind speed associated with a squall over Guwahati Airport is about 39 knots. Comparison with the past studies indicates that characteristics of thunderstorms and squalls have not changed significantly over the years.

The comparison of two parametric wind models for hurricane storm surge prediction

The tropical storm surge models depend critically on the maximum surface wind and shape of the wind profile. Since none of them are easy to measure, designing the parametric wind models for the storm surge prediction becomes divergent. Two widely used, but very different, wind models are examined. The study of their parameters showed that their resulting maximum wind and the shape of the wind profiles are similar. This property is a very useful guide for evaluating different surge models.