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Heat wave of 2015 over India, a natural disaster with 2500 human deaths, was studied to understand the characteristics, associated atmospheric circulation patterns and to evaluate its predictability. Although temperatures are highest in May over India, occurrence of heat wave conditions over southeast coastal parts of India in May 2015 had been unanticipated. Analyses revealed that isolated region of Andhra Pradesh (AP) had experienced severe heat wave conditions during May 23–27, 2015, with temperatures above 42 °C and the sudden escalation by 7–10 °C within a short span of 2–3 days. Short-range weather predictions with Advanced Research Weather Research and Forecasting model at 3-km resolution, up to 72-h lead time, have been found accurate with statistical metrics of small mean absolute error and root-mean-square error and high index of agreement confirming the predictability of the heat wave evolution. Analyses have indicated that regional atmospheric pressure disparities within the Eurasia region, i.e., increased pressure gradient between the Middle East and India, had been responsible for increased northwest wind flow over to northwest India and to southeast India which have advected higher temperatures. Estimates of warm air advection have shown heat accumulation over AP region, due to sea breeze effect. The study led to the conclusion that changing pressure gradients between Middle East and India, enhancement of northwest wind flow with warm air advection and sea breeze effect along southeast coast blocking the free flow have contributed to the observed heat wave episode over coastal Andhra Pradesh.  相似文献   
2.
Climate Dynamics - The present study explored the performance of the current coupled models obtained from the Asia Pacific Economic Cooperation (APEC) Climate Centre (APCC) in representing the...  相似文献   
3.
Ensemble prediction methodology based on variations in physical process parameterizations in tropical cyclone track prediction has been assessed. Advanced Research Weather Research and Forecasting model with 30-km resolution was used to make 5-day simulation of the movement of Orissa super cyclone (1999), one of the most intense tropical cyclones over the North Indian Ocean. Altogether 36 ensemble members with all possible combinations of three cumulus convection, two planetary boundary layer and six cloud microphysics parameterization schemes were produced. A comparison of individual members indicated that Kain–Fritsch cumulus convection scheme, Mellor–Yamada–Janjic planetary boundary layer scheme and Purdue Lin cloud microphysics scheme showed better performance. The best possible ensemble formulation is identified based on SPREAD and root mean square error (RMSE). While the individual members had track errors ranging from 96–240 km at 24 h to 50–803 km at 120 h, most of the ensemble predictions show significant betterment with mean errors less than 130 km up to 120 h. The convection ensembles had large spread of the cluster, and boundary layer ensembles had significant error disparity, indicating their important roles in the movement of tropical cyclones. Six-member ensemble predictions with cloud microphysics schemes of LIN, WSM5, and WSM6 produce the best predictions with least of RMSE, and large SPREAD indicates the need for inclusion of all possible hydrometeors in the simulation and that six-member ensemble is sufficient to produce the best ensemble prediction of tropical cyclone tracks over Bay of Bengal.  相似文献   
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The roles of vortex initialization and model spin-up in tropical cyclone (TC) prediction using Advanced Research Weather Research and Forecasting (ARW) Model are studied through a case study of NARGIS (2008) cyclone over Bay of Bengal. ARW model is designed to have three two-way interactive nested domains, and a suite of 36 numerical experiments are performed with three values of maximum wind (MW), four of radius of maximum wind (RMW), and three of α and one experiment without vortex initialization. The results indicate that vortex initialization is important toward realistic representation of initial structure and location of cyclone vortex. Model spin-up during the first 18–24 h of model integration lead to faster intensification than of the real atmosphere, thus a weaker initial vortex evolved more realistically. Three experiments from vortex initialization produced MW and RMW nearer to the observations, but none of these produced a good prediction due to unrealistic intensification during model spin-up. A weaker vortex with intensity less than 50 % than observations produced the best forecast in terms of intensity, track, and landfall. The results suggest that slightly larger (~30 %) RMW than observations with α as ?0.5 (for 81 km model resolution) that produces weaker vortex is to be implemented in the design of bogus vortex. This study assesses the merits of TC bogus scheme in ARW model, illustrates the need for vortex initialization, and analyzes the spin-up problem in cold-start model simulations of TC prediction.  相似文献   
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