User:Dr G China Satyanarayana/sandbox

Figure 1: (Spatial Distribution of Mean surface Maximum Temperature (a-c); frequencies of days with surface maximum temperatures above 40oC/year (d-f); above 42oC days/year from March to May over Indian Subcontinent). (Reference: An accentuated “hot blob” over Vidarbha, India, during the pre-monsoon season. Nat Hazards 105, 1359–1373 (2021). https://doi.org/10.1007/s11069-020-04357-2)

Salient Research Achievements: 	The highest temperatures and maximal frequencies of hot days are found to be occurring over south-central parts of India, i.e. Vidarbha and Telangana. The maximum over Vidarbha, christened as “hot blob”, is established. This is in contrast to the generally anticipated high temperatures over Rajasthan due to higher insolation and its desert surface. 	The horizontal temperature advection at lower levels shows a distinct convergence zone that causes accumulation of heat, supported by local surface heating of black soil giving rise to the “hot blob” over Vidarbha. 	The atmospheric flow patterns during March and April, with two high-pressure zones over the Arabian Sea and Bay of Bengal forming an east–west oriented ridge over the “tropic of cancer” with a “COL” region, were noted to be the reason for the accumulation of heat over Vidarbha and Telangana. 	Days with the highest average frequency of 14–20 days were noted over the zone of “hot blob” during the May month, and from the spatial distribution plot, it is clear that the regions of the south-central parts are the warmest when compared to the rest of the Indian subcontinent. This finding of the isolated hotspot will be useful to comprehend the occurrence of heatwaves over south-east coastal regions. (Reference: An accentuated “hot blob” over Vidarbha, India, during the pre-monsoon season. Natural Hazards 105, 1359–1373 (2021). https://doi.org/10.1007/s11069-020-04357-2) Figure 2: Spatial distributions of (a) mean maximum surface air temperatures (°C) and (b) average number of days with maximum temperatures exceeding 42 °C for May. Maximum temperature zones are marked as boxes and labelled in (b); Spatial distributions of the number of days with mean temperatures ≥40 °C (>37 °C) for plains (coastal zones) and anomalies (c) above 4 °C and (d) above 5 °C days during May as accumulated for the period from 1951 to 2015. Heat wave zones are marked as boxes and labelled in (d)). (Reference: Phenology of heat waves over India. Atmospheric Research. 245. 105078. 10.1016/j.atmosres.2020.105078.(2020)) Research Outcomes: 	Analysis of surface maximum temperatures revealed three regions of maximum, over West Rajasthan; North Madhya Pradesh and South-west Uttar Pradesh; and East Maharashtra (Vidarbha). 	The number of days with temperatures higher than 42 °C has also depicted the identified three regions (T1, T2 and T3) of maximum temperatures to have highest frequencies. 	Analysis of heat wave periods considering the IMD criteria for the occurrence of heat wave condition, divulged three distinct regions over north (HW1), northeast (HW2) and southeast parts of India (HW3). Importantly, these three regions are different from the regions of maximum temperatures. This inference connotes the regions of maximum temperatures are not the heat wave locations but they induce the heat waves through downwind advection under favourable atmospheric conditions. 	Analysis of heat wave periods, considering the IMD criteria, had revealed the occurrences of heat waves were more with 34 (182 days) over Northeast; 31 (165 days) over North; and are 21 (111 days) over Southeast parts of India. 	 An important result of this study is that the occurrence of heat waves over Southeast India have been noticed since 1970, which imply that the initiation in 1970s may be due to global warming trends. This result agrees with Ross et al. (2018) who reported the observation of heat waves since 1970s over Southeast India during the current global warming. 	The duration of heat waves over Southeast India, on par with those over northeast and north, signify higher vulnerability of the Southeast India due to larger anomalous temperatures where the climate mean temperatures are lower than over North India.

Figure 3: Mean 10-m level wind flow and 2-m level air temperatures (oC) corresponding to 0900 UTC for May. Wind vector length denote wind speed at 1 cm equal to 15 m/sec. (Reference: Phenology of heat waves over India. Atmospheric Research. 245. 105078. 10.1016/j.atmosres.2020.105078.(2020)) Salient Research Achievements: Analysis of wind flow over larger South Asia domain show the westerly/ south-westerly wind flow from Middle East bring in hot air into the Indian subcontinent through northwest parts. The desert region of Northwest India thus records highest temperatures. However, northwest winds advect heat from the northwest to the central parts of India. It is observed that the wind flow below 850 hPa is sustained north-westerly/ west-north-westerly to the west of the heat wave region. This flow pattern indicates the advection of heat from the observed maximum temperature region over T2 zone and reduction of strength to the east of HW2 zone lead to the accumulation of heat over the HW2 region. This west-northwest wind flow over the HW2 region indicates strengthening of the mean northwest wind flow during the period of the heat wave. Thus predominant westerly component is identified to be responsible for the occurrence of heat waves over this region.

Reference: Phenology of heat waves over India. Atmospheric Research. 245. 105078. 10.1016/j.atmosres.2020.105078.) Analysis of anomalous winds during the heat wave periods over the three vulnerable regions, revealed that anomalous south-westerly, westerly/ north-westerly and north-westerly wind flow from the high temperature regions of West Rajasthan (T1), Northwest Madhya Pradesh, Southwest Uttar Pradesh (T2) and East Maharashtra (T3) contribute to the onset of heat waves over North (HW1), Northeast (HW2) and Southeast (HW3) parts of India respectively.

(Reference: An accentuated “hot blob” over Vidarbha, India, during the pre-monsoon season. Nat Hazards 105, 1359–1373 (2021). https://doi.org/10.1007/s11069-020-04357-2) The spatial distributions of mean monthly (March, April and May) horizontal temperature divergence (∇ ⋅ VT) at 925 hPa level are computed and presented in Fig. 5a. In March, heat convergence was noted over south-central India with a maximum over Vidarbha (magnitude of 2×10–4/s) extending towards north-west and south peninsula. Heat divergence was noted over the Arabian Sea and Bay of Bengal and over continental North India. The same trend continued in April but with increased magnitude of convergence over Vidarbha (3×10–4/s) and formation of a weak convergence centre over north-west India. In contrast, the divergence over the Arabian Sea and Bay of Bengal remained the same as of March. In May, the convergence centres over Vidarbha and north-west became concentric with slightly increased magnitude. The divergence over the Arabian Sea moved inland covering the Western Ghats and the divergence over North India increased in magnitude. All these features indicate culmination of heat accumulation over south-central and north-west parts and heat divergence over North India. The mean of three months follows the features of May due to higher magnitudes. The atmospheric flow patterns during March and April, with two high-pressure zones over the Arabian Sea and Bay of Bengal forming an east–west oriented ridge over the “tropic of cancer” with a “COL” region, were noted to be the reason for the accumulation of heat over Vidarbha and Telangana as given in Fig. 5b. This synoptic regime confirms the earlier studies of Subbaramayya et al. (1988). (Reference: An accentuated “hot blob” over Vidarbha, India, during the pre-monsoon season. Nat Hazards 105, 1359–1373 (2021). https://doi.org/10.1007/s11069-020-04357-2) Analysis of simulated surface maximum temperatures from five different NEX-GDDP generated from model climate simulations under CMIP5 program disclosed that all of the model simulations show maximum temperatures and higher frequency hot days over Vidarbha, India, during March to May confirming the results from gridded data analysis. The results of this study conclusively bring out the presence of a “hot blob”, the hottest region of the Indian subcontinent, i.e. to be over “Vidarbha” situated in the south-central parts. Estimation of frequency days surpassing 40 °C also displays maximum over south-central India agreeing with the observed maximum in the analysis of grid data over the same region. The model simulations show that the entire month of May would have temperatures higher than 40 °C over Vidarbha. These analyses supplement the gridded data analysis to identify and establish a heat maximum over Vidarbha as model simulations produce the features of atmosphere conforming to the physics and dynamics of climate models. Model simulation results confirm and emphasize the observed heat maximum over Vidarbha, affirming the identification of “hot blob”. (Reference: Heat wave characteristics over India during ENSO events in Journal of Earth Science System (Under Review (minor comments accepted (2021)) This study investigates the heat wave characteristics during El Nino (PEN), El Nino (EN) and succeeding El Nino (SEN) events using daily maximum and minimum temperature gridded data from IMD. The intensity, duration, frequency and area of extent of heat waves and how do they vary during PEN, EN and SEN years also carried out. Some of the important findings of this study include: (i). The climatological mean of maximum temperature is evident that the maximum temperatures are higher than of 1-2oC over north and central parts of India with respect to west Rajasthan. (ii). The frequency of heat waves with above 42oC gives a clear identification of the three isolated hotspot regions, namely northwest Madhya Pradesh, southwest Uttar Pradesh and east Maharashtra (Satyanarayana and Dodla 2020). (iii). The frequency of heat wave days with climatological mean+4oC is maximum during May over the southeastern parts. (iv). It was observed that heat wave events during SEN years intensify compared with the events during EN and PEN years. Also, the duration of heat wave events extends (shorten) during SEN (EN and PEN) over many parts of Indian subcontinent. (v). The composite anomalies of mean maximum temperature, the frequency of days above 42oC and heat wave (>40oC & mean+4oC) days are higher than normal during SEN and cool during EN years all over the Indian subcontinent. Still,over northeast India reverse phenomena is observed. (vi). Composite analysis of minimum temperature is higher than the normal during SEN and lower during EN years. Also during PEN minimum temperatures and heat wave days were higher over south-eastern parts of the country. (vii). Observed the synoptic features associated with heat waves during PEN, EN, and SEN from composite anomalies of zonal wind at 925 hPa, and it is evident that westerlies strengthen in SEN over the Indian subcontinent except over northeast India, which is the reason for the occurrence of more heat waves over these regions. Soil moisture anomalies regulate India's heat waves, which mean that maximum temperatures increase when soil moisture decreases and vice versa. (viii). Positive anomalies of SST are associated with warm temperatures over the Bay of Bengal and the Arabian Sea during PEN and SEN years. The above results indicate that the observed QBO and ENSO phenomenon clearly reflects the above 42oC days and heat wave frequencies over India. It might be interesting to explore the periodicities of the surface maximum temperatures. Figure 8: Spatial distributions of model predicted 2-m-level temperatures (oC) at 0900 UTC over Andhra Pradesh with lead times of 24- (Day 1); 48- (Day 2), and 72-h (Day 3) for each of the days during May 23–26, 2015. (Reference: Analysis and prediction of a catastrophic Indian coastal heat wave of 2015; Nat. Hazards 87:395–414. https://doi.org/10.1007/s11069-017-2769-7.(2017)) In this study, a heat wave episode of May, 2015 over India that caused about 2500 human deaths is investigated. The characteristics of the heat wave have been established and corresponding changes in the atmospheric circulation patterns have been identified. The dynamical and thermodynamical reasons for the evolution of the heat wave have been explored and the predictability of the life cycle of the heat wave using a high resolution atmospheric model has been demonstrated. The characteristics of the HW under study were noted to be that the Central Andhra Pradesh (AP, located on the southeast coast of India) region had abnormal high temperatures exceeding 43 C, with anomalies of 4-6 C for 4 consecutive days of 23-26 May, 2015. The HW under study has been systematically investigated using different data sets. Analysis of temperatures over Eurasia during May indicated extreme hot region with temperatures higher than 40 C over the Middle East, Pakistan and Northwest India within a wider hot region extending west-east from North Africa to Central India. Corresponding mean wind flow shows two distinct branches, one from Kazakhstan in North and another from the Middle East region in the west, culminating to bring in the northwesterly wind flow over to northwest India. Spatial distributions of maximum temperature during the second half of May, 2015 have shown that hot region with temperatures higher than 40 C present over Northwest India gradually extended towards the southeast, due to  prevailing northwest winds, over to central parts and coastal AP region. Temperatures exceeding 43 C had been noted over the central AP region during 23-26 May. Although temperatures higher than 43 C were present over a wider region from northwest to southeast parts of India, HW conditions were identified over the AP region only. The central AP region had anomalies of 5-7 C, implying the existence of severe HW conditions. Analysis of time series of maximum temperatures during 1-31 May at several locations over AP brought out that the temperatures were below normal (by about 2 C) at most of the stations during the first half of May and increased suddenly to 4-7 C above normal during the second half of May. This manifests a sudden rise of temperatures from 7-10 C within 2-3 days increasing the impact and perhaps been the main reason for unexpected human deaths in large numbers. In order to understand the role of atmospheric circulations, the differences in the surface pressure, temperature and wind distributions during the two fortnight periods of 1-15 and 16-31 May have been studied. The study revealed that the high pressure regions over Kazakhstan and Russia have been weaker and the high pressure over North Africa intensified and the low pressure over India had weakened during the first fortnight of May, 2015. Contrastingly, during the latter half of May, low pressure over India slightly strengthened and pressures over Middle East increased, implying an increased pressure gradient between Middle East and India and that the pressures have decreased over Kazakhstan signify decreasing North-South gradient during the second fortnight. This analysis emphasizes that the anomalous warming over Middle East lead to increased pressure gradients between Middle East and India and strengthening of northwest flow over to northwest India, which had contributed to the observed HW over AP on the east coast. Further an attempt has been made to predict the HW under study using an ARW model with 3-km resolution for lead times up to 72-hours. The results indicated that the model predicted the evolution of the HW accurately and the model evaluation confirmed the model performance as evidenced by small values of mean absolute error, root mean square error and high index of agreement. The present study is a maiden attempt to predict one of the recent heat wave episodes over India using ARW high resolution atmospheric model. The results demonstrate the usefulness of ARW model in predicting the near surface temperatures and the heat wave conditions with a lead time of 72-hours. The model errors in predicting the 2-m level temperatures are noted to be very small as compared to corresponding predictions with WRF model over other parts of the world. The model results were used to further understand the dynamical reasons for the heat wave. Analysis of temperature advection have brought out an interesting and important dynamical reason for the particular vulnerability of the coastal region as that the northwest flow brought in warm air advection from warmer Northwest India over to central and southeast parts and the advection was continuous with no accumulation all along but as the warm advection reached coastal region, sea breeze effect curtailed the warm air advection further and contributed to accumulation of heat near the coast. It is known that coastal regions are cooler than in-land stations due to proximity to the sea and the effect of sea breeze during daytime, but the same sea breeze effect has contributed to the observed HW over coastal AP region during the latter fortnight of May, 2015. It has been inferred from dynamical analysis that accumulation of heat (convergence of V*T) had occurred over the heat wave region and synoptically, northwesterly wind flow advected higher temperatures from Rajasthan (Northwest India) towards the coast of Andhra Pradesh, where the presence of opposing sea breeze across the coastline contributed for the heat accumulation culminating as the observed heat wave episode. Keeping in view of the important inference from this study, detailed investigations of earlier heat waves over India would be taken up as a continuation of this research. Efforts will be made to investigate the heat waves over other parts of the globe to examine if similar dynamical reasons have been responsible for the coastal heat waves. Although heat waves are known to occur all over the globe, their exacerbation in the global warming scenario made their understanding and prediction important for management of their impact. The authors concede that the results of the present study pertain to only one case study and suggest that modeling studies of several heat waves are to be made to complement and confirm the results of the present study.