Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.3880
CHAOJIU DA, TAI CHEN, BINGLU SHEN, JIAN SONG
In this paper, preliminary theoretical research on abrupt change induced by the forcing term in a dynamical system is described. Taking the Lorenz equationtrajectoryasthe research object, the trajectory response to different pulse forcing terms is studied based on the stability theorem of differential equations and numerical methods. From the perspective of a dynamical system, abrupt changecan be classified as internal or external. The former reflectstrajectory self-adjustment inside the attractor, whereasthe latter represents the bizarre behaviorof the trajectoryin its deviation from the attractor. This classification helps in understanding the physical mechanisms of different manifestations of atmospheric abrupt change. For different intensities and durations of the pulse forcing term,which are simplified to the magnitude and width of a rectangular wave, respectively, the corresponding abrupt change is analyzed quantitatively. It is established that the larger the amplitude of the pulse forcing term, the greater the deviation of thetrajectory from the attractor and the more violent theabrupt change. Moreover, the greater the width of the pulse forcing term, the longer the duration over which the trajectory deviates from the attractor. Finally, two simple but meaningful linear relationships are obtained: one between the amplitude of the pulse forcing term and the distance of trajectory deviation from the attractor, and the other between the width of the pulse forcing term and the duration over which the trajectory dwells outside of the attractor. These relationships indicate that nonlinear systems have some linear properties.
{"title":"Classification and characteristics of abrupt change based on the Lorenz equation","authors":"CHAOJIU DA, TAI CHEN, BINGLU SHEN, JIAN SONG","doi":"10.54302/mausam.v74i4.3880","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.3880","url":null,"abstract":"In this paper, preliminary theoretical research on abrupt change induced by the forcing term in a dynamical system is described. Taking the Lorenz equationtrajectoryasthe research object, the trajectory response to different pulse forcing terms is studied based on the stability theorem of differential equations and numerical methods. From the perspective of a dynamical system, abrupt changecan be classified as internal or external. The former reflectstrajectory self-adjustment inside the attractor, whereasthe latter represents the bizarre behaviorof the trajectoryin its deviation from the attractor. This classification helps in understanding the physical mechanisms of different manifestations of atmospheric abrupt change. For different intensities and durations of the pulse forcing term,which are simplified to the magnitude and width of a rectangular wave, respectively, the corresponding abrupt change is analyzed quantitatively. It is established that the larger the amplitude of the pulse forcing term, the greater the deviation of thetrajectory from the attractor and the more violent theabrupt change. Moreover, the greater the width of the pulse forcing term, the longer the duration over which the trajectory deviates from the attractor. Finally, two simple but meaningful linear relationships are obtained: one between the amplitude of the pulse forcing term and the distance of trajectory deviation from the attractor, and the other between the width of the pulse forcing term and the duration over which the trajectory dwells outside of the attractor. These relationships indicate that nonlinear systems have some linear properties.
","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.5903
GAURAV YADAV, GEETA SINGH, S.D. ATTRI
The continuous change in climatic conditions has created a very difficult situation for the people living all over the world. The cities with higher population and poor air quality have been hard hit by the rising temperature and humidity, bad air quality of an urban environment plays a significant role in affecting climatic variables. As Delhi, the capital of India, tops the list of air pollution hotspots among all top polluted cities around the world is selected for this study. Through this study a relationship was assessed, among criteria air pollutants and meteorological parameters. It was hypothesized that criteria air pollutants will positively predict the change in temperature and relative humidity (pillars of climate change) during daily dataset(January 01, 2015 – December 31, 2021) and average annual dataset (2000 to 2021) in Delhi. To test this hypothesis, elastic net-applied regularization has been used in model exploration and coefficient estimation using EVIEWS 12. It was found that during the selected study period, most of the criteria air pollutants were playing a significant role in increasing the changes in climatic conditions of Delhi. This research further explains about the interlinkage between air pollution and climate change with the help of available literature.
{"title":"Poor air quality as an important predictor of climate change in Delhi","authors":"GAURAV YADAV, GEETA SINGH, S.D. ATTRI","doi":"10.54302/mausam.v74i4.5903","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.5903","url":null,"abstract":"The continuous change in climatic conditions has created a very difficult situation for the people living all over the world. The cities with higher population and poor air quality have been hard hit by the rising temperature and humidity, bad air quality of an urban environment plays a significant role in affecting climatic variables. As Delhi, the capital of India, tops the list of air pollution hotspots among all top polluted cities around the world is selected for this study. Through this study a relationship was assessed, among criteria air pollutants and meteorological parameters. It was hypothesized that criteria air pollutants will positively predict the change in temperature and relative humidity (pillars of climate change) during daily dataset(January 01, 2015 – December 31, 2021) and average annual dataset (2000 to 2021) in Delhi. To test this hypothesis, elastic net-applied regularization has been used in model exploration and coefficient estimation using EVIEWS 12. It was found that during the selected study period, most of the criteria air pollutants were playing a significant role in increasing the changes in climatic conditions of Delhi. This research further explains about the interlinkage between air pollution and climate change with the help of available literature.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.5381
RAKHEE SHARMA, ARCHANA SINGH, MAMTA MITTAL
For the timely planning and management of water resources, evaporation prediction must be estimated properly, especially in regions that are prone to drought and where evaporation directly affects the pest population. Changes in meteorological variables such as temperature, relative humidity, solar radiation, rainfall have a great impact on the evaporation process. In order to forecast the variable, ensemble feature selection techniques along with various machine learning techniques were investigated. Meteorological weekly weather data were collected from the ICRISAT location over a period from 1974 to 2021. The reliability of these developed models was based on statistical approaches namely Mean Absolute Error, Root Mean Square Error, Coefficient of Determination, Nash–Sutcliffe Efficiency coefficient, and Willmott’s Index of agreement along with several graphical aids. The results indicate that lasso regression outperforms all other machine learning approaches and the results are validated using current data (2020-2021). For a better understanding of the results, these validated results were also compared with results obtained from the established linear regression method and artificial neural network. It was further found that lasso regression shows an improved performance (R2 = 0.929) over linear regression (R2 = 0.871) and artificial neural network (R2 = 0.889).
{"title":"Efficient prediction of evaporation using ensemble feature selection techniques","authors":"RAKHEE SHARMA, ARCHANA SINGH, MAMTA MITTAL","doi":"10.54302/mausam.v74i4.5381","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.5381","url":null,"abstract":"For the timely planning and management of water resources, evaporation prediction must be estimated properly, especially in regions that are prone to drought and where evaporation directly affects the pest population. Changes in meteorological variables such as temperature, relative humidity, solar radiation, rainfall have a great impact on the evaporation process. In order to forecast the variable, ensemble feature selection techniques along with various machine learning techniques were investigated. Meteorological weekly weather data were collected from the ICRISAT location over a period from 1974 to 2021. The reliability of these developed models was based on statistical approaches namely Mean Absolute Error, Root Mean Square Error, Coefficient of Determination, Nash–Sutcliffe Efficiency coefficient, and Willmott’s Index of agreement along with several graphical aids. The results indicate that lasso regression outperforms all other machine learning approaches and the results are validated using current data (2020-2021). For a better understanding of the results, these validated results were also compared with results obtained from the established linear regression method and artificial neural network. It was further found that lasso regression shows an improved performance (R2 = 0.929) over linear regression (R2 = 0.871) and artificial neural network (R2 = 0.889).","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.6404
J. P. GUPTA, A. H. WARSI, PRADEEP SHARMA
Premonsoon season over Uttar Pradesh is characterized withthunderstorm accompanied with rain, dust storm, gale winds and hail storms etc. These storms generally develop locally in association with convection and moisture convergence and seen as single cells in Doppler Weather Radar, but sometime these thunderstorms are associated with synoptic scale systems viz. Western Disturbance as cyclonic circulation/trough, induced low/ cyclonic circulation or northwest-southeast oriented trough, thereby increasing the spatial extent and severity of these thunderstorms significantly. In the present study, Duststorm/Thunderstorm activity that occurred over the state on large scale on 13th May 2018 and which claimed more than 49 human lives and large number of livestock in Uttar Pradesh has been analyzed. The purpose of this study wasto find out probable dynamic and thermodynamic aspects of this activity. The study indicates that the environment was highly favourable thermodynamically for severe thunderstorm activity with high maximum temperatures (>40C), high CAPE(>1000), high Total Total Index(>50) and high negative Lifted Index values (<-5) over most parts of the northwest Indian plains. The moisture discontinuity line was clearly noticed over south Uttar Pradesh with high moisture contents towards its north. Also 00UTC GFS wind analysis of the day at 925hPa indicated strong southeasterlies of the order of 30-35Kts over Uttar Pradesh resulting high moisture incursion in the lower levels over this region. The Low level wind shear was also high and was about 25-30Kt as evident from Skew-T gram of Lucknow for 12UTC of the day taken from Wyoming site as well as 12UTC wind shear analysis using ERA Interim daily data of ECMWF on 13 May, 2018. These features together with synoptic conditions viz; Western Disturbance (WD) in mid and upper levels and a Cyclonic Circulation (cycir) over south Haryana & neighbourhood as well as an east-west trough extending from this cycir in the lower levels made the environment highly favourable for severe thunderstorm activity over the region.
北方邦季风前季节的特点是雷暴伴有降雨、沙尘暴、大风和冰雹等。这些雷暴通常在局部与对流和水汽辐合有关，在多普勒天气雷达中被视为单体，但有时这些雷暴与天气尺度系统有关，即西部扰动作为气旋环流/槽，诱导低/气旋环流或西北-东南方向的槽，从而显著增加了这些雷暴的空间范围和严重程度。在本研究中，对2018年5月13日发生在北方邦的大规模沙尘暴/雷暴活动进行了分析，该活动造成北方邦49多人死亡和大量牲畜死亡。这项研究的目的是找出这种活动可能的动力学和热力学方面。研究表明，西北印度平原大部分地区具有高最高气温(>40C)、高CAPE(>1000)、高Total Total Index(>50)和高负抬升指数(<-5)的强雷暴活动的热力环境。水汽不连续线在北方邦南部明显可见，其北部水分含量高。此外，00UTC GFS对当天925hPa的风分析显示，北方邦上空有30-35Kts的强烈东南风，导致该地区低层有高水汽侵入。低层风切变也很高，约为25-30Kt，这可以从怀俄明州站点当天12UTC的勒克诺偏t克以及ECMWF 2018年5月13日ERA中期每日数据的12UTC风切变分析中看出。这些特征连同天气条件，即;中高层的西部扰动(WD)和哈里亚纳邦南部上空的气旋环流(cyclar)邻近地区以及从低空环流中延伸出来的东西向低槽为该地区的强雷暴活动提供了非常有利的环境。
{"title":"Severe dust storm/thunderstorm activity over Uttar Pradesh on 13th May, 2018 - A case study","authors":"J. P. GUPTA, A. H. WARSI, PRADEEP SHARMA","doi":"10.54302/mausam.v74i4.6404","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.6404","url":null,"abstract":"Premonsoon season over Uttar Pradesh is characterized withthunderstorm accompanied with rain, dust storm, gale winds and hail storms etc. These storms generally develop locally in association with convection and moisture convergence and seen as single cells in Doppler Weather Radar, but sometime these thunderstorms are associated with synoptic scale systems viz. Western Disturbance as cyclonic circulation/trough, induced low/ cyclonic circulation or northwest-southeast oriented trough, thereby increasing the spatial extent and severity of these thunderstorms significantly. In the present study, Duststorm/Thunderstorm activity that occurred over the state on large scale on 13th May 2018 and which claimed more than 49 human lives and large number of livestock in Uttar Pradesh has been analyzed. The purpose of this study wasto find out probable dynamic and thermodynamic aspects of this activity. The study indicates that the environment was highly favourable thermodynamically for severe thunderstorm activity with high maximum temperatures (>40C), high CAPE(>1000), high Total Total Index(>50) and high negative Lifted Index values (<-5) over most parts of the northwest Indian plains. The moisture discontinuity line was clearly noticed over south Uttar Pradesh with high moisture contents towards its north. Also 00UTC GFS wind analysis of the day at 925hPa indicated strong southeasterlies of the order of 30-35Kts over Uttar Pradesh resulting high moisture incursion in the lower levels over this region. The Low level wind shear was also high and was about 25-30Kt as evident from Skew-T gram of Lucknow for 12UTC of the day taken from Wyoming site as well as 12UTC wind shear analysis using ERA Interim daily data of ECMWF on 13 May, 2018. These features together with synoptic conditions viz; Western Disturbance (WD) in mid and upper levels and a Cyclonic Circulation (cycir) over south Haryana & neighbourhood as well as an east-west trough extending from this cycir in the lower levels made the environment highly favourable for severe thunderstorm activity over the region.
","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.805
CHANDRAN S., SELVAN P., NAMITHA M. R., PRADEEP MISHRA, KUMAR V.
A 34-year rainfall data from 1976 to 2009 of ten sub-basins of the Vaigai River in Tamil Nadu were collected and analysed statistically using various probability distribution functions. The best-fit probability distributions for the annual, monthly and seasonal rainfall for the study area were found using two goodness-of-fit tests. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting the study area's annual rainfall. The best ARIMA models were selected for each sub-basin and the average annual precipitation for 2010, 2015, 2020 and 2025 has been forecasted. The forecasted result compared well with observed dataup to 2020, which indicates the appropriateness of the model.
{"title":"Probability analysis and rainfall forecasting using ARIMA model","authors":"CHANDRAN S., SELVAN P., NAMITHA M. R., PRADEEP MISHRA, KUMAR V.","doi":"10.54302/mausam.v74i4.805","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.805","url":null,"abstract":"A 34-year rainfall data from 1976 to 2009 of ten sub-basins of the Vaigai River in Tamil Nadu were collected and analysed statistically using various probability distribution functions. The best-fit probability distributions for the annual, monthly and seasonal rainfall for the study area were found using two goodness-of-fit tests. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting the study area's annual rainfall. The best ARIMA models were selected for each sub-basin and the average annual precipitation for 2010, 2015, 2020 and 2025 has been forecasted. The forecasted result compared well with observed dataup to 2020, which indicates the appropriateness of the model.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.5984
LITING YAN, AO YU, GE ZHANG, JINYE ZHANG
The rapid development of modern industrial society has relied heavily on cheap and abundant fossil fuel energy. However, to achieve sustainable development, there is an increasing focus on developing new energy sources such as photovoltaics (PV) and wind energy. In the context of using solar irradiance to generate electricity, predicting the solarpower in advance is crucial for efficient utilization. This paper utilizes the pvlib-python model to predict three types of irradiance in clear sky conditions: POA_DNI, POA_GHI, and POA_DHI. Furthermore, we incorporate aerosol data from pvlib to improve the prediction accuracy.Three sites from BSRN are selected and the predicted data are compared with the observed data to evaluate the model's prediction effectiveness. The result reveals that the model performs best for POA_GHI and the actual cloud cover distribution has a significant impact on the prediction accuracy.
{"title":"Prediction of solar irradiance based on Python","authors":"LITING YAN, AO YU, GE ZHANG, JINYE ZHANG","doi":"10.54302/mausam.v74i4.5984","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.5984","url":null,"abstract":"The rapid development of modern industrial society has relied heavily on cheap and abundant fossil fuel energy. However, to achieve sustainable development, there is an increasing focus on developing new energy sources such as photovoltaics (PV) and wind energy. In the context of using solar irradiance to generate electricity, predicting the solarpower in advance is crucial for efficient utilization. This paper utilizes the pvlib-python model to predict three types of irradiance in clear sky conditions: POA_DNI, POA_GHI, and POA_DHI. Furthermore, we incorporate aerosol data from pvlib to improve the prediction accuracy.Three sites from BSRN are selected and the predicted data are compared with the observed data to evaluate the model's prediction effectiveness. The result reveals that the model performs best for POA_GHI and the actual cloud cover distribution has a significant impact on the prediction accuracy.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.5513
ADEEL TAHIR, MUHAMMAD ASHRAF, ZAHEER UDDIN, MUHAMMAD SARIM, SYED NASEEM SHAH
Environmental changes occur due to various parameters, and global warming is one of those parameters. It is observed that the daily mean temperature has constantly been increasing as time passes. The knowledge of temperature distribution allows us to decide the stuff that strongly depends upon temperature variation. An attempt has been made to model and forecast temperature distributions for 2018-2020. Artificial Neural Network (ANN) and multiple regression analyses have been used to forecast daily mean temperatures for one of Pakistan's cities of Sindh (Nawabshah). Environmental data from 2010 to 2020 has been used to predict daily mean temperature. The statistical errors such as RMSE, MABE and MAPE and coefficient of determination R2 are calculated to check the results' validity. Both models are suitable for predicting temperature distribution; however, ANN gives the best result. Two different regression models (linear & non-linear) are employed for the numerical fitting of temperature data; the non-linear model shows the better fitting.
{"title":"Numerical modeling and forecasting temperature distribution by neural network and regression analysis","authors":"ADEEL TAHIR, MUHAMMAD ASHRAF, ZAHEER UDDIN, MUHAMMAD SARIM, SYED NASEEM SHAH","doi":"10.54302/mausam.v74i4.5513","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.5513","url":null,"abstract":"Environmental changes occur due to various parameters, and global warming is one of those parameters. It is observed that the daily mean temperature has constantly been increasing as time passes. The knowledge of temperature distribution allows us to decide the stuff that strongly depends upon temperature variation. An attempt has been made to model and forecast temperature distributions for 2018-2020. Artificial Neural Network (ANN) and multiple regression analyses have been used to forecast daily mean temperatures for one of Pakistan's cities of Sindh (Nawabshah). Environmental data from 2010 to 2020 has been used to predict daily mean temperature. The statistical errors such as RMSE, MABE and MAPE and coefficient of determination R2 are calculated to check the results' validity. Both models are suitable for predicting temperature distribution; however, ANN gives the best result. Two different regression models (linear & non-linear) are employed for the numerical fitting of temperature data; the non-linear model shows the better fitting.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.3527
P. W. CHAN, K. K. LAI, Q. S. LI, P. W. CHAN
Dust devils at Hong Kong International Airport in two consecutive days in the summer of Hong Kong are documented. They are found to be related to the sea breeze convergence lines and are anticyclonic. The background meteorological conditions under which the dust devils occur are documented. The computer simulation of the tiny anticyclonic flow at the sea breeze convergence line is studied. This paper discusses the difficulties in the micro-scale simulation of the sea breeze circulation in an area of complex terrain and the successful reproduction of the sense of rotation of the dust devil flow. It is hoped that the paper could be a useful reference for the studies of dust devils in the literature.
{"title":"Observation and numerical simulation of dust devils at the Hong Kong International Airport in sea breeze situation","authors":"P. W. CHAN, K. K. LAI, Q. S. LI, P. W. CHAN","doi":"10.54302/mausam.v74i4.3527","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.3527","url":null,"abstract":"Dust devils at Hong Kong International Airport in two consecutive days in the summer of Hong Kong are documented. They are found to be related to the sea breeze convergence lines and are anticyclonic. The background meteorological conditions under which the dust devils occur are documented. The computer simulation of the tiny anticyclonic flow at the sea breeze convergence line is studied. This paper discusses the difficulties in the micro-scale simulation of the sea breeze circulation in an area of complex terrain and the successful reproduction of the sense of rotation of the dust devil flow. It is hoped that the paper could be a useful reference for the studies of dust devils in the literature.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.5379
CHETANA PATIL, SOMENATH DUTTA, G. K. SAWAISARJE, POOJA YADAV
In recent years, heavy rainfall events have been increasing over the Uttarakhand region. Improvement in the prediction of such events crucially dependent on the inclusion of the physical & dynamical processes responsible for such events, in the NWP model. This again, in turn depends on the understanding of such processes. In this study an attempt has been made to understand parts of these processes and some of the dynamical aspects of these heavy rainfall events. For this different important derived NWP products, viz., differential vorticity advection (DVA), differential thermal advection (DTA), Differential moisture advection (DMA), Precipitable water (PW), non-dimensional stability index (NDSI) have been computed using ECMWF high-resolution gridded reanalysis data sets. Heavy rainfall events are defined using IMD high resolution gridded daily rainfall data set. Preliminary analysis revealed that there was a steady increase in DVA, decrease in DTA, increase in PW and decrease in DMA before the heavy rainfall event. An enhanced DVA results in an enhancement in LLC, a decrease in DTA along with a decrease in DMA results in an enhancement of lapse rate. Combined effect of these results in the increase in the low-level convergence at Uttarakhand region along with the rising motion are the major dynamical processes resulted in the heavy rainfall event.
{"title":"A study on some dynamical aspects of Uttarakhand heavy rainfall events","authors":"CHETANA PATIL, SOMENATH DUTTA, G. K. SAWAISARJE, POOJA YADAV","doi":"10.54302/mausam.v74i4.5379","DOIUrl":"https://doi.org/10.54302/mausam.v74i4.5379","url":null,"abstract":"In recent years, heavy rainfall events have been increasing over the Uttarakhand region. Improvement in the prediction of such events crucially dependent on the inclusion of the physical & dynamical processes responsible for such events, in the NWP model. This again, in turn depends on the understanding of such processes. In this study an attempt has been made to understand parts of these processes and some of the dynamical aspects of these heavy rainfall events. For this different important derived NWP products, viz., differential vorticity advection (DVA), differential thermal advection (DTA), Differential moisture advection (DMA), Precipitable water (PW), non-dimensional stability index (NDSI) have been computed using ECMWF high-resolution gridded reanalysis data sets. Heavy rainfall events are defined using IMD high resolution gridded daily rainfall data set. Preliminary analysis revealed that there was a steady increase in DVA, decrease in DTA, increase in PW and decrease in DMA before the heavy rainfall event. An enhanced DVA results in an enhancement in LLC, a decrease in DTA along with a decrease in DMA results in an enhancement of lapse rate. Combined effect of these results in the increase in the low-level convergence at Uttarakhand region along with the rising motion are the major dynamical processes resulted in the heavy rainfall event.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134934953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.54302/mausam.v74i4.6028
BABITA DANI, VAIBHAVA SRIVASTAVA, A. P. SINGH, RAJEEV BHATLA
Numerical modelling of tsunami waves has been made for the western coasts of India using TUNAMI N2 code. In this study the fault parameters are considered from earlier published literatures. Bathymetry data and possible tsunami generation locations have been obtained from the ETOPO2 (Global Relief Model) and General Bathymetric Chart of the Oceans (GEBCO) satellite data. For tsunami run-up the land topography data Shuttle Radar Topographic Mission (SRTM) is used. The present simulation consists of a duration of 6 hours (360 min). Possible arrival time with amplitude at various locations have been estimated. The paper also analyses the changes in the directivity of the generated tsunami waves towards western coasts of India by changing the dip and strike angles as different scenarios. Time series and height along the different parts of Gujarat coast and hourly travel-time chart of the tsunami wave are also discussed. After the earthquake and initial tsunami wave generation, it reaches at all the locations along the Gulf of Kachchh (Gujarat) in nearly 2 hrs to 5.30 hrs with amplitudes from 1 to 2.5 m, Mumbai in around 4.45 hrs with amplitude 2 m, Goa in around 3.08 hrs with amplitude 1 m, Karwar (Karnataka) in around 3.12 hrs and Mangalore in around 3.36 hrs with amplitudes 1 m each. The authenticity of the estimated tsunami phases of the 1945 tsunamigenic earthquake along the MSZ are corroborated with the available reports and published literatures.
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