Pub Date : 2023-12-31DOI: 10.54302/mausam.v75i1.3576
P. Setiya, A. Nain, Anurag Satpathi
The study was aimed to develop the yield forecast model for rice crop yield. Four different techniques i.e. Stepwise Multiple Linear Regression (SMLR), Artificial Neural Network (ANN), Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net (ELNET)were used to build the prediction models. Dataset of meteorological data and crop yield data of 15 years have been used to develop the forecast models. The developed models were also validated on the dataset of three years. The assessment of the developed models wasdone by using root mean square error (RMSE),normalized root mean square error (nRMSE),Mean Absolute Error (MAE) and on the basis of coefficient of determination (R2). The experimental analysis suggested that the performance for Artificial Neural Network (R2=0.99, RMSE=0.07, nRMSE=2.20, MAE=0.06) is better as compared to SMLR(R2=0.97, RMSE=0.08, nRMSE=2.34, MAE=0.05), LASSO (R2=0.62, RMSE=0.26, nRMSE=7.81, MAE=0.24) and ELNET (R2=0.54, RMSE=0.38, nRMSE=11.41, MAE=0.37) for the predictionof rice crop yield for Udham Singh Nagar (USN) district of Uttarakhand. Therefore, for the prediction of rice yield, ANN technique can be well utilised for Udham Singh Nagar district of Uttarakhand.
{"title":"Comparative analysis of SMLR, ANN, Elastic net and LASSO based models for rice crop yield prediction in Uttarakhand","authors":"P. Setiya, A. Nain, Anurag Satpathi","doi":"10.54302/mausam.v75i1.3576","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.3576","url":null,"abstract":"The study was aimed to develop the yield forecast model for rice crop yield. Four different techniques i.e. Stepwise Multiple Linear Regression (SMLR), Artificial Neural Network (ANN), Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net (ELNET)were used to build the prediction models. Dataset of meteorological data and crop yield data of 15 years have been used to develop the forecast models. The developed models were also validated on the dataset of three years. The assessment of the developed models wasdone by using root mean square error (RMSE),normalized root mean square error (nRMSE),Mean Absolute Error (MAE) and on the basis of coefficient of determination (R2). The experimental analysis suggested that the performance for Artificial Neural Network (R2=0.99, RMSE=0.07, nRMSE=2.20, MAE=0.06) is better as compared to SMLR(R2=0.97, RMSE=0.08, nRMSE=2.34, MAE=0.05), LASSO (R2=0.62, RMSE=0.26, nRMSE=7.81, MAE=0.24) and ELNET (R2=0.54, RMSE=0.38, nRMSE=11.41, MAE=0.37) for the predictionof rice crop yield for Udham Singh Nagar (USN) district of Uttarakhand. Therefore, for the prediction of rice yield, ANN technique can be well utilised for Udham Singh Nagar district of Uttarakhand.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133470","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.765
P. Naskar, Dushmanta R. Pattanaik
This study has been undertaken to find out the variation of central pressure (intensity) of intense Tropical Cyclones (TCs) with Sea Surface Temperature (SST), Mid-tropospheric Relative Humidity (MRH), Mid-tropospheric Instability (MI), Vertical Wind Shear (VWS), 200-hPa divergence, and Surface Latent Heat Flux (SLHF) during the lifetime intense TCs. This study also aims to determine the most crucial parameter which shows the highest correlation with central pressure (intensity) of intense TCs during their lifetime. Out of all these parameters, SLHF is highly correlated (R = 0.74) with the central pressure (intensity) of intense TCs. Increase and decrease of SLHF correspond to decrease and increase of TCs central pressure (increase and decrease in TCs intensity). The highest SLHF corresponds to the lowest central pressure (highest intensity).
{"title":"Variations in intensity of Bay of Bengal tropical cyclones with surface latent heat flux and other parameters","authors":"P. Naskar, Dushmanta R. Pattanaik","doi":"10.54302/mausam.v75i1.765","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.765","url":null,"abstract":"This study has been undertaken to find out the variation of central pressure (intensity) of intense Tropical Cyclones (TCs) with Sea Surface Temperature (SST), Mid-tropospheric Relative Humidity (MRH), Mid-tropospheric Instability (MI), Vertical Wind Shear (VWS), 200-hPa divergence, and Surface Latent Heat Flux (SLHF) during the lifetime intense TCs. This study also aims to determine the most crucial parameter which shows the highest correlation with central pressure (intensity) of intense TCs during their lifetime. Out of all these parameters, SLHF is highly correlated (R = 0.74) with the central pressure (intensity) of intense TCs. Increase and decrease of SLHF correspond to decrease and increase of TCs central pressure (increase and decrease in TCs intensity). The highest SLHF corresponds to the lowest central pressure (highest intensity).","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136389","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.6133
Vineet Ahuja, Chhavi P. Pandey, L. K. Joshi, H. Nandan, Parmanand P. Pathak
Climate change has become a major issue for the world today. Small changes in the climate in the Himalayan region can have a significant impact on the delicate ecosystem, which is very sensitive to such changes. Recent investigations into climate change in the Western Himalayas have provided compelling evidence that these regions are especially susceptible to a wide variety of catastrophic occurrences. In the current scenario, the threat posed by climate change to human existence in Jammu and Kashmir (J&K), as well as the region of Ladakh, has grown more tangible and evident. Temperature and precipitation statistics could be used to observe this regional climatic shift. This study analyses and forecasts long-term spatio-temporal variations in precipitation and temperature using a century-long dataset from 1901 to 2002 over 14 districts of Jammu and Kashmir and Ladakh. The Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test of stationarity on the data show that the time series is stationary. Extreme Value Theory (EVT), which is an outstanding statistical method to interpret the records for the estimation of the future probability of the occurrence of extremes, is utilised in this study. Further, precipitation and temperature extremes are forecasted for 50, 80, 100, 120, 200, 250, 300, and 500 year return periods respectively and results reveal that the districts- Jammu, Rajouri, Leh, Srinagar, Baramulla and Poonch will be more prone to extreme weather events phenomenon.
{"title":"Extreme value analysis of precipitation and temperature over Jammu & Kashmir and Ladakh in western Himalaya, India","authors":"Vineet Ahuja, Chhavi P. Pandey, L. K. Joshi, H. Nandan, Parmanand P. Pathak","doi":"10.54302/mausam.v75i1.6133","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.6133","url":null,"abstract":"Climate change has become a major issue for the world today. Small changes in the climate in the Himalayan region can have a significant impact on the delicate ecosystem, which is very sensitive to such changes. Recent investigations into climate change in the Western Himalayas have provided compelling evidence that these regions are especially susceptible to a wide variety of catastrophic occurrences. In the current scenario, the threat posed by climate change to human existence in Jammu and Kashmir (J&K), as well as the region of Ladakh, has grown more tangible and evident. Temperature and precipitation statistics could be used to observe this regional climatic shift. This study analyses and forecasts long-term spatio-temporal variations in precipitation and temperature using a century-long dataset from 1901 to 2002 over 14 districts of Jammu and Kashmir and Ladakh. The Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test of stationarity on the data show that the time series is stationary. Extreme Value Theory (EVT), which is an outstanding statistical method to interpret the records for the estimation of the future probability of the occurrence of extremes, is utilised in this study. Further, precipitation and temperature extremes are forecasted for 50, 80, 100, 120, 200, 250, 300, and 500 year return periods respectively and results reveal that the districts- Jammu, Rajouri, Leh, Srinagar, Baramulla and Poonch will be more prone to extreme weather events phenomenon.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139130232","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.6081
Raju Kalita, Dipangkar Kalita, Atul K. Saxena
The Statistical Downscaling Model (SDSM 4.2) is used to project the future precipitation and maximum and minimum temperatures at Sohra, one of the extreme places on earth, using the predictors of the Second-Generation Canadian Earth System Model (CanESM2). The SDSM was calibrated with daily precipitation and temperature data from 1979 to 2005 and validated from 2006 to 2020. Future scenarios generated under the three Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 are divided into three future periods, Near Future (2021-2040), Mid Future (2041-2071), and Far Future (2071-2100). It is found that the precipitation and maximum/minimum temperature at Sohra are influenced mainly by the major global predictors; specific humidity at 850 hPa height (s850) and mean temperature at 2 m (temp)/near surface specific humidity (shum), respectively. The downscaled result reveals an increase in Monsoon precipitation in the range of 266-1543 mm under various RCPs compared with the base periods 1985-2005 during the Near Future and 1979-2008 during the Mid and Far Future. Also, annual maximum and minimum temperature increases in the range of 1-2.8 °C and 1.2-3.6 °C for all RCPs in the future.
{"title":"Future projections of precipitation and temperature extremes at Sohra (Cherrapunji) using Statistical Downscaling Model","authors":"Raju Kalita, Dipangkar Kalita, Atul K. Saxena","doi":"10.54302/mausam.v75i1.6081","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.6081","url":null,"abstract":"The Statistical Downscaling Model (SDSM 4.2) is used to project the future precipitation and maximum and minimum temperatures at Sohra, one of the extreme places on earth, using the predictors of the Second-Generation Canadian Earth System Model (CanESM2). The SDSM was calibrated with daily precipitation and temperature data from 1979 to 2005 and validated from 2006 to 2020. Future scenarios generated under the three Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 are divided into three future periods, Near Future (2021-2040), Mid Future (2041-2071), and Far Future (2071-2100). It is found that the precipitation and maximum/minimum temperature at Sohra are influenced mainly by the major global predictors; specific humidity at 850 hPa height (s850) and mean temperature at 2 m (temp)/near surface specific humidity (shum), respectively. The downscaled result reveals an increase in Monsoon precipitation in the range of 266-1543 mm under various RCPs compared with the base periods 1985-2005 during the Near Future and 1979-2008 during the Mid and Far Future. Also, annual maximum and minimum temperature increases in the range of 1-2.8 °C and 1.2-3.6 °C for all RCPs in the future.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133102","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.3568
ANOOP KUMAR MISHRA, Mohammad Suhail Meera, V. Nagaraju
Maharashtra experienced a series of calamitous flood events during July and September months of monsoon season of 2019 affecting millions of people. Mumbai, Palghar, Thane, Raigad, Satara, Sangli, Pune and Kolhapaur were most affected districts of Maharashtra. Near real time satellite observations from space have been used in this study to monitor these events. Availability of accurate precipitation information at very fine resolution of 5 km (half hourly) from a rainfall model that integrates observations from multi-spectral satellite sensors offers an excellent opportunity to monitor flood events effectively. Utility of this model was tested by investigating flood events of Kedarnath in 2013, Jammu and Kashmir in 2014 and Tamil Nadu in 2015. This model was also used to explore recent flood events of Kerala and Assam in 2019. Mumbai, Palghar, Thane, Raigad, Satara, Sangli, Pune and Kolhapaur districts received very heavy rainfall from multiple rain episodes during first, third and last week of July, and second and last week of September that resulted in heavy flooding over these districts. Results reveal that few of these districts received cumulative rainfall in excess of 2000 mm from multiple heavy rainy events during July to September. Mumbai, Palghar, Thane and Raigad received a cumulative rainfall in excess of 1700 mm during July and September. Sangali district received an excess of about 200% rainfall than average monthly rain during July 2019. Heavy cumulative rainfall from multiple rain spells resulted in heavy flooding over various districts of Maharashtra. Results reported in this study highlight the importance of mitigation and adaptation strategies against flood disasters.
{"title":"Exploring extreme flood events of a western state of India during monsoon season of 2019 from space","authors":"ANOOP KUMAR MISHRA, Mohammad Suhail Meera, V. Nagaraju","doi":"10.54302/mausam.v75i1.3568","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.3568","url":null,"abstract":"Maharashtra experienced a series of calamitous flood events during July and September months of monsoon season of 2019 affecting millions of people. Mumbai, Palghar, Thane, Raigad, Satara, Sangli, Pune and Kolhapaur were most affected districts of Maharashtra. Near real time satellite observations from space have been used in this study to monitor these events. Availability of accurate precipitation information at very fine resolution of 5 km (half hourly) from a rainfall model that integrates observations from multi-spectral satellite sensors offers an excellent opportunity to monitor flood events effectively. Utility of this model was tested by investigating flood events of Kedarnath in 2013, Jammu and Kashmir in 2014 and Tamil Nadu in 2015. This model was also used to explore recent flood events of Kerala and Assam in 2019. Mumbai, Palghar, Thane, Raigad, Satara, Sangli, Pune and Kolhapaur districts received very heavy rainfall from multiple rain episodes during first, third and last week of July, and second and last week of September that resulted in heavy flooding over these districts. Results reveal that few of these districts received cumulative rainfall in excess of 2000 mm from multiple heavy rainy events during July to September. Mumbai, Palghar, Thane and Raigad received a cumulative rainfall in excess of 1700 mm during July and September. Sangali district received an excess of about 200% rainfall than average monthly rain during July 2019. Heavy cumulative rainfall from multiple rain spells resulted in heavy flooding over various districts of Maharashtra. Results reported in this study highlight the importance of mitigation and adaptation strategies against flood disasters.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133308","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.6146
S. Chug, S. Nath
{"title":"RECENT ADVANCES IN SOCIAL WEATHER, COMMON ALERT PROTOCOL AND DISSEMINATION SERVICES THROUGH APIS IN INDIA METEOROLOGICAL DEPARTMENT","authors":"S. Chug, S. Nath","doi":"10.54302/mausam.v75i1.6146","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.6146","url":null,"abstract":"","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136112","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.5916
Nishtha Sehgal, Tanvi Malhan, R. K. Giri, Ramashray Yadav, Yogesh Kumar, Laxmi Pathak, आवद्कता हस।
The objective of the study was twofold (i) Review of INSAT-3D/3DR night time fog detection channel differencing (MIR- TIR1) scheme developed by Space Application Centre (SAC) Indian Space Research Centre (ISRO) thresholds which were not uniform for winter season radiation fog and vary geographically over Indian domain & (ii) An analysis of Fog events of 2021-2022 winter season analysis using the anomalies (temperature, wind, moisture, inversion, geo-potential height etc) from NCEP reanalysis and ERA-5 data sets. This study is a way forward to look into the importance of recently introduced model reanalysis data sets to monitor and understand the recent changes of fog events behaviour. It is seen that the fog events winter season (2021-2022) was reduced appreciably and this change is really a concern but 2021-22 winter fog occurrences were very well captured in both models as well as INSAT-3D/3DR data analysis. The results brought out from the model as well as satellite data analysis were found to be very useful for forecasters and end users especially in monitoring and prediction of fog events. However, to quantify the night time fog thresholds based on INSAT data for different regions of India and appreciable reduction of fog events in the recent past needs long term data sets study.
{"title":"An analysis of fog events in respect of winter season 2021-2022 using model reanalysis & INSAT-3D/3DR satellite data","authors":"Nishtha Sehgal, Tanvi Malhan, R. K. Giri, Ramashray Yadav, Yogesh Kumar, Laxmi Pathak, आवद्कता हस।","doi":"10.54302/mausam.v75i1.5916","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.5916","url":null,"abstract":"The objective of the study was twofold (i) Review of INSAT-3D/3DR night time fog detection channel differencing (MIR- TIR1) scheme developed by Space Application Centre (SAC) Indian Space Research Centre (ISRO) thresholds which were not uniform for winter season radiation fog and vary geographically over Indian domain & (ii) An analysis of Fog events of 2021-2022 winter season analysis using the anomalies (temperature, wind, moisture, inversion, geo-potential height etc) from NCEP reanalysis and ERA-5 data sets. This study is a way forward to look into the importance of recently introduced model reanalysis data sets to monitor and understand the recent changes of fog events behaviour. It is seen that the fog events winter season (2021-2022) was reduced appreciably and this change is really a concern but 2021-22 winter fog occurrences were very well captured in both models as well as INSAT-3D/3DR data analysis. The results brought out from the model as well as satellite data analysis were found to be very useful for forecasters and end users especially in monitoring and prediction of fog events. However, to quantify the night time fog thresholds based on INSAT data for different regions of India and appreciable reduction of fog events in the recent past needs long term data sets study.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139133217","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.5374
J. P S
In this study an effort is done to explain the maintenance of the Very Severe Cyclonic Storm(VSCS) Ockhi using the angular momentum(AM) budget technique . The AM budget equation for a region bounded by , to and to in (x,y,p,t) co-ordinate system is used from an earlier study. The different terms are explained with relative importance. This technique is used to the diagnosis of different small, medium and large weather systems by several authors. The Very Severe Cyclonic Storm(VSCS) Ockhi –a rare situation in Arabian Sea – is studied with a reanalyzed dataset in a fine mesh width. The values of different terms in the AM budget equation are calculated for pressure levels-1000,800,500,200,100hpa’s and for four day periods viz. 30 Nov ,01 Dec ,02 Dec and 03 Dec 2017 .The AM budget was prepared for the eight observation time periods of 00, 03,06,09,12,15,18,21 UTC for each day. The area selected is 5.04N - 19.2N, 60E- 77E where VSCS TC Ockhi formed.The sink and source terms are compared and the results are correlated with the help of charts . The NCMRWF IMDAA data set is used and the results are depicted in charts and results are compared with the observed synoptic behavior of the system . Keywords: - Angular Momentum Budget, Equation, Source/Sink terms, VSCS Ockhi-Diagnosis
{"title":"Momentum budget analysis of maintenance of Arabian Sea tropical cyclone Ockhi","authors":"J. P S","doi":"10.54302/mausam.v75i1.5374","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.5374","url":null,"abstract":"In this study an effort is done to explain the maintenance of the Very Severe Cyclonic Storm(VSCS) Ockhi using the angular momentum(AM) budget technique . The AM budget equation for a region bounded by , to and to in (x,y,p,t) co-ordinate system is used from an earlier study. The different terms are explained with relative importance. This technique is used to the diagnosis of different small, medium and large weather systems by several authors. The Very Severe Cyclonic Storm(VSCS) Ockhi –a rare situation in Arabian Sea – is studied with a reanalyzed dataset in a fine mesh width. The values of different terms in the AM budget equation are calculated for pressure levels-1000,800,500,200,100hpa’s and for four day periods viz. 30 Nov ,01 Dec ,02 Dec and 03 Dec 2017 .The AM budget was prepared for the eight observation time periods of 00, 03,06,09,12,15,18,21 UTC for each day. The area selected is 5.04N - 19.2N, 60E- 77E where VSCS TC Ockhi formed.The sink and source terms are compared and the results are correlated with the help of charts . The NCMRWF IMDAA data set is used and the results are depicted in charts and results are compared with the observed synoptic behavior of the system . Keywords: - Angular Momentum Budget, Equation, Source/Sink terms, VSCS Ockhi-Diagnosis","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139134452","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.3573
Peyman Mahmoudi, S. A. Shirazi, Seyed Mahdi Amir Jahanshahi, F. Firoozi, N. Mazhar
.The present study aimed at investigating the relationship between two variables of temperature and precipitation with vegetation dynamics in one of the arid and semi-arid regions of the world, i.e. Baluchistan in Southwestern Asia, which is shared by the three countries of Iran, Pakistan and Afghanistan. In order to achieve the objectives, two different databases were used: 1. MODIS NDVI 16-day composite products (MOD13A3) of Terra satellite, with 1*1 km spatial resolution, which was obtained for a 17-year period (2000-2016) from the Earth Observing System (EOS) Data Gateway of the National Aeronautics and Space Administration (NASA); 2. Gridded monthly temperature and precipitation data was obtained for the same 17-year period from the Climate Research Unit (CRU) of the University of East Anglia. The Pearson product-moment correlation coefficient was also used to examine the relationship between vegetation dynamics and two climate variables of temperature and precipitation simultaneously as well as in three time lags i.e.; one month, two months and three months. The results of the analysis of a correlation between the mean temperature and monthly NDVI in different time lags indicated that in the humid and semi-humid regions in the northern half of Baluchistan, NDVI simultaneously reacted to temperature variations, while in the arid and semi-arid regions in the southern half of Baluchistan, NDVI had a one-month time lag with temperature. However, the results of the analysis of a correlation between precipitation and monthly NDVI in different time lags indicated that NDVI simultaneously reacted to precipitation variations, that is precipitation of each month had the greatest effect on the NDVI of the same month.
.本研究旨在调查世界上干旱和半干旱地区之一，即伊朗、巴基斯坦和阿富汗三国共有的西南亚俾路支斯坦地区的温度和降水量这两个变量与植被动态之间的关系。为了实现目标，使用了两个不同的数据库：1.从美国国家航空航天局（NASA）的地球观测系统（EOS）数据网关获得了 17 年（2000-2016 年）期间（1*1 公里）的 Terra 卫星 MODIS NDVI 16 天复合产品（MOD13A3）；2. 从东英吉利大学气候研究室（CRU）获得了同样 17 年期间的网格化月度气温和降水数据。此外，还使用了皮尔逊积幂相关系数（Pearson product-moment correlation coefficient）来研究植被动态与气温和降水这两个气候变量之间的关系。平均气温与月净植被指数在不同滞后期之间的相关性分析结果表明，在俾路支斯坦北半部的湿润和半湿润地区，净植被指数同时对气温变化做出反应，而在俾路支斯坦南半部的干旱和半干旱地区，净植被指数与气温的时滞为一个月。然而，对不同滞后时间段的降水量与每月归一化差异植被指数之间相关性的分析结果表明，归一化差异植被指数同时对降水量变化做出反应，即每月降水量对同月归一化差异植被指数的影响最大。
{"title":"A satellite bioclimatology of Baluchistan in Southwestern Asia","authors":"Peyman Mahmoudi, S. A. Shirazi, Seyed Mahdi Amir Jahanshahi, F. Firoozi, N. Mazhar","doi":"10.54302/mausam.v75i1.3573","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.3573","url":null,"abstract":".The present study aimed at investigating the relationship between two variables of temperature and precipitation with vegetation dynamics in one of the arid and semi-arid regions of the world, i.e. Baluchistan in Southwestern Asia, which is shared by the three countries of Iran, Pakistan and Afghanistan. In order to achieve the objectives, two different databases were used: 1. MODIS NDVI 16-day composite products (MOD13A3) of Terra satellite, with 1*1 km spatial resolution, which was obtained for a 17-year period (2000-2016) from the Earth Observing System (EOS) Data Gateway of the National Aeronautics and Space Administration (NASA); 2. Gridded monthly temperature and precipitation data was obtained for the same 17-year period from the Climate Research Unit (CRU) of the University of East Anglia. The Pearson product-moment correlation coefficient was also used to examine the relationship between vegetation dynamics and two climate variables of temperature and precipitation simultaneously as well as in three time lags i.e.; one month, two months and three months. The results of the analysis of a correlation between the mean temperature and monthly NDVI in different time lags indicated that in the humid and semi-humid regions in the northern half of Baluchistan, NDVI simultaneously reacted to temperature variations, while in the arid and semi-arid regions in the southern half of Baluchistan, NDVI had a one-month time lag with temperature. However, the results of the analysis of a correlation between precipitation and monthly NDVI in different time lags indicated that NDVI simultaneously reacted to precipitation variations, that is precipitation of each month had the greatest effect on the NDVI of the same month.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136503","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 : 2023-12-31DOI: 10.54302/mausam.v75i1.5595
Fathallah Fatima Ezzahra, Algouti Ahmed, A. Abdellah
{"title":"MAPPING OF DROUGHT RISK AREAS IN AGRICULTURAL LANDS IN THE CHICHAOUA BASIN - MOROCCO NORTH AFRICA-USING TEMPERATURE INDEX (TCI)","authors":"Fathallah Fatima Ezzahra, Algouti Ahmed, A. Abdellah","doi":"10.54302/mausam.v75i1.5595","DOIUrl":"https://doi.org/10.54302/mausam.v75i1.5595","url":null,"abstract":"","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139131713","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}
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