MAUSAM

Assessing the suitability of different modeling techniques for meteorological forecasting on Chickpea wilt

Promil Kapoor — 2025-04-01

The daily climate data collected for Hisar district between November 1, 1977 and April 30, 2022, has been analyzed and presented in this study. The data set was divided into two parts: training and testing data. This study presents the results of ARIMA, state space, and seasonal Holt-Winters models fitted for maximum temperature, minimum temperature, relative humidity (M), relative humidity (E), bright sunshine hours, and rainfall. The models were trained on data spanning from November 1977 to April 2013. The top selected ARIMA models were chosen based on evaluation criteria, such as the Akaike information criterion, root mean squared error, mean absolute error, mean absolute percentage error, in-sample MSE, and the maximum number of significant coefficients. The state space models were selected based on minimum values of the Akaike information criterion (AIC), Bayesian information criterion (BIC), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), in-sample Mean Squared Error (MSE), and Mean Absolute PercentageError (MAPE). The seasonal Holt-Winters models were fitted with additive specifications and a period of 365. Global chickpea production is highly dependent on various biotic and abiotic stresses. One of the critical biotic stresses, Fusarium wilt, significantly limits chickpea productivity causing economic losses ranging from 10 to 40% in many countries and escalates to 100% when temperature and humidity are favourable. Weather forecasting is crucial in plant disease management as it helps to predict disease outbreaks by analyzing how weather conditions influence pathogen development and spread, allowing farmers to take timely preventative measures.

Application of SARIMA model for precipitation modelling driven by exogenous variables

Md Yeasin — 2025-04-01

The Seasonal Autoregressive Integrated Moving Average (SARIMA) model has gained popularity since its inception due to its ability to forecast seasonality. Usually, the SARIMA model captures the seasonality but does not consider the effect of the exogenous variable(s) in the seasonality process. Hence, this study aims to empirically introduce and implement the SARIMA-X model which can account for seasonality as well as the effects of influencing factors (X). Climate change has become the foremost global challenge facing human existence and the effect will be multifaceted with respect to social, economic and environmental challenges. This manuscript aims to forecast the precipitation time series data of Bangalore, India. The methodology employed in the analysis and modelling of precipitation series was the SARIMA-X model with exogenous variables temperature, relative humidity and surface pressure. In this manuscript, we have briefly discussed the SARIMA-X model along with its estimation procedure. The proposed model was diagnosed and the results showed that the model was adequate and parsimonious. The proposed model has compared with the traditional SARIMA model. The supremacy of using exogenous factors in seasonality modelling is concluded by this comparative study.

Innovative trend analysis of long-term rainfall variation over West Bengal, India

Gaurav Patel — 2025-04-01

This study uses 115 years’ gridded rainfall data from 121 gauge stations to observe long-term changes in annual and seasonal rainfall in the entire West Bengal, India. The significance and amplitude of these changes and overall trends are assessed with the use of such gridded data for the period from 1901 to 2015 collected from the India Meteorological Department, by applying innovative trend analysis. According to the findings of the study, rainfall in the study area decreases significantly during the winter season and pre-monsoon season, while increases significantly during the monsoon season and post-monsoon season. The monsoon rainfall experiences the largest increase at 4.68 mm/year and the smallest decrease at 2.95 mm/year. The overall trends of seasonal rainfalls are found to be statistically significant at the 5% significance level except for a few districts for pre-monsoon, monsoon, and post-monsoon rainfalls. This work aims to provide scientific support to recognize and strategically mitigate the impact of climatic changes on water management in West Bengal and thereby reduce the risk of climate change.

Deciphering rainfall patterns in Haryana, India : a comprehensive analysis of optimal probability distributions

Anurag — 2025-04-01

This research aimed to examine the trends of extreme rainfall events and determine the most suitable probability distribution for rainfall in Haryana state, which is divided into two agroclimatic zones: eastern and western. Five stations (Ambala, Karnal, Hisar, Sirsa and Bawal) were selected from across the state for this analysis. The study processed and analyzed 36 years (1985-2020) of daily rainfall data from each station to identify the maximum one-day and five-day rainfall, as well as monsoonal and total rainfall. The Man-Kandal test and Sen’s slope estimator were used to assess trends in these events. Ten probability distributions were chosen for the rainfall analysis, followed by goodness-of-fit tests such as the Kolmogorov-Smirnov test, Anderson Darling and the chi-square test at a 0.01 level of significance to select the best-fit probability distribution. The study found that one-day maximum rainfall in the state varied significantly, ranging from 23 mm (at Hisar) to 203 mm (at Sirsa). Notably, there was a significant increasing trend in one-day maximum rainfall at Bawal (southern Haryana) at a rate of 0.95mm/year. The maximum five-day rainfall was highest at Ambala (560.8 mm) and lowest at Hisar (29.6 mm). Monsoon rain accounted for 78% of the mean annual rainfall, which ranged from 373.6 mm (at Sirsa) to 843.5 mm (at Ambala). The probability analyses indicated that the General Extreme Value function was a good fit for most rainfall events at most locations. However, based on rainfall variables, the Lognormal (3P) function was the best fit for most locations when explaining the distribution of one-day maximum rainfall events in Haryana. For five-day maximum rainfall events as well as monsoonal rainfall, the Gen. Extreme Value function was the best fit; and for annual rainfall events, both the Gen. Extreme Value and Normal functions performed well.

Rainfall variability and probability analysis in Tarai and mid Himalayan regions of Uttarakhand

Shubhika Goel — 2025-04-01

The rainfall analysis is helpful for proper crop planning under changing environment in any region. Therefore in this study an attempt has been made to analyze long term rainfall data, i.e., 40 years from 1981-2020 (Tarai region) and 36 years from 1985-2020 (mid Himalayan region) as per availability and comparison is being done on the type of crop to be grown, sowing time, irrigation scheduling etc. The initial and conditional probability of rainfall on weekly basis was analyzed at different levels, i.e., >5mm, >10mm, >20mm, >30mm, >40mm and >50mm using Markov chain model. In addition to this, incomplete gamma distribution was also used to find out the occurrence of rainfall events at different probability levels, i.e., 10, 25, 50, 75 & 90 per cent.

The results revealed that though the amount of rainfall in the Tarai region is higher when compared with mid Himalayan region but most of them is limited to southwest monsoon season only. The crops can be raised easily throughout the year in the mid Himalayan region because of uniform distribution of rainfall in all the seasons except in the post monsoon season year and by arranging lifesaving irrigation to growing crops during light/moderate/severe dry spells conditions only from available natural springs/perennial streams/harvesting run off water during the water stress weeks. On the other hand, in the Tarai region proper irrigation facilities must be ensured during all the seasons except in the southwest monsoon season in order to have productive yield.

Spatiotemporal changes in Indian land aridity : An assessment based on the CRU data and UNEP’s aridity index

Nitish Kumar Singh — 2025-04-01

This study delves into the nuanced dynamics of aridity patterns over Indian land from 1901 to 2021, crucial for informed land and water management amidst rising demands and climate uncertainties. Employing the CRU dataset and UNEP's aridity index, the research identifies five aridity categories and conducts a meticulous spatio-temporal analysis. Utilizing the MK-trend analysis method, significant trends are discerned, elucidating shifts in hyper-arid, arid, semi-arid, sub-humid, and humid lands. Notably, a diminishing trend is observed in hyper-arid, arid, and humid areas, while semi-arid and sub-humid areas exhibit expansion. Intriguingly, transformations between aridity types underscore the evolving landscape, with many formerly arid regions transitioning towards greater humidity and many humid regions experience heightened aridity, possibly influenced by changing temperature and rainfall patterns. These findings underscore the complex interplay of climate factors shaping India's aridity landscape, necessitating further research for a comprehensive understanding of localized aridity dynamics.

Decoding climate change : Modeling resilience of sugarcane Co86032 in Padegaon (Maharashtra), India with DSSAT and Random forest

Shahenaz Mulla — 2025-04-01

Climate change presents significant challenges to agricultural productivity, especially in tropical regions where crops like sugarcane are crucial for the economy. This study investigates the impact of climatic factors on the Co86032 sugarcane cultivar under the RCP 4.5 scenario. The integration of DSSAT and Random Forest models allows for a detailed exploration of non-linear relationships between temperature, rainfall, and crop outcomes. We used the DSSAT model and data mining to analyze the effects of past climate data (1986-2021) and future projections (2024-2098) of temperature and rainfall on key crop factors such as yield, sucrose content, green leaf area index, and harvest index. Results show that high temperatures (Tx) have a significant impact on yield and sucrose content, emphasizing the need for temperature management strategies, such as optimized planting schedules and heat-tolerant crop varieties.

The results indicate that high temperatures (Tx), a crucial factor in the RCP4.5 scenario, notably affect sugarcane yield and sucrose content, highlighting more focus on the management of maximum temperature fluctuation. This can be done with heat-tolerant breeding programs and optimizing planting strategies. In contrast, rainfall (Rf) has a weaker correlation with crop productivity, highlighting the importance of irrigation infrastructure in managing water stress. It also emphasizes the importance of stress management, crop diversification, and climate-smart farming techniques for improved resilience and resource use. Advanced irrigation systems aligned with temperature trends are recommended to stabilize crop yields. Adaptive and real-time decision-making supported by predictive models (DSSAT) gives optimal crop management practices and the Random Forest model enhances yield predictions under varying climate scenarios. This combined modeling offers practical solutions for farmers and policymakers. Thus, precision agriculture tools like weather-based advisories, irrigation planning, and crop diversification are crucial for mitigating climate impacts and improving crop performance in changing conditions.

This study highlights the importance of understanding how climate influences sugarcane growth to assist industries in making informed decisions and adaptive precision farming practices to tackle the effects of climate change.

Spatial and temporal variations of temperature and rainfall, and land use/land cover changes in the Bengaluru urban district

Dhanya G — 2025-04-01

Sustainable Development Goal (SDG) 11 focuses on ‘Sustainable Cities and Communities.’ This paper presents the spatial and temporal changes in rainfall and temperature from 1980 to 2022 and Land Use and Land Cover (LULC) in the Bengaluru urban district between 1992 and 2022. This study employs linear regression and non-parametric Modified Mann-Kendall techniques to evaluate the importance of weather data patterns at yearly, monthly, and seasonal levels. The findings reveal a decrease in mean maximum temperature and an increase in minimum temperature, indicating cooler days and warmer nights. Seasonal rainfall also exhibits an increasing trend in the study area over the observation period of 40 years. To quantify some of the key reasons for these microclimate changes, LULC analysis was conducted over 30 years (1992-2022). This analysis indicates a substantial transformation in Bengaluru's landscape, with built-up areas growing at the expense of water bodies, vegetation, and fallow landdue to the rapid urbanization around Bengaluru and the consequent land-use alterations without adequate planning and assessing their environmental and climate impacts. While this study is based in Bengaluru, the method used in this study can be expanded to other megacities to contribute to the achievement of SDG 11.

A statistical perspective on Assam’s temperature pattern from 1985-2022

Dipanjali Ray — 2025-04-01

This paper focusses on the variation of a significant parameter of climate, Temperature. To study the variation of this parameter, various zones of Assam has been consideredsince it is expected to be highlyprone to consequences to climate change because of its sensitive geo-ecological set-up and strategic location. This paper gives not only the idea about how temperature is changing but also explains aberration from one station to other stations in four selected zones of Assam by calculating Growth rate from 1985-2022 season wise. To extract specific information about the temperature of Assam during the period 1985-2022, monthly mean maximum temperature and monthly mean minimum temperature is considered. Growth rate of temperature indicates that the percentage rate of change in maximum temperature is least in Dhubri station and highest in Dibrugarh station for all season. But in case of minimum temperature, variation rate is least in Dibrugarh station for all season except post-monsoon season and shows highest in Dhubri station for all seasons. Along these, this paper tries to elaborate the statistical frame of temperature during the period 1985-2022. Besides these, the statistical time series models are considered for projection; the extreme value analysis is done to assure the significance of extreme events.

Meteorological conditions associated with the unprecedented weather activity over eastern parts of Uttar Pradesh, India on 16 & 17 September 2021

Shashi Kant — 2025-04-01

This paper is concerned with the heavy rainfall episode reported over some locations of the eastern parts of Uttar Pradesh, India during 16 & 17 September 2021 and the associated meteorological conditions are investigated. Each heavy rainfall episode deserves major scientific documentation for the improvement in the existing knowledge of the concerned users. Even though it may also benefit the general public, as heavy rainfall concerns everybody in the domain. This case study will serve the above purpose and may be useful for policymakers, disaster managers, disaster response, and mitigation.

Regarding the favourable meteorological conditions for heavy rainfall episode, it is found that synoptically there was an active Well Marked Low-Pressure system over the region. In addition, other conditions like positive relative vorticity, upper-level divergence, higher relative humidity, lower-level convergence, and vertical velocity (Omega) profiles also provided a favorable environmental mechanism. Continuous moisture supply from the Bay of Bengal through easterly/southeasterly winds extended up to middle tropospheric levels (500 hPa), which was another important factor for the occurrence of rainfall episodes. This case serves as an example that even in the absence of an active Jet core at 200 hPa over India, very heavy/extremely heavy rainfall may occur over east Uttar Pradesh.

Evaluation and mapping of aerosol optical depth in Southeast Asia using ground-based and satellite data for solar energy applications

Rusmadee Sabooding — 2025-04-01

This study presents column integrated AOD readings from satellites and from fourteen sunphotometers in southeast Asia. The comparison result shows that AOD estimated from Aqua satellite and sunphotometeris in reasonable agreement with the measurement, with RMSE of 0.09–0.42 for monthly cases. The AOD obtained by comparing data from the OMI with those obtained from sunphotometer observations was found to be of good agreement, with a RMSE of 0.27 and MBE of –0.01. The study presents AOD resource maps generated by GIS, Kriging (Geographic Information System) utilizing OMI data for 16-year period 2005–2020. The seasons for southeast Asia are defined as summer (March-May) and winter (June–February).According to upper southeast Asia seasonal patterns, the AOD was higher and reached its maximum in the summer but was lower and reached its minimum in winter. In the case of lower southeast Asia, the AOD was maximum in the winter but was minimum in summer. The maps reveal that geographic characteristics of eleven countries and the tropical monsoons had a significant impact on regional distribution of AOD. This work presents a model for determining AOD using organic carbon and black carbon from MERRA-2 and specific humidity from GLDAS. The model was created to estimate daily AOD (R = 0.71) and monthly AOD (R = 0.83) based on 5-year (2012–2016) AOD data from these stations, and independent data were used to validate for the 4-year period (2017 to 2020). It can be seen that values of monthly AOD predicted by the model had an RMSE of 0.20. The model2 monthly AOD (R = 0.94) was developed using visibility (195 meteorological stations) and angstrom expernent (Aqua) to enable the estimation of AOD. When compared to an independent data set, this model2 performs reasonably, with RMSE and MBE of 0.23 and –0.01, respectively.

Tridecadal aerosol impact on meteorology in the arid and humid regions of India (1991-2022)

Arban Shongdor Youroi — 2025-04-01

This study investigates tri-decadal (1991-2022) trends in near-surface and columnar aerosols in two distinct regions of India: the arid region (encompassing Gujarat, Punjab, Haryana, Rajasthan, and Delhi) and the humid Northeast Region (including Meghalaya, Assam, Nagaland, Manipur, Mizoram and Tripura) to comprehend the relation between these aerosols and meteorological parameters in these two regions. By employing satellite reanalysis datasets, including the Indian Monsoon Data Assimilation and Analysis (IMDAA) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2), the study assesses spatial and temporal variations in aerosol optical depth (AOD) and Ångström Exponent (AE), considering diverse aerosol types such as black carbon, sulfate, dust, and sea salt. Results reveal distinct AOD characteristics between arid and humid regions, with differing medians and variability. Monthly variations highlight distinctive patterns in aerosol concentrations, influenced by both natural sources and anthropogenic activities. Wind speed and direction was investigated with emphasis on how wind circulation patterns elucidate aerosol dispersion, highlighting seasonal influences. Correlation analyses between aerosols and meteorological anomalies reveal negative correlations with precipitation and positive correlations with temperature, indicating aerosol indirect and direct effects, respectively. Continuous Wavelet Transform (CWT) was utilized to assess long-term periodicities of AOD and precipitation over the two regions which are subjected to distinct abundance of rainfall. This study offers a brief insight into the interaction of prevailing aerosols in these environmental settings and the local climate over past three decades with notable distinctions over the two regions.

Hydro-thermal regimes and their impact on relative weather disparities and grain yield of wheat in central Punjab

Sony Bora — 2025-04-01

The temperature and humidity factors, known as Relative temperature disparity (RTD) and relative humidity disparity (RHD) along with phenology and crop yield were found to be significantly influenced by various sowing environments and irrigation regimes. RTD and RHD ranged between 47.71 to 64.65 and 34.68 to 63.07 respectively in Ludhiana, Punjab. The field experiment was conducted during the rabi season of 2021-22 and 2022-23 at Ludhiana (30.90° N, 75.85 °E and 247m above MSL) in split plot design with four replications with three dates of sowing ((D₁= 27 October, D₂= 17 November, D₃= 8 December) and 3 irrigation regimes (I₁= 4 irrigations at CRI, Jointing, 50% Flowering, Soft dough stages, I₂= 3 irrigations at CRI, Flag leaf emergence, soft dough stage, I₃= 2 irrigations at Jointing, Soft dough stage). The crop sown on 27 October took the maximum number of days to attain physiological maturity, followed by crop sown on 17 November and 8 December. Wheat sown on 17 November (4257.7 kg/ha) along with I₁ irrigation level (4114.7 kg/ha) recorded the maximum yield. Higher RTD at vegetative stages (CRI, booting) and reproductive stage (milking) and lower RTD at maturity as well as higher RHD at booting and milking and lower at CRI and maturity resulted in higher yield in wheat sown on 17 November. With respect to timely sown crop, delay in sowing by 20 days resulted in decrease in the yield by 25.8 % while, advancement in sowing by 20 days indicated a decrement in the yield by 7.7 %.

Evaluating the impact of agrometeorological advisory services on crop yields using propensity score matching method in Karnataka's rainfed regions

Rakesh Gomaji Nannewar — 2025-04-01

The impact of Agrometeorological Advisory Services (AAS) on agricultural productivity in four districts in the northern part of the state of Karnataka in India is assessed in this paper. We particularly focus on the role of District Agrometeorological Units (DAMUs) prior to their discontinuation in 2024. The study examines the correlation between access to AAS and crop yields for four major Kharif crops, viz., pigeon pea, pearl millet, maize, and jowar, using the Propensity Score Matching (PSM) method.

Our results indicate a significant positive impact of AAS on crop yields. Yields for pigeon pea, pearl millet, jowar, and maize are higher by 24kg/acre, 41 kg/acre, 52 kg/acre, and 102 kg/acre, respectively, for beneficiaries as compared to non-beneficiaries. This translates into potential economic gains of approximately 962 ± 162 million across the four districts, assuming a similar proportion of non-beneficiaries across the districts as encountered in the sample. Notably, DAMUs, strategically placed in the premises of the Krishi Vigyan Kendras (KVKs), have played a pivotal role in disseminating these advisories, especially in Koppal and Ballari districts, where over 70% of cultivators reported having accessed AAS either directly or indirectly.

Given that weather variability and its consequent impacts on agriculture are only projected to increase with climate change, our results indicate the need to enhance the content and dissemination of AAS by reestablishing and strengthening the DAMUs to maintain, if not improve, agricultural yields and help smallholder farmers adapt.

A smartphone application for estimating irrigation frequency and runtime for Californiancrops based on the water balance approach

Daniel Simonet — 2025-04-01

Optimizing irrigation ensures that plants receive the right amount of water without any loss from deep percolation or drainage. However, non-professional crop growers, such as gardeners and garden hobbyists, have limited access to data-driven solutions to optimize irrigation cycles. This app aims to fill this gap by providing Irrigation Frequency and Runtime for a range of selected crops in California. The evapotranspiration-based smartphone app uses locally calibrated crop coefficients, Maximum Allowed Depletion factors, and weather data to determine the average daily irrigation runtime. It is also the first smartphone application that calculates effective rainfall for any selected location in California. In the future, the app could be applied to other U.S. states.

Cyclonic and anticyclonic circulations of 850 hPa over India and adjoining areas based on highly packed hand drawn streamline charts : part 1 - characteristics

Anish Kumar M Nair — 2025-04-01

Cyclonic (‘C’) and Anticyclonic (‘A’) circulations play a decisive role in deciding the weather of a region. Therefore, understanding the characteristics of circulation and their spatio-temporal distribution has become important. The present exploratory study characterizes circulations of 850 hPa pressure level over India and adjoining regions. Highly packed wind streamlines are drawn for 850 hPa integrating wind data from satellites, radiosondes, pilot balloons and Doppler Weather Radars. ‘C’ and ‘A’ circulations centre points are identified and the characteristics of their distribution are explored spatially on seasonal, long-term and monthly time scale over the Indian and surrounding regions for 2014 to 2020. Several meteorological significant features are visually manifested in ‘C’ and (‘A’) circulations and their role in dynamics is discussed in the manuscript. Frequency distribution shows wide-spread and large numbers of (‘C’) circulations are present over the north and northwest India, the Indo-Gangetic plain, and in the east equatorial Indian Ocean region. Seasonal analysis reveals an association with the southwest monsoon trough, the head Bay of Bengal lows, heat lows over land and in the southern peninsula. (‘A’) circulation centre point distribution is concentrated further south of the trough region and concentrated mainly on the land. The winter season has noticeably more (‘A’) circulation which could be attributed to the descending limb of the Hadley Cell. Spatial distribution of circulation shows land-sea contrast. The analysis has several applications, including operational weather forecasting, aviation and ballistic meteorology and scope for advanced research.

Tornado over West Bengal on 25 May, 2021 in association with Very Severe Cyclonic Storm - YAAS over Bay of Bengal

A. J. Litta — 2025-04-01

Tropical cyclone (TC) tornadoes are brief and often unpredictable events that can produce fatalities and create economic loss. Climatological studies characterize TC spawned tornadoes as primarily originating from miniature supercells in the outer rainbands. The tornadic features forecasting and radar detection are particularly challenging. In this paper we analyzed the observation data which indicated the occurrence of a tornado over North 24 Parganas and Hooghly districts of West Bengal on 25 May, 2021 in association with Very Severe Cyclonic Storm (VSCS) "YAAS'' which crossed Odisha coast around 0600 UTC of 26^thMay, 2021. The tornado locations were in the convective outer bands of the VSCS "YAAS'' at 0900 UTC of 25^thMay, 2021. The characteristics of the tornado were studied with Kolkata doppler weather radar images, vertical wind profile and sounding data. This tornadoexhibited characteristics similar to typical supercell storms such as hook echo and mesocyclone. This study brings out the conditions favourable for the occurrence of a TC tornado over North 24 Parganas and Hooghly districts of West Bengal in association with VSCS "YAAS''.

Influence of sunspot activity and EL Niño southern oscillation on northeast monsoon rainfall in the coastal districts of Tamil Nadu

S. Lakshmi — 2025-04-01

The current study is focused on establishing the effects of global variables such as the Sunspot Number (SSN)and El Niño Southern Oscillation (ENSO) on the local parameter, North East Monsoon Rainfall (NEMR) in the coastal districts of Tamil Nadu (CDTN) India from 1901-2020. In the rising region of the solar cycle, excess precipitation is observed within about two years from the year of minimum SSN. The solar cycle and rainfall (RF) have a 1-4year phase delay (solar cycle leads) of solar maximum. The periodicity and phase delay of SSN and precipitation have been identified using Fourier Transformation and cross-correlation, respectively. During the solar maximum, the precipitation is observed to be less. The obtained results elucidate the inverse relationship between solar maximum and NEMR as well as the invariance of NEMR during solar minimum. El Niño/La Niña and the sunspots maximum/minimum number have a high likelihood of co-occurring. The correlation map analyzes the composite of OLR and excess/deficit NEMR years across two consecutive El Niño/La Niña years. This analysis confirms that prolonged El Niño events lead to excess rainfall, while La Niña events result in rainfall deficit.The Morlet wavelet transformation(MWT) analysis has been used to examine the temporal connection between SSN, ENSO, and NEMR cyclicities. The findings of this study may be useful in predicting future droughts and wet years based on sunspot activity and to the policymakers for better management of water resources.

Extremities analysis over Parambikulam Aliyar project basin of Tamil Nadu

Guhan Velusamy — 2025-04-01

Study examined the evaluation of contemporary space-time patterns of extreme temperature and precipitation values in Parambikulam Aliyar Project basin for the years 1981 to 2017. The investigation of extremes conducted in Aliyar sub-basin Catchment area, Aliyar sub-basin command area, Palar sub-basin Catchment area, Palar sub-basin command area, PAP hill region, PAP plain region, PAP whole basin. The results clearly revealed that represent consecutive dry days in Aliyar sub-basin Catchment area showed slightly increasing trend (from 56 days in 1981 to 63 days in 2017) which could served as an indicator of dryness and chance of seasonal drought occurrence. In the Palar sub-basin catchment areas under the PAP basin, consecutive dry days do not show any trend. With regards to consecutive wet days, PAP hill areas are showing a significant positive trend (P-Value of 0.038, and R² of 0. 432). The trend in the simple precipitation intensity index (SDII) showed slight upward movement (7 to 8mm/ day). In the command area, only rx5day showed a major increase of 1.25 mm/year variation. The mean reduction in the mean daily temperature and mean minimum temperature as per the Sen’s slope estimator stands at -0.011 °C/ Year and -0.003 °C/ year for Aliyar sub-basin catchment and -0.012 °C/ Year and -0.003 °C/ year for Aliyar command area. Spatial extent of PAP hilly region and PAP as a whole showed a slightly rising trend in precipitation extreme events. However, in PAP plain areas, slight reductions were noticed in r20mm, rx3day, and rx5day precipitation indices. These findings highlight the importance of long term climate data analysis for decision making and adaptation strategies in the face of climate extremities.

Comparison of SPI and SPEI indices for drought assessment in eastern part of Satara district of Maharashtra, India

Prakash T. Waghmare — 2025-04-01

Drought indices are normally used as a tool to assess drought conditions. In the proposed study, we have assessed meteorological drought conditions using the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)for the eastern part of the Satara district of Maharashtra, India. For this investigation, precipitation and temperature data have been used from the period of 1979 to 2014 for sixteen meteorological stations. The same data was collected from the Climate Forecast System Reanalysis (CFSR) website.The result reveals that, according to SPI, severe dry conditions are more prominently observed at stations 2, 3, 8, 9, 11 and 12. Moderate dry conditions are observed at stations 1, 4 and 7. The SPI reveals that notable severe drought events were found in the years 1983 to 1988, 1992, 2000 to 2004, 2007, 2008, 2012 and 2013. According to SPEI, every station has experienced a dry and wet period. Extreme dry conditions are notably observed at stations 2, 3, 5, 6, 8, 9, 11, 12, 15 and 16. Moderate dry conditions are prominently observed at stations 1, 4 and 7. The SPEI reveals that notable extreme drought events were found in the years 1985 to 1990, 1993, 2000 to 2007, 2009, 2013 and 2014. The correlation analysis revealed that there is a strong linear relationship between the SPI and SPEI values.

Identification of faults in the subsurface of Java Island using the ambient noise tomography method

Tio Azhar Prakoso Setiadi — 2025-04-01

This study applies the Ambient Noise Tomography (ANT) method to identify faults in the subsurface seismic structure of Java Island, characterized by complex tectonic conditions. The research utilizes waveform data recorded in 2021 by 99 BMKG stationary seismic sensors distributed across Java Island. Data processing includes single data preparation, cross-correlation, stacking, dispersion curve measurement, group velocity tomography, and result interpretation. The inversion process generates tomographic images of Rayleigh wave group velocities ranging from 1.88 km/s to 2.60 km/s, revealing significant contrasts in velocity anomalies. These contrasts, located at the boundaries between low and high velocity zones, are strongly correlated with fault lines and volcanic zones across the island. The results demonstrate the capability of the ANT method to delineate subsurface geological structures, including active fault systems, with high precision.

Weather in India

Editor Mausam — 2025-04-01

Chief features

(i) In the Hot weather season of 2024, only one intense low-pressure system, severe Cyclonic storm, “Remal,” formed over the Bay of Bengal during the season from 24-28 May. Along with this severe cyclonic storm, a low-pressure area formed over the Arabian Sea on 23-24 May.

(ii) The hot weather season 2024 with reference to severe heat wave/heat wave* conditions was mild but began in the last week of March continued to first week of April and again appeared during last week of April. In the month of May, the heat wave/severe heat wave conditions were observed over northwest, central India and eastern parts of India.

(iii) The seasonal rainfall over homogenous region of central India was excess while the country as a whole and remaining three regions recorded normal rainfall. Rainfall for all the months (March to May) for the country was normal to above normal except some sub-divisions from the south peninsula and northwest India where it was deficient.

(iv) Thunderstorms/hailstorms were frequent throughout the season over the country.

(v) Monsoon advanced into some parts of the Maldives & Comorin area and some parts of the South Bay of Bengal, Nicobar Islands, and South Andaman Sea on 19 May, 2024. It reached Kerala on 30 May, two days prior to its normal date, i.e., 1 June.

Probable maximum precipitation estimation and its spatio-temporal analysis

Ila Agnihotri — 2025-04-01

Probable Maximum Precipitation (PMP) is the greatest depth of precipitation for a given duration meteorologically possible for a design watershed or a given storm area. It can be thought of as a reasonable upper limit of the rainfall that could be anticipated in a given region.

PMP values have been estimated for 173 rainfall monitoring stations in Maharashtra, using 113 years long period daily rainfall data applying Modified Hershfield technique. Station data captures extreme behavior of rainfall in a better way as compared to gridded rainfall data sets as it represents normalized versions. The method is based on enveloped frequency factor analysis and on the assumption that long term rainfall records well capture information on extreme rainfall events in an area. The enveloping curves were generated for each of the four meteorological sub-divisions of Maharashtra, namely Konkan & Goa, Madhya Maharashtra, Marathwada, and Vidarbha.

In Maharashtra, 1-day PMP varies from 22.57 to 95.26 cm, 2-day PMP varies from 31.66 to 127.79 cm, and 3-day PMP ranges from 36.1 to 134.22 cm. The highest values of1-3 day observed rainfall and PMP were found to be located in the Konkan and Goa sub-division stations. Most variation was observed in the Konkan and Goa sub-division stations for 1-day PMP, whereas the Madhya Maharashtra sub-division exhibitedthe highest variation for 2-day and 3-day PMP. Konkan Goa sub-division represents high rainfall and high PMP region, so more preparedness needs to be realized in this region.

Role of Southern Hemispheric Equatorial Trough in the development of Indian Summer Monsoon

Gauravendra Pratap Singh — 2025-04-01

An attempt has been made in the present paper to examine the usefulness of Outgoing Longwave Radiation (OLR) over Southern Hemispheric Equatorial Trough (SHET) in foreshadowing Indian Summer Monsoon Rainfall (ISMR) qualitatively during extreme ISMR (deficient or excess) years. The daily OLR data analyzed in the study are computed on weekly basis over June- September for the study of lagged correlation between the SHET and ISMR. For developing a model for Long Range Forecasting of ISMR and its verification OLR data for a period of 30 years (1981-2010) have been used.However, SHET is not always active across its entire zone of 40°E to 100° E. To compare the relative role of SHET activity in its western and eastern parts on the variability of rainfall over India as a whole, the SHET zone has been divided into three parts: Western SHET (WSHET) (-5° to -15°S, 40°-60°E), Central SHET (CSHET) (-5° to -15°S, 60°-80°E) and Eastern SHET (ESHET) (-5° to -15°S, 80°-100°E). The mean OLR was computed by averaging throughout the WSHET, CSHET, and ESHET regions for 20 weeks of the season every 30 years (1981-2010). In the current study, WSHET and CSHET had a good negative correlation (-0.52 and -0.55) with AISMR. The significant features of SHET in three excess years (1983, 1988 and 1994) show that there is marked difference in the spatial and temporal variability OLR in monthly as well as seasonal scale. During deficient monsoon years (1982, 2002 and 2009), it was observed that convection was more than normal over Pacific region as well as over southern equatorial Indian Ocean. During deficient years, Eastern Equatorial Indian Ocean SHET (ESHET) OLR was significantly negatively correlated with AISMR whereas there is no significant correlation with Western Equatorial Indian Ocean SHET (WSHET) OLR.