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Agriculture is the most vulnerable sector to climate change and weather anomalies. In rainfed ecosystems, rainfall amount and distribution are the deciding factors for crop planning. Rainfall variability and trend analysis help to minimize weather related risk and enhance the productivity by proper crop planning. The study on rainfall distribution and its trend was assessed in a rainfed area of Ramanathapuram district of Tamil Nadu, India by using Simple descriptive statistics along with non-parametric analysis of Men-Kendall analysis, Sen's slope estimator; innovative trend analysis and sequential Men-Kendall test were carried out to understand the quantity of rainfall and rainy-day variability for the period of 1982 to 2022. The results indicated that the mean annual rainfall is 716 mm and spread over 56 rainy days with 21 percent of coefficient of variation. Seasonal analysis indicated that, there was no significant trend was observed among the seasons, but NEM showed a significant increase in trend (p-value = 0.048) with a positive magnitude of 3.2 mm/year of rainfall. An increasing trend in heavy rainfall events during the NEM season is evident with 92 percent. [ABSTRACT FROM AUTHOR]

Background: In peninsular India, the frequency of climate-related risks is significantly lowering agricultural productivity and farmers' standard of living. Reducing losses in the agriculture sector requires precise and timely weather information, weather based advisories on crop production, protection and post-harvest. Disseminating agromet advisories directly to the farmers using ICT tools allows farmers to adopt appropriate corrective measures, minimize loss and ensure climate resilient agriculture. In this sense, the Tamil Nadu Agricultural University established an Automated Agromet Advisory Web cum Mobile App (TNAU-AAS) in 2018, which sends location, crop and stage specific agromet advisories directly to farmers' mobile App. Methods: TNAU-AAS App was evaluated in pulse crops as "Piloting pulse produce support system through ICT enabled services" between 2019 and 2021 in three TNAU centers under three different eco systems namely irrigated (Coimbatore), rice fallow (Aduthurai) and rainfed (Kovilpatti). Pulse growing farmers were registered in this smartphone application for agromet advisory based response farming. Result: The TNAU-AAS App had delivered approximately 10-12 advisories to each farmer, tailored to their unique crop and stage during the cropping period. Survey results inferred that the farmers received timely notifications on their mobile phones, 2-3 days in advance, which assisted them in preplanning. Occurrences of pests and diseases were well aligned (68-83%) with TNAU-AAS recommendations and the climate vulnerability of non AAS farmers is more than AAS farmer. According to partial budget analysis, the irrigated, rice fallow and rainfed black gram farmers have gained Rs. 2800, Rs. 2300 and Rs. 1900 per ha, respectively. It is concluded that the ICT-enabled agromet advisory system guarantees timely alerts, boosts labor and land productivity, lowers input loss and shields crops from weather-induced pests and diseases as well as climatic variability risk. [ABSTRACT FROM AUTHOR]

The utilization of satellite based and reanalysis climatic data has significantly advanced in hydro meteorological research in regions with limited observations. Before implementing satellite based and reanalysis-based data in specific locations, it is crucial to thoroughly assess their accuracy. This study focused on evaluating the accuracy of reanalysis climate data and Tropical Rainfall Measuring Mission (TRMM) satellite rainfall data compared to observed climate data in different agro climatic zones of Tamil Nadu, India. The evaluation was conducted on a monthly basis from 1981 to 2017. Furthermore, the performance of the precipitation product obtained from Tropical Rainfall Measuring Mission was also evaluated with reanalysis data at weekly basis from 1998 to 2017. Various statistical methods such as bias, root mean square error, index of agreement, and refined index of agreement were employed for this assessment. The results show that, the reanalysis and observed monthly data for rainfall, maximum and minimum temperature show a strong correlation in all zones of Tamil Nadu, except for the High rainfall and Hilly zone. TRMM rainfall values effectively capture rainfall data, but satellite data can overestimate and underestimate rainfall amounts, as revealed by the validation of satellite and reanalysis precipitation data. [ABSTRACT FROM AUTHOR]

The article focuses on the study on the impact of El Niño-Southern Oscillation (ENSO) induce rainfall on the productivity of maize farm in Tamil Nado, India. Topics discussed include the measurement of ENSO condition using the Southern Oscillation Index (SOI), the influence of SOI phases on the characteristics of rainfall during the rainfed cropping period, and the statistical analysis of the effect of SOI phase son maize growth and yield.

Drought is one of the recurrent climate phenomenon that crippling the societal and economic development of the agrarian country. It occurs almost everywhere, although its features vary from region to region. The present study was undertaken to assess the drought in Tamil Nadu using the precipitation data of historic climatic period (1981-2017) with high spatial resolution (17 Km). Rainfall deviation from the long term mean during SWM, NEM and annual time scale was calculated at district level for identifying the drought prone districts in Tamil Nadu. The results showed that the frequency of the drought events was higher during the SWM as compared to NEM. Results indicated that Tirunelveli, Theni, Tiruppur, Karur, Tiruchirapalli districts were prone to the drought during SWM. As the NEM is the primary rainfall season and active crop growing period, suitable drought mitigation strategies need to be designed for the districts viz., Kanyakumari, Salem, Thiruvallur, which are highly affected due to deficit rainfall during NEM. [ABSTRACT FROM AUTHOR]

Several factors are responsible for recent climatic anomalies includes seasonal and inter-annual variability of rainfall in the region in which regional and global sea surface temperature (SST) changes is the most significant factor. It is well recognized that El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability on seasonal to inter-annual scales and its impacts are felt worldwide. Seasonal to inter-annual rainfall fluctuations strongly affect the success of agriculture and the abundance of water resources. Daily rainfall data at district scale was obtained from India Meteorological Department (IMD) for a period of 43 years (1971–2013) was categorized based on the ENSO episodes and the analysis was performed for the rainfed cropping period (RCP, September–December). A week (7 days) with the cumulative rainfall amount of 50 mm was considered as one wet spell. Non rainy days observed continuously for a decade (10 days) that period was considered to be one dry spell. Results revealed that El Niño conditions positively influenced the rainfall. Compared to neutral years, La Niña years received less rainfall as it showed the negative deviation in most of districts of Tamil Nadu. More wet spell and lesser dry spell weeks was observed under El Niño condition while the lesser wet spell and more dry spell was observed under La Niña conditions. Higher amount of rainfall during El Niño led to more number of wet spells under El Niño event. [ABSTRACT FROM AUTHOR]

El Niño Southern Oscillation (ENSO) is one of the most important drivers of climate variability. To study the impact of ENSOonseasonal rainfall over Tamil Nadu, historical weather data for the period of 43 years (1971-2013) were categorized based on the ENSO episodes and the analysis was performed for assessing ENSO linked climate variability (onset and cessation) for North east monsoon rainfall (NEM: October - December) and rainfed cropping period (September - December) over Tamil Nadu. Onset was determined using the pentad analysis performed from 1st October through 31th October, considering first pentad with quantum of 10 mm of rainfall followed by four consecutive pentads of 10 mm of rainfall per pentad. The same approach was followed for deciding the onset of sowing rains for rainfed cropping period starting from 1st September to 10th October. In NEM and rainfed cropping period, cessation of monsoon was seen in December month. If the cessation didn't occur during December, the cessation time was noted in November month and the season was considered as the last day that received rainfall amount of > 2.5 mm. In NEM, higher per cent of years had onset in the slot from 1st to 5th of October (65.0, 63.4, 65.2 per cent of El Niño, La Niña and Neutral years, respectively). Few years were in neutral phase (26.3 %) and in El Niño (19.4 %) andunderLa Niña (15.2%) phase the results showed the onset happened between 6th and 10th of October. In most of the El Niño years (68 %), sowing rain occurred during 1st week of September (1st to 7th September), while in 40 per cent of the La Niña years sowing rain was delayed by one week and received during 2nd week of September. Cessation was earlier in most of the La Niña years as compared to El Niño and neutral years. [ABSTRACT FROM AUTHOR]