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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]

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]