Daily Intensity Index Research Articles

Insights into Rainfall Extremities Across the Agroclimatic Zones of Tamil Nadu, India

Rainfall is a crucial agrometeorological parameter that impacts hydrology and agricultural planning in a region. The spatiotemporal changes in the occurrences of precipitation extremes must be monitored to reduce the hazards caused by the fluctuating rainfall pattern. The extreme rainfall indices for each year categorized under excess, normal and deficit rainfall categories were calculated over the agroclimatic zones of Tamil Nadu using the high-resolution CHIRPS datasets from 1991 to 2022. The results highlighted that High Rainfall Zone has more consecutive wet days (22 days), minimum consecutive dry days (25 days) and Daily Intensity Index with threshold of 2.5 mm (28.6 mm) compared to other zones. The maximum consecutive dry days of 99 days, a high rainy day of 142 days, and minimum daily intensity of 8.9 mm are experienced by the Cauvery Delta Zone, High Altitude and Hilly Zone, and Western Zone, respectively. Overall, the High Rainfall Zone faces a higher number of extreme rainfall events in terms of wet days and intensity, whereas the average maximum consecutive dry days and minimum rainfall intensity is observed over the north eastern zone and north western zone, respectively indicating high dry periods.

Extreme Rainfall and Temperature Changes Assessment on late-twenty-first-century over the Mono River Basin, Togo (West-Africa)

Abstract. This study assessed the extreme rainfall and temperature changes over Mono river basin by the end of 21st century under the highest greenhouse gas emission scenario RCP8.5. Simulations of eight regional climate models (RCMs) provided by Africa-CORDEX program were considered. The maximum and minimum temperatures and rainfall were analyzed. Two groups of indices were analyzed. The first group consists of frequency indices: maximum number of consecutive dry days and wet days. The second group is intensity indices: five-day maximum rainfall and simple daily intensity index. These variables were calculated at annual and seasonal scales. Changes from the baseline period 1971–2000 were computed for far future 2071–2100. As result, almost all the RCMs considered predicted a decrease of the rainfall and increase of maximum and minimum temperatures over most parts of the Mono basin, particularly in the south. Declining mean monthly precipitation and irregular rainy seasons at all scales were exhibited by most of the models. Simple daily intensity and five-day maximum rainfall are projected to decrease by the majority of the used models. As for dry and wet sequences, the RCMs showed an increase of the consecutive dry days and a decrease of wet days.

The use of changes in electricity consumption to assess the condition of the Water Treatment Plant

The article discusses the use of the daily diurnal energy intensity index to assess the efficiency of deepwater aggregates and the technical condition of the water treatment station

Trends and variability in extremes of precipitation in Curitiba – Southern Brazil

ABSTRACTBased on the daily rainfall data since 1889 in Curitiba, one of the largest cities in southern Brazil, a trend towards increased precipitation and more intense rainfall can be seen. The annual and seasonal volume of rainfall has increased, amounts greater than 10, 20 and 40 mm being observed more often, but with a reduction in the number of rainy days and the number of days with rainfall below 10 mm. Seasonal 95th percentile series have increased in summer, fall and winter. In addition, several indices of climate extremes presented significant increasing trends: monthly maximum 1‐day precipitation, annual total precipitation greater than 95th and 99th percentiles, number of consecutive dry days and the daily intensity index. Generalized extreme value (GEV) distribution function parameters also indicated higher occurrence of extremes detected by the increase in both the scale parameter σ and the location parameter μ in summer, fall and winter. The return time for severe rainfall declined in the second half of the period compared to the first, indicating more frequent occurrence of future extreme events. The main climate indices affecting the 95th percentile series were sea surface temperature (SST), South Atlantic Convergence Zone (SACZ) and Southern Oscillation Index (SOI) during spring, and Atlantic Multi‐decadal Oscillation (AMO), Large‐Scale Index for South America Monsoon (LISAM) and SOI during the summer, which explained variability of the extremes at around 20 and 13%, respectively in each season. Regarding the variability of summer, fall and spring total rainfall, they presented values around 20% for the explained variance due to climate indices. Other factors should be investigated to explain the variability such as urbanization, air pollution and local circulations. Dominant oscillation periods in the time series constructed with one monthly extreme appeared at 3 to 8‐year (inter‐annual) cycles, with 12 years (decadal) and around 30–64 years on the inter‐decadal scale. These oscillations have resonance with SOI, SACZ and Southern Annular Mode (SAM) indices (high frequencies), and Pacific Decadal Oscillation (PDO) and AMO (low frequency).