Seasonal intensity-duration-frequency relationships for Pelotas, Rio Grande do Sul, Brazil

ABSTRACT Although several studies have evaluated the intensity-duration-frequency relationships of extreme rainfall events, these relationships under different seasonal conditions remain relatively unknown. Thus, this study aimed to determine whether the intensity-duration-frequency relationships obtained seasonally from the rainfall records in the winter and summer represent the maximum rainfall events for the city of Pelotas, Rio Grande do Sul state, Brazil. Pluviographic data from 1982 to 2015 were used to create two seasonal series: one for the summer from December 21 to March 20 and the other for the winter from June 21 to September 22. These seasonal relationships were compared with the annual pluviographic data. The intensity, duration, and frequency relationships obtained from the summer rain data adequately represented the maximum rainfall in Pelotas, Rio Grande do Sul state, Brazil. The maximum intensity values of rainfall obtained from the relationship of intensity, duration, and frequency for the winter did not adequately encapsulate the occurrence of rain with greater intensities.

A synthetic view of rainfall intensification in the West African Sahel

The West African Sahel has been facing for more than 30 years an increase in extreme rainfalls with strong socio-economic impacts. This situation challenges decision-makers to define adaptation strategies in a rapidly changing climate. The present study proposes (i) a quantitative characterization of the trends in extreme rainfalls at the regional scale, (ii) the translation of the trends into metrics that can be used by hydrological risk managers, (iii) elements for understanding the link between the climatology of extreme and mean rainfall. Based on a regional non-stationary statistical model applied to in-situ daily rainfall data over the period 1983-2015, we show that the region-wide increasing trend in extreme rainfalls is highly significant. The change in extreme value distribution reflects an increase in both the mean and variability, producing a 5%/decade increase in extreme rainfall intensity whatever the return period. The statistical framework provides operational elements for revising the design methods of hydraulic structures which most often assume a stationary climate. Finally, the study shows that the increase in extreme rainfall is more attributable to an increase in the intensity of storms (80%) than to their occurrence (20%), reflecting a major disruption from the decadal variability of the rainfall regime documented in the region since 1950.

Recent Changes in Average Recurrence Interval Precipitation Extremes in the Middle-Atlantic United States

Increases in the frequency of extreme rainfall occurrence have emerged as one of the more consistent climate trends in recent decades, particularly in the eastern United States. Such changes challenge the veracity of the conventional assumption of stationarity that has been applied in the published extreme rainfall analyses that are the foundation for engineering design assessments and resiliency planning. Using partial duration series with varying record lengths, temporal changes in daily and hourly rainfall extremes corresponding to average annual recurrence probabilities ranging from 50% (i.e. the 2-year storm) to 1% (i.e. the 100-year storm) are evaluated. From 2000 through 2019, extreme rainfall amounts across a range of durations and recurrence probabilities have increased at 75% of the long-term precipitation observation stations in the Middle-Atlantic region. At about a quarter of the stations, increases in extreme rainfall have exceeded 5% from 2000 through 2019, with some stations experiencing increases in excess of 10% for both daily and hourly durations. At over 40% of the stations the rainfall extremes based on the 1950-1999 partial duration series show a significant (p >0.90) change in the 100-yr ARI relative to the 1950-2019 period. Collectively the results indicate that given recent trends in extreme rainfall, routine updates of extreme rainfall analyses are warranted on 20-year intervals.

Ground validation of GPM IMERG-F precipitation products with the point rain gauge records on the extreme rainfall over a mountainous area of Sumatra Island

Accurate satellite precipitation estimates over areas of complex topography are still challenging, while such accuracy is of importance to the adoption of satellite data for hydrological applications. This study evaluated the ability of Integrated Multi-satellitE Retrievals for GPM -Final (IMERG) V06 product to observe the extreme rainfall over a mountainous area of Sumatra Island. Fifteen years of optical rain gauge (ORG) observation at Kototabang, West Sumatra, Indonesia (100.32°E, 0.20°S, 865 m above sea level), were used as reference surface measurement. The performance of IMERG-F was evaluated using 13 extreme rain indexes formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The IMERG-F overestimated the values of all precipitation amount-based indices (PRCPTOT, R85P, R95P, and R99P), three precipitation frequency-based indices (R1mm, R10mm, R20mm), one precipitation duration-based indices (CWD), and one precipitation intensity-based indices (RX5day). Furthermore, the IMERG-F underestimated the values of precipitation frequency-based indices (R50mm), one precipitation duration-based indices (CDD), one precipitation intensity-based indices (SDII). In terms of correlation, only five indexes have a correlation coefficient (R) > 0.5, consistent with Kling–Gupta Efficiency (KGE) value. These results confirm the need to improve the accuracy of the IMERG-F data in mountainous areas.

Detecting Extreme Rainfall Events Using the WRF-ERDS Workflow: The 15 July 2020 Palermo Case Study

In this work, we describe the integration of Weather and Research Forecasting (WRF) forecasts produced by CIMA Research Foundation within ITHACA Extreme Rainfall Detection System (ERDS) to increase the forecasting skills of the overall early warning system. The entire workflow is applied to the heavy rainfall event that affected the city of Palermo on 15 July 2020, causing urban flooding due to an exceptional rainfall amount of more than 130 mm recorded in about 2.5 h. This rainfall event was not properly forecasted by meteorological models operational at the time of the event, thus not allowing to issue an adequate alert over that area. The results highlight that the improvement in the quantitative precipitation scenario forecast skills, supported by the adoption of the H2020 LEXIS computing facilities and by the assimilation of in situ observations, allowed the ERDS system to improve the prediction of the peak rainfall depths, thus paving the way to the potential issuing of an alert over the Palermo area.