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.

Variability and probabilistic estimates of rainfall extremes In Bangladesh during the southwest monsoon season

The present study describes the temporal and spatial distributions of mean monthly rainfall and its variability together with the spatial distributions of the probabilistic estimates of rainfall extremes over Bangladesh during the- southwest monsoon season. The- probabilistic rainfall extremes have been computed for IWO lime scales: (a) in I year out of 4 years, and (b) in 1 year out of 10 years -representing relatively less extreme events and extreme events respectively. The mean monthly rainfall increases from June to July at most places over Bangladesh and then decreases up to September. The variability of rainfall decreases with increasing rainfall up to July at many places and then increases up to September. The study also reveals that the mean rainfall and the- probabilistic rainfall extremes are maximum over the southern and north-eastern parts of the country where the variability of rainfall is low and the rainfall is reliable. There exists a belt of low rainfall over the- central part of Bangladesh roughly between 23oN and 24°N. The rainfall gradients are maximum over north-eastern Bangladesh and the gradients of the probabilistic high rainfall are more than those of the probabilistic low rainfall in this area.

The role of cyclonic activity in tropical temperature-rainfall scaling

The attribution of changing intensity of rainfall extremes to global warming is a key challenge of climate research. From a thermodynamic perspective, via the Clausius-Clapeyron relationship, rainfall events are expected to become stronger due to the increased water-holding capacity of a warmer atmosphere. Here, we employ global, 1-hourly temperature and 3-hourly rainfall data to investigate the scaling between temperature and extreme rainfall. Although the Clausius-Clapeyron scaling of +7% rainfall intensity increase per degree warming roughly holds on a global average, we find very heterogeneous spatial patterns. Over tropical oceans, we reveal areas with consistently strong negative scaling (below −40%∘C−1). We show that the negative scaling is due to a robust linear correlation between pre-rainfall cooling of near-surface air temperature and extreme rainfall intensity. We explain this correlation by atmospheric and oceanic dynamics associated with cyclonic activity. Our results emphasize that thermodynamic arguments alone are not enough to attribute changing rainfall extremes to global warming. Circulation dynamics must also be thoroughly considered.

Tropical Origins of the Record-breaking 2020 Summer Rainfall Extremes in East Asia

The East Asian countries have experienced heavy rainfalls in boreal summer 2020. Here, we investigate the dynamical processes driving the East Asian rainfall extremes during July and August. The Indian Ocean basin warming in June can be responsible for the anticyclonic anomalies in the western North Pacific (WNP), which contribute to the zonally-elongated rainfalls in East Asia during July through an atmospheric Rossby wave train. In August, the East Asian rainfall increase is also related to the anticyclonic anomalies in the subtropical WNP, although it is located further north. It is suggested that the north tropical Atlantic warming in June partly contributes to the subtropical WNP rainfall decrease in August through a subtropical teleconnection. The rainfall decrease in the subtropical WNP region during August drives the local anticyclonic anomalies that cause the rainfall increase in East Asia. The tropical Indian Ocean anomalously warmed in June and the subtropical WNP rainfall decreased in August 2020, which played a role in modulating the WNP anticyclonic anomalies. Therefore, the record-breaking rainfalls in East Asia occurred during July and August 2020 can potentially be explained by the teleconnections induced by the tropical origins, such as tropical Indian Ocean warming and subtropical WNP rainfall decrease.

The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy

The dependence of rainfall on elevation has frequently been documented in the scientific literature and may be relevant in Italy, due to the high degree of geographical and morphological heterogeneity of the country. However, a detailed analysis of the spatial variability of short-duration rainfall extremes and their connection to the landforms does not exist. Using a new, comprehensive and position-corrected rainfall extreme dataset (I2-RED), we present a systematic study of the relationship between geomorphological forms and the average of rainfall extremes (index rainfall) across the whole of Italy. We first investigated the dependence of sub-daily rainfall depths on elevation and other landscape indices through univariate and multivariate linear regressions. After analyzing the results, we repeated the analysis on geomorphological subdivisions of Italy. The results of the national-scale regression analysis did not confirm the assumption of elevation being the sole driver of the variability of rainfall extremes. The longitude, latitude, distance from the coastline, morphological obstructions and mean annual rainfall resulted to be significantly related to the index rainfall, and to play different roles for different durations (1- to 24-hours). However, when comparing the results of the best multivariate regression models with univariate regressions for morphological subdivisions, we found that “local” rainfall-topography relationships within the geomorphological subdivisions outperformed the country-wide multiple regressions and offered a reasonable representation of the effect of morphology on rainfall extremes.