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.

Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study

In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have been reported in the Al-Lith region of western Saudi Arabia that took away many lives and caused disruption in services and trade. To find and examine the extremities and IDF curves, daily rainfall data from 1966 to 2018 is used. The IDF curves are created for a variety of return periods and climate scenarios in three terrain variabilities. This research examines various distributions to estimate the maximum rainfall for several metrological stations with varying return periods and terrain conditions. Three main zones are identified based on ground elevation variability and IDF distributions from upstream in the eastern mountainous area to downstream in the western coastal area. These IDF curves can be used to identify vulnerable hotspot areas in arid areas such as the Wadi AL-Lith, and flood mitigation steps can be suggested to minimize flood risk.

Flexible and consistent quantile estimation for intensity–duration–frequency curves

Assessing the relationship between the intensity, duration, and frequency (IDF) of extreme precipitation is required for the design of water management systems. However, when modeling sub-daily precipitation extremes, there are commonly only short observation time series available. This problem can be overcome by applying the duration-dependent formulation of the generalized extreme value (GEV) distribution which fits an IDF model with a range of durations simultaneously. The originally proposed duration-dependent GEV model exhibits a power-law-like behavior of the quantiles and takes care of a deviation from this scaling relation (curvature) for sub-hourly durations (Koutsoyiannis et al., 1998). We suggest that a more flexible model might be required to model a wide range of durations (1 min to 5 d). Therefore, we extend the model with the following two features: (i) different slopes for different quantiles (multiscaling) and (ii) the deviation from the power law for large durations (flattening), which is newly introduced in this study. Based on the quantile skill score, we investigate the performance of the resulting flexible model with respect to the benefit of the individual features (curvature, multiscaling, and flattening) with simulated and empirical data. We provide detailed information on the duration and probability ranges for which specific features or a systematic combination of features leads to improvements for stations in a case study area in the Wupper catchment (Germany). Our results show that allowing curvature or multiscaling improves the model only for very short or long durations, respectively, but leads to disadvantages in modeling the other duration ranges. In contrast, allowing flattening on average leads to an improvement for medium durations between 1 h and 1 d, without affecting other duration regimes. Overall, the new parametric form offers a flexible and enhanced performance model for consistently describing IDF relations over a wide range of durations, which has not been done before as most existing studies focus on durations longer than 1 h or day and do not address the deviation from the power law for very long durations (2–5 d).

Some aspects of squall over Indira Gandhi International airport, New Delhi

A study is undertaken to analyse the characteristics of squall over Delhi and to find out the potential precursors for its prediction. For this purpose, the squall data of Indira Gandhi International (IGI) airport along with the surface and upper air meteorological parameters recorded by India Meteorological Department have been considered for all individual months over the period of 2001-2010. Apart from the characteristics like period of occurrence, intensity, duration, frequency and nature of squall, the environmental changes due to squall and thermodynamic features and indices leading to squall have been analysed. Higher than normal warming of lower troposphere upto 700 hPa level in March, April & June and at 925 hPa in May accompanied with cold dry air advection leading to lower than normal dew point in middle and upper levels (500-300 hPa in March, May and June, 400-300 hPa in April) are favourable for occurrence of the squall over Delhi. The lower level inversion in March and April only also helps in the occurrence of squall. In monsoon months of July- September, cold and dry air advection in middle and upper tropospheric levels (8- 15° C below normal dew point at 400-300 hPa in July, about 15° C below normal dew point at 300-200 hPa in August and 17- 24° C below normal dew point at 500-300 hPa in September) favours occurrence of squall over Delhi. Unlike pre-monsoon months lower level moisture does not play any role for the occurrence of squall over Delhi in monsoon months. Significantly higher than normal SWEAT index in March to September at 0000 UTC can be used as predictor of squall over Delhi on that day. Total totals index is the next suitable precursor for all the months except June.

Modeling seasonal variations of extreme rainfall on different timescales in Germany

We model monthly precipitation maxima at 132 stations in Germany for a wide range of durations from 1 min to about 6 d using a duration-dependent generalized extreme value (d-GEV) distribution with monthly varying parameters. This allows for the estimation of both monthly and annual intensity–duration–frequency (IDF) curves: (1) the monthly IDF curves of the summer months exhibit a more rapid decrease of intensity with duration, as well as higher intensities for short durations than the IDF curves for the remaining months of the year. Thus, when short convective extreme events occur, they are very likely to occur in summer everywhere in Germany. In contrast, extreme events with a duration of several hours up to about 1 d are conditionally more likely to occur within a longer period or even spread throughout the whole year, depending on the station. There are major differences within Germany with respect to the months in which long-lasting stratiform extreme events are more likely to occur. At some stations the IDF curves (for a given quantile) for different months intersect. The meteorological interpretation of this intersection is that the season in which a certain extreme event is most likely to occur shifts from summer towards autumn or winter for longer durations. (2) We compare the annual IDF curves resulting from the monthly model with those estimated conventionally, that is, based on modeling annual maxima. We find that adding information in the form of smooth variations during the year leads to a considerable reduction of uncertainties. We additionally observe that at some stations, the annual IDF curves obtained by modeling monthly maxima deviate from the assumption of scale invariance, resulting in a flattening in the slope of the IDF curves for long durations.

Study of Impact of Cloud-Seeding on Intensity-Duration-Frequency (IDF) Curves of Sharjah City, the United Arab Emirates

Despite the availability of some studies related to rainfall characteristics in Sharjah city and the UAE, very few of these studies have investigated any causal link between recent cloud-seeding missions and the increasing rainfall intensities and urban floods being experienced. This study has assessed the impact of cloud-seeding operations that started in 2010 on the IDF curves of Sharjah city, The UAE. Hourly rainfall data spanning between 2010 and 2020 available at three stations, namely Sharjah Airport, Al Dhaid, and Mleiha, and provided by the National Center of Meteorology were used. To allow comparison with the pre-cloudseeding (2010) era, these records were extended back to 1992 using the much longer data available at Dubai Airport with the aid of the Self-organizing map approach. The developed IDF curves showed an apparent increase in rainfall intensities after implementing the cloud-seeding missions. In addition, the estimated mean rainfall intensities for three regions of the city were also much higher for the cloudseeded years compared to the pre-cloudseeding period. The study suggests that, while cloud-seeding provides water security benefits, its impact on urban flooding should also be carefully considered in the context of urban development plans.

Stochastic simulation of reference rainfall scenarios for hydrological applications using a universal multifractal approach

Hydrological applications such as storm-water management or flood design usually deal with and are driven by region-specific reference rainfall regulations or guidelines based on Intensity-Duration-Frequency (IDF) curves. IDF curves are usually obtained via frequency analysis of rainfall data using which the exceedance probability of rain intensity for different durations are determined. It is also rather common for reference rainfall to be expressed in terms of precipitation P, accumulated in a duration D (related to rainfall intensity ), with a return period T (inverse of exceedance probability). Meteorological modules of hydro-meteorological models used for the aforementioned applications therefore need to be capable of simulating such reference rainfall scenarios. The multifractal cascade framework, since it incorporates physically realistic properties of rainfall processes (non-homogeneity or intermittency, scale invariance and extremal statistics) seems to suit this purpose. Here we propose a discrete-in-scale universal multifractal (UM) cascade based approach. Daily, Hourly and six-minute rainfall time series datasets (with lengths ranging from 100 to 15 years) over three regions (Paris, Nantes, and Aix-en-Provence) in France that are characterized by different climates are analyzed to identify scaling regimes and estimate corresponding UM parameters (α, C1) required by the UM cascade model. Suitable renormalization constants that correspond to the P, D, T values of reference rainfall are used to simulate an ensemble of reference rainfall scenarios, and the simulations are finally compared with datasets. Although only purely temporal simulations are considered here, this approach could possibly be generalized to higher spatial dimensions as well.