Short Duration Rainfall Intensity Research Articles

Unravelling the complex interplay between daily and sub-daily rainfall extremes in different climates

Understanding short-duration intense rainfall is crucial for mitigating flash floods, landslides, soil erosion, and pollution incidents. Yet, most observations from rain gauges are only available at the daily resolution. We use the new Global Sub Daily Rainfall dataset to explore extreme rainfall at both daily and sub-daily durations worldwide. Employing Single Gauge Analysis (SGA) and pioneering global-scale Regional Frequency Analysis (RFA), we reveal for the first time how Generalized Extreme Value Distribution (GEV) parameters change across climates and data durations (1h, 3h, 6h, 24h, and daily). This marks the first-ever near-global-scale RFA, made possible by the development of an algorithm that automates RFA on observed rainfall datasets. We compare our results with GEV applied to a gridded rainfall reanalysis (ERA5). Our key findings are that: 1) using ERA5, return levels are significantly underestimated across all climates for 1h rainfall and across all data durations for gauges in the tropical climate region. Even when accounting for differences between point and areal estimates, the median 1h return level estimates are approximately 40% lower compared to RFA. We therefore strongly advise against the use of reanalysis gridded rainfall for studying these extremes. 2) While most gauges show similar return levels with RFA or SGA, some differ significantly, and either method may yield the highest values. Thus, we strongly recommend using both SGA and RFA simultaneously to estimate return levels for a robust risk assessment in flood infrastructure design. 3) The interaction between daily and sub-daily GEV shape parameters varies across climate regions, rendering a universal method for inferring sub-daily rainfall extremes from daily extremes (e.g., using Intensity-Duration-Frequency curves) impractical. Our research provides innovative methodological insights that warrant consideration in future studies on rainfall extremes. Our results not only benefit local stakeholders globally but also serve as a crucial validation tool for the rising number of convection-permitting climate model experiments conducted worldwide.

Spatial and temporal characteristics and weather situation analysis of summer monsoon rainstorms in Yangjiang

Abstract The annual average rainfall of summer monsoon rainstorms in Yangjiang is highest in the southeast, decreasing towards the wings. Rainfall most frequently occurs in the early morning and around noon in June, with the western region experiencing the peak slightly earlier than other areas. Short-duration intense rainfall in the south occurs most frequently between 02:00 and 08:00, while in the north, it is more common between 08:00 and 14:00; the 6-hour accumulated rainfall ≥50mm most frequently occurs between 02:00 and 08:00. The weather situation conducive to monsoon rainstorms involves the stability of the South Asian high pressure at 200hPa over the Indochinese Peninsula, with Yangjiang at 500hPa ahead of the southern trough. During the early morning, the southwest monsoon strengthens from 925hPa over the northern Bay of Bengal to the northern South China Sea, pushing northward to Yangjiang’s land, creating the atmospheric conditions for monsoon rainstorms. Moisture primarily enters from the Indochinese Peninsula through the South China Sea, gradually increasing at night and reaching its peak from late night to early morning. The moisture channel and convergence height are below 700hPa. Atmospheric upward motion extends from the mid-to-upper levels to near the surface in the early morning, with the strong center moving from south to north.

A hybrid model coupling process-driven and data-driven models for improved real-time flood forecasting

Accurate and reliable incoming flood forecasting is an important prerequisite for flood warning, flood risk analysis and reservoir flood control operation. This paper proposes a hybrid model for real-time flood forecasting that couples process-driven hydrological models (HMs) with data-driven models (DDMs). The generic hybrid model framework adds DDMs as the post-processing procedure for residual correction to the original results of HMs, and considers multiple uncertainties in input data, parameter and model structure simultaneously. The performance of the hybrid model is evaluated comprehensively in terms of deterministic forecast accuracy, interval forecast reliability, and the reliability and sharpness of probabilistic forecast. Taking the multireservoir system at the east Pi River as a study case, the results indicate that: (1) Compared to the benchmark model (ensemble XAJ model), the hybrid model with additional residual analysis show a significant improvement. The average continuous ranked probability score (CRPS) metric values calculated by the Stacking-Hybrid model improved by 71.5 %, 67.0 % and 38.1 % in the three data samples. Furthermore, the adaptability of the Stacking-Hybrid model for residual correction during short-duration intense rainfall events has been validated, with the relative error of the peak discharge improved to within ± 10 %. (2) The Stacking-Hybrid model, which also takes into account structure uncertainty, is able to better exploit the combined advantages and improve the stability of the model performance compared to those that only apply a single DDM. (3) When the number of iterations within the BOA reaches 300, the parameter optimization process is capable to search for the hyperparameters that bring out the best performance of the DDMs. (4) When the ensemble size reaches 200, the uncertainty of HM parameters can be fully defined, and the consumed computational resources can be controlled within an acceptable bound while ensuring stable model performance. Overall, the hybrid model that takes into account multiple sources of uncertainty generates both interval and probabilistic forecast in addition to deterministic forecast, which can provide richer risk information for subsequent flood warning and reservoir operation, making the flood prevention decisions more reliable and scientific.

Seismic and hydrological triggers for a complex cascading geohazard of the Tianmo Gully in the southeastern Tibetan Plateau

On 11th July 2018, a destructive rock-ice avalanche and subsequent glacier debris flow occurred in the Tianmo Gully in the southeastern Tibetan Plateau (SETP). However, the source area and triggering factors of this cascading geohazard event remained unclear. In this study, we combined satellite remote sensing, meteorological observations, numerical modeling, and post-event field investigation to comprehensively analyze its evolution processes and potential triggers. The remote sensing observations of terrain and landform changes suggest that the initial avalanche occurred on the southeastern flank of the glacier, releasing approximately 2.77 × 106 m3 of lithic and ice material. From our analysis, we suggest that the complex evolution process of this cascading geohazard event could be manifested as earthquake and hydrological triggers → an initial rock-ice avalanche → glacial debris flow → triggered landslides → landslide dam → dammed lake. Our results suggest that the 2017 Ms. 6.9 Nyingchi earthquake, the unusually high meltwater from snow and ice during the abnormally warm and dry summer in 2018, and the short-duration intense rainfall (22 mm on 10 July) recorded one day before the event are the three main factors for the catastrophic event. These factors caused the rock-ice avalanche in the source zone and subsequently cascaded glacial debris flow and shallow landslides. This study highlights the urgent need for regular monitoring of high-risk glaciers, including anomalous changes in temperature and precipitation, and accelerated movements of glaciers due to earthquakes, especially in the SETP, where climate warming will be expected to intensify occurrences of such cascading geohazard events in the future.

A comparison study on the role of urbanization in altering the short-duration and long-duration intense rainfall

Urbanization has significantly changed the regional hydrological cycle and energy balance. However, the different roles of urbanization on intense rainfall with short and long persistence need a better understanding, particularly in coastal mega cities with complex terrains. In this study, we compared the spatial and diurnal characteristics of intense rainfall across two coastal cities with different degrees of urbanization with 70 meteorological stations. The effects of anthropogenic and geographical factors on short-duration intense rainfall (SDIR) and long-duration intense rainfall (LDIR) were investigated using the statistical method. SDIR and LDIR events show different spatial patterns that SDIR events center in the highly urbanized regions while LDIR events center in the coastal mountainous regions. In terms of diurnal features, it is found that the higher occurrence frequency of SDIR in the dense urban region than that in suburbs occurs over the period with strong urban heat island intensity (UHII). It indicated that thermal contrast between urban and suburbs breeds an atmospheric environment for inspiriting the convection and SDIR events. The urban-induced increase in SDIR events depended on urbanization stages, with only dense urban regions showing a significant influence. The results of geographical detector model (GDM) also demonstrated that the synergy of build-up area and population explained 48 %–51 % of spatial heterogeneity of SDIR. Nevertheless, urbanization has little effect in modifying the diurnal features of LDIR events, while it might influence spatial rainfall patterns by enhancing rainfall peaks. The GDM results indicated that terrain positively dominates the spatial distribution for LDIR events, and the interactions of multi-factors (terrain, urbanization, or distance to the coast et al.) have enhanced explanatory power (q values up to 0.70). The results provide a fundamental understanding for the effects of anthropogenic and geographical factors on different types of rainfall events in coastal mega cities.

Impact of Lidar Data Assimilation on Simulating Afternoon Thunderstorms near Pingtung Airport, Taiwan: A Case Study

This study focused on improving the forecasting of the afternoon thunderstorm (AT) event on 5 August 2018 near Pingtung Airport in southern Taiwan through a three-dimensional variational data assimilation system using Doppler lidar-based wind profiler data from the Weather and Research Forecast model. The assimilation of lidar wind profiler data had a positive impact on predicting the occurrence and development of ATs and wind fields associated with the local circulations of the sea–land breeze and the mountains. Evaluation of the model quantitative precipitation forecast by using root-mean-square error analysis, Pearson product–moment correlation coefficient analysis, Spearman rank correlation coefficient analysis, and threat and bias scores revealed that experiments using data assimilation performed much better than those not using data assimilation. Among the experiments using data assimilation, when the implementation time of assimilation of the wind profiler data in the model was closer to the occurrence time of the observed ATs, the forecast performance greatly improved. Overall, our assimilation strategy has crucial implications for the prediction of short-duration intense rainfall caused by ATs with small temporal and spatial scales of few hours and a few tens of kilometers. Our strategy can help guarantee the flight safety of aircraft.

Internal variability and temperature scaling of future sub-daily rainfall return levels over Europe

The range of sub-daily extreme precipitation due to internal variability is quantified within the single model initial-condition large ensemble featuring 50 members of the Canadian regional climate model, version 5 (CRCM5) under the high-emission scenario representative concentration pathway 8.5. Ten-year return levels of sub-daily precipitation are calculated for three future periods (2010–2039, 2040–2069, 2070–2099) and hourly to 24-hourly aggregations over a European domain. The return levels are found to increase by 4%–8% for every future 30 year period averaged for the study area, where short-duration rainfall intensities increase to a greater extent than longer-duration rainfall intensities. The ranges between the median of the 50 members and the 5th and 95th quantile amount to −15.6%–19.3%, −16.0%–20.1%, and −16.5%–20.9% for the near, mid and far future, respectively. It is also shown that the scaling of the precipitation increase with temperature (Clausius–Clapeyron scaling) exhibits substantial variations between the 50 CRCM5 members at regional aggregations. These findings illustrate the large impact of internal variability on the uncertainty of extreme precipitation return level estimates. Here, regions of significant changes are identified, where future median extreme precipitation exceeds the 95th quantile of the reference period (1980–2009). These regions are located in northern Europe, central Europe and the eastern part of the Mediterranean.

Analysis of Flooding Adaptation and Groundwater Recharge After Adopting JW Ecological Technology in a Highly Developed Urbanization Area

The relationship between Taiwan’s groundwater resources recharge strategy and flood disasters is significant. The adaptation strategies of traditional urbanization areas simulate the spatial distribution of permeable pavements under different rainfall intensities that affect surface runoff and infiltration. Since there are many parameters of the Stormwater Management Model set in different low-impact development modules, this study refers to transform the inundation to groundwater recharge. In this study, we simulated the spatial distribution multi-advantages of the JW ecological technology under short-duration intense rainfall events. The results show that the application of JW ecological technology can effectively increase groundwater resources by 64.1% through infiltration and reduce economic losses by about NTD 1.25 million under the rainfall event of 112 mm/1 h. The infiltration replenishment amount was about 61%, which could reduce the economic loss of NTD 4.4 million under the rainfall event of 350 mm/6 h. Thus, applying JW ecological technology in a highly developed urbanization area can effectively reduce surface runoff and economic losses. At the same time, the issue of water resources was adapted by the groundwater recharge.

A Temperature-Scaling Approach for Projecting Changes in Short Duration Rainfall Extremes from GCM Data

Current and future urban flooding is influenced by changes in short-duration rainfall intensities. Conventional approaches to projecting rainfall extremes are based on precipitation projections taken from General Circulation Models (GCM) or Regional Climate Models (RCM). However, these and more complex and reliable climate simulations are not yet available for many locations around the world. In this work, we test an approach that projects future rainfall extremes by scaling the empirical relation between dew-point temperature and hourly rainfall and projected changes in dew-point temperature from the EC-Earth GCM. These projections are developed for the RCP 8.5 scenario and are applied to a case study in the Netherlands. The shift in intensity-duration-frequency (IDF) curves shows that a 100-year (hourly) rainfall event today could become a 73-year event (GCM), but could become as frequent as a 30-year (temperature-scaling) in the period 2071–2100. While more advanced methods can help to further constrain future changes in rainfall extremes, the temperature-scaling approach can be of use in practical applications in urban flood risk and design studies for locations where no high-resolution precipitation projections are available.

Exploring the use of underground gravity monitoring to evaluate radar estimates of heavy rainfall

Abstract. The radar-based estimation of intense precipitation produced by convective storms is a challenging task and the verification through comparison with gauges is questionable due to the very high spatial variability of such types of precipitation. In this study, we explore the potential benefit of using a superconducting gravimeter as a new source of in situ observations for the evaluation of radar-based precipitation estimates. The superconducting gravimeter used in this study is installed in Membach (BE), 48 m underneath the surface, at 85 km distance from a C-band weather radar located in Wideumont (BE). The 15-year observation record 2003–2017 is available for both gravimeter and radar with 1 and 5 min time steps, respectively. Water mass increase at ground due to precipitation results in a decrease in underground measured gravity. The gravimeter integrates soil water in a radius of about 400 m around the instrument. This allows capture of rainfall at a larger spatial scale than traditional rain gauges. The precision of the gravimeter is a few tenths of nm s−2, 1 nm s−2 corresponding to 2.6 mm of water. The comparison of reflectivity and gravity time series shows that short-duration intense rainfall events produce a rapid decrease in the underground measured gravity. A remarkable correspondence between radar and gravimeter time series is found. The precipitation amounts derived from gravity measurements and from radar observations are further compared for 505 rainfall events. A correlation coefficient of 0.58, a mean bias (radar–gravimeter)/gravimeter of 0.24 and a mean absolute difference (MAD) of 3.19 mm are obtained. A better agreement is reached when applying a hail correction by truncating reflectivity values to a given threshold. No bias, a correlation coefficient of 0.64 and a MAD of 2.3 mm are reached using a 48 dBZ threshold. The added value of underground gravity measurements as a verification dataset is discussed. The two main benefits are the spatial scale at which precipitation is captured and the interesting property that gravity measurements are directly influenced by water mass at ground no matter the type of precipitation: hail or rain.

Estimation of short-duration rainfall intensity from daily rainfall values in Klang Valley, Malaysia

Data on intensity–duration–frequency or design rainfall are one of the most important information required for various hydrological and water resources studies. However, such crucial data are often unavailable in various parts of the world due to lack of enough rain gauging stations. It is not only tedious to determine design rainfall from the raw data but also occasionally impossible to calculate due to lack or absence of short-duration rainfall data. Generally, the manual rain gauges outnumber the automatic gauges, making it difficult to have adequate data on short-duration rainfall values, which is very important for urban hydrology. However, no graphical or mathematical relation could be found in the literature, which can be used for quick estimation of short-duration design rainfall from the daily rainfall data recorded by the manual stations. Annual maximum rainfall data from 143 rain gauging stations located at Klang Valley in Malaysia were used in this study. Statistical analyses and logarithmic graph fitting techniques were used to develop excellent correlation between short-duration rainfall and daily rainfall values for 96 automatic and 46 manual stations. Rainfall data analyze the design rainfall data of various duration and return periods. The 15, 30 and 45 min of short-duration rainfall, which is the most common rainfall duration in the study area, was observed to be 32.4%, 47.1% and 57.4% of the daily rainfall amount, respectively. The amount of rainfall during 1-, 2- and 3-h storm events contribute 64.9%, 76.5% and 80.9% of the daily rainfall. Such relations can be used for quick estimation of short-duration rainfall resulting in saving time, money and other resources.

When Will We Detect Changes in Short-Duration Precipitation Extremes?

The question of when the influence of climate change on U.K. rainfall extremes may be detected is important from a planning perspective, providing a time scale for necessary climate change adaptation measures. Short-duration intense rainfall is responsible for flash flooding, and several studies have suggested an amplified response to warming for rainfall extremes on hourly and subhourly time scales. However, there are very few studies examining the detection of changes in subdaily rainfall. This is due to the high cost of very high-resolution (kilometer scale) climate models needed to capture hourly rainfall extremes and to a lack of sufficiently long, high-quality, subdaily observational records. Results using output from a 1.5-km climate model over the southern United Kingdom indicate that changes in 10-min and hourly precipitation emerge before changes in daily precipitation. In particular, model results suggest detection times for short-duration rainfall intensity in the 2040s in winter and the 2080s in summer, which are, respectively, 5–10 years and decades earlier than for daily extremes. Results from a new quality-controlled observational dataset of hourly rainfall over the United Kingdom do not show a similar difference between daily and hourly trends. Natural variability appears to dominate current observed trends (including an increase in the intensity of heavy summer rainfall over the last 30 years), with some suggestion of larger daily than hourly trends for recent decades. The expectation of the reverse, namely, larger trends for short-duration rainfall, as the signature of underlying climate change has potentially important implications for detection and attribution studies.

Rainfall Intensity-Duration-Frequency relationship for Trichy and Kumulur

The rainfall Intensity-Duration-Frequency (IDF) relationship is commonly required for planning and designing of various water resource projects. It is a mathematical relationship between the rainfall intensity, duration and return period. This relationship is determined through statistical analysis of recorded rainfall data. The objective of this study is to derive IDF relationship of rainfall at Trichy and Kumulur. A total durations ranging from 10 minutes to 24 hr (10min, 20 min, 30 min, 60 min, 120 min, 180 min, 360 min, 720 min and 1440 min) for return periods of 2, 5, 10, 25, 50 and 100 years were analyzed. In this study, yearly maximum rainfall data for Trichy (1951–2010) and Kumulur (1991–2014) were used. Empirical reduction formula of India Meteorological Department (IMD) has been used to estimate the short duration rainfall intensity from yearly maximum rainfall data. Gumbel and Log Pearson Type III (LPT III) Distribution method was used to develop IDF curves and equations. The results obtained using Gumbel method is somewhat higher than the outcomes obtained using the LPT III distribution method. The chi-square goodness of fit test was used to determine the best fit probability distribution. The parameters of the IDF equations and coefficient of correlation for different return periods (2, 5, 10, 25, 50 and 100 years) were calculated by using least square method. The results obtained revealed that in all the cases the correlation coefficient is very high representing the goodness of fit of the formulae to estimate IDF in the station of interest.

Evidence for a Strong Association of Short-Duration Intense Rainfall with Urbanization in the Beijing Urban Area

AbstractCorrelations of the urban heat island intensity (UHII) and key surface variables with the short-duration intense rainfall (SDIR) events are examined for the Beijing urban areas by applying hourly data of a high-density automatic weather station (AWS) network. Higher frequencies (amounts) of the SDIR events are found in or near the central urban area, and most of the SDIR events begin to appear in late evening and nighttime, but tend to end in late night and early morning. Correlations of the UHII with the SDIR frequency (amount) are all highly significant for more than 3 h ahead of the beginning of the SDIR events. Although the UHII at immediate hours (<3 h) before the SDIR occurrence is more indicative of SDIR events, their occurrence more depends on the magnitude of the UHII at earlier hours. The UHII before the beginning of the SDIR events also shows high-value centers in the central urban area, which is generally consistent with the distribution of the SDIR events. The spatial and temporal patterns of regional SDIR events exhibit similar characteristics to the site-based SDIR events and also show a good relationship with the UHII in the urban areas. In addition to the UHII over the urban areas, surface air temperature, surface air pressure, relative humidity, and near-surface wind directions at the Beijing station experience large changes before and after the beginning time of regional SDIR events, and have the potential to indicate the occurrence of SDIR events in the studied area.

Daily rainfall disaggregation for Tocantins State, Brazil

In order to design effective Brazilian hydraulic structures, it is necessary to obtain data relating to short-duration intense rainfall from historical series of daily rainfall. This recurring need can be fulfilled by rainfall disaggregation methodology. The objective of this study was to determine the intense rainfall disaggregation constants for the State of Tocantins and to compare these constants with those obtained for other regions of Brazil. For the modeling of the frequency of intense rainfall of different durations of less than 24 hours, the Gumbel probability distribution (GPD) was employed using rainfall series from 10 locations in Tocantins state. The results showed that the GPD was adequate by the Kolmogorov-Smirnov and Chi-square tests. The disaggregation constants presented low variability values for different return periods (from 10 to 100 years); the values for Tocantins state are: h12h/h24h=0.93, h6h/h24h=0.86, h4h/h24h=0.82, h3h/h24h=0.78, h2h/h24h=0.72, h1h/h24h=0.61, h50min/h1h=0.92, h40min/h1h=0.83, h30min/h1h=0.68, h20min/h30min=0.76 e h10min/h30min=0.46. The comparison of the results with those from studies developed for other Brazilian regions showed variations of up to -62.30%, allowing us to conclude that the use of local constants is important in the process of rainfall disaggregation.

Modeling of Short Duration Rainfall Intensity Duration Frequency(SDR-IDF) Equation for Basrah City

The Rainfall Intensity-Duration-Frequency (IDF) relationship is one of the most commonly used tools in water resources engineering, either for planning, designing and operating of water resource projects or for various engineering projects against floods. The objective of this study is to develop an empirical formula to estimate rainfall intensity for any duration and any return period with minimum effort. Daily rainfall data for years 1980-2010 from Iraqi Metrological Organization and Seismology was used in this study. Hershfeildʼs method was used to estimate the short duration rainfall intensity from daily rainfall data. Various distribution functions were used for analysis and Chi-Square goodness to fit test were used to identify the best statistical distribution among them. Study showed that Log Pearson type III is the best probability distribution and the best (IDF)empirical formula was in the form [i=a/(b=td)]

Investigation into increasing short-duration rainfall intensities in South Africa

Extreme storms in South Africa and specifically in the Western Cape have been responsible for widespread destruction to property and infrastructure, even leading to displacement and death. The occurrences of these storms have been increasingly linked to human-induced climate change that is expected to cause more variable weather. Studies on climate circulation models for future climate conditions project that rainfall in the Western Cape and wider South African region is to become more intense and extreme. Sub-daily rainfall for 3 stations in the Western Cape and 4 stations in the rest of South Africa were analysed in order to determine if any trends towards more intense and extreme rainfall are observed and whether the trend is unique to the Western Cape or indicates a wider trend. This study explores this expectation by using historical short-duration rainfall (less than 24 h) for 7 stations in the Western Cape and South African region. Digitised autographic and automatic weather station 5-min rainfall data were combined to extend the effective record length. Both the magnitude and frequency of occurrence of rainfall events were analysed to assess if rainfall intensities are showing any evidence of increasing over time. For the magnitude of rainfall events, extreme value theory was applied to non-stationary sequences, using both a parametric and non-parametric approach for both event maxima and peaks over threshold modelling. The frequency analysis entailed measuring the frequency of exceedance of rainfall events over a certain threshold value. Both the magnitude and frequency analysis indicated that the combination of the two record types influenced the results of some of the stations, while the others showed no consistent evidence of changing rainfall intensities. This led to the conclusion that, from the available observed short-duration record, no evidence was found of trends or indications of changes in rainfall intensities. Keywords : climate change, short duration rainfall, extreme value theory, non-stationary

Analysis of effects of climate change on runoff in an urban drainage system: a case study from Seoul, Korea.

Both water quantity and quality are impacted by climate change. In addition, rapid urbanization has also brought an immeasurable loss of life and property resulting from floods. Hence, there is a need to predict changes in rainfall events to effectively design stormwater infrastructure to protect urban areas from disaster. This study develops a framework for predicting future short duration rainfall intensity and examining the effects of climate change on urban runoff in the Gunja Drainage Basin. Non-stationarities in rainfall records are first analysed using trend analysis to extrapolate future climate change scenarios. The US Environmental Protection Agency Storm Water Management Model (SWMM) was used for single event simulation of runoff quantity from the study area. For the 1-hour and 24-hour durations, statistically significant upward trends were observed. Although the 10-minute duration was only nearly significant at the 90% level, the steepest slope was observed for this short duration. Moreover, it was observed that the simulated peak discharge from SWMM increases as the short duration rainfall intensity increases. The proposed framework is thought to provide a means to review the current design of stormwater infrastructures to determine their capacity, along with consideration of climate change impact.

Extreme rainfall relationship in Mexico

Precipitation statistics are inherent to the design of water resource systems by the prediction of two aspects of hydrological processes: the extremes and the averages. Extreme rainfall with high temporal resolution (i.e. an hour or less) is necessary for the design of urban drainage systems, as urban areas are generally characterized by their fast response. However, most weather stations only register daily rainfall. The relationship between the hourly intensity of rain and the daily rain intensity is called parameter K. Thus, if extreme daily rainfall data is available, the parameter K allows the estimation of extreme short-duration rainfall intensities. This study offers a map with the regionalization of the relationship between the maximum intensities of precipitation occurring over intervals 1 and 24 hours (parameter K) for the whole country of Mexico, facilitating the description of the geographical variability of precipitation. In this country a high spatial variability of the parameter K was observed, according to the large area studied.

Short-duration intense rainfall in the wards of Tokyo and its relationship with the spatial distribution of buildings

Short-duration intense rainfall in the wards of Tokyo and its relationship with the spatial distribution of buildings